JP4277858B2 - Information display control device and program - Google Patents

Description

  The present invention relates to an information display control device and a program for performing control to display an example sentence using a headword that matches an input word.

  Conventionally, an information display control device called an electronic dictionary in which several types of electronic dictionary data are incorporated, such as a Japanese language dictionary, an English-Japanese dictionary, a Japanese-English dictionary, an English-English dictionary, and an encyclopedia, is known. One of the functions provided in the electronic dictionary is an example sentence search function.

For example, the headword “look” and the explanation information that is the meaning content are associated with each other and stored in an English-Japanese dictionary database (hereinafter, the database is referred to as “DB”), but the headword “look” is included in the explanation information. "Is included. The example sentence search function is a function for searching and displaying an example sentence in which a desired word is used from example sentences included in such a dictionary DB. As a technique for speeding up example sentence search, for example, the technique of Patent Document 1 is known.
JP 2001-134567 A

  However, even if the conventional example sentence search function is speeded up using the technique described in Patent Document 1, there are the following inherent problems. That is, for example, when the user performs an example sentence search using “look” and “up” as search terms, an example sentence including “look” and “up” is simply searched and displayed, so that “She came up Example sentences not directly related to “look” or “up” such as “for a look at the new boy.” will be displayed.

  If the example sentence displayed using the example sentence search function is 2 to 3 examples that fit within one screen, the user has less time to search for the desired example sentence, but dozens of example sentences that cannot fit within one screen. If is displayed, it may even cause a feeling of frustration. In particular, in recent years, a so-called full content type electronic dictionary in which a paper dictionary is entirely digitized has come to be used frequently. In this electronic dictionary, there is a large amount of explanation information for one headword, and a large number of example sentences are stored in proportion to this. Therefore, there are many cases where dozens of example sentences are searched and displayed by the example sentence search function. In such a case, the user needs to check the contents of the example sentences and scroll them.

  An object of the present invention is to search and display an example sentence suitable for a word input as a search word in an example sentence search in an information display control device such as an electronic dictionary.

In order to solve the above problems, an information display control device according to the first aspect of the present invention provides:
Dictionary information storage means for storing an entry word and explanation information of the entry word in association with each other;
First input means for inputting a word in response to a user operation;
Dictionary information display control means for performing control to extract and display the description information having the word input by the first input means as a headword from the dictionary information storage means;
In an information display control device comprising:
Example sentence storage means for storing an example sentence in association with the source headword of the example sentence;
Words, the example sentence word storage means for storing in association with example sentences stored in the example sentence storage means, including the word,
A word-level storage means for storing the level of each word set in advance,
Second input means for inputting a plurality of words in response to a user operation,
Extraction means for extracting the example sentence including all the plurality of words inputted from the example sentence stored in correspondence with the example sentence word storage means by the second input means,
Processing button display control means for performing control to display a button corresponding to each of a plurality of processes;
A selection means for selecting an arbitrary button whose display is controlled by the processing button display control means according to a user operation;
When the button corresponding to the word level assigning process by the selection means is selected, according to the order of the highest level or the lowest level of the level of each word included in each example sentence extracted by the extraction means, to display and word-level order display control means for controlling the order of the sentence,
It is characterized by providing.

Further, the program of the invention described in claim 7 stores dictionary information storage means for storing a headword and explanation information of the headword in association with each other, and stores an example sentence in association with the source headword of the example sentence. example sentence storage means for, words, and sentence word storage means for storing in association with example sentences stored in the example sentence storage means containing the words, and word-level storage means for storing the level of each word that is set in advance On a computer with
A first input function for inputting a word in response to a user operation;
Dictionary information display control function for performing control to extract and display the description information having the word input by the first input function as a headword from the dictionary information storage means;
A second input function of inputting a plurality of words in response to a user operation,
An extraction function for extracting an example sentence including all of the plurality of words input by the second input function from example sentences stored in association with the example sentence word storage unit;
A process button display control function for performing control to display a button corresponding to each of a plurality of processes;
A selection function for selecting an arbitrary button whose display is controlled by the processing button display control function according to a user operation;
When the button corresponding to the word level assigning process by the selected function is selected, in order of the highest level or the lowest level of the level of each word included in each example sentence extracted by the extraction function, and displays and word-level order display control function to control the order of the sentence,
It is characterized by realizing.

According to the first or seventh aspect of the present invention, an example sentence including a plurality of words input as search words by the extraction means or the extraction function is extracted. The word level order display control means or the word level order display control function follows a certain rule of the order of the highest level or the lowest level among the levels of each word included in the example sentence extracted by the extraction means . The display of example sentences can be controlled in a regular order. Therefore, for example, when the retrieved example sentence does not fit on one screen, the user needs to confirm the contents of each example sentence by sequentially performing a scroll operation or the like. However, since display control is performed in an array according to a certain rule, it is possible to realize more appropriate example sentence display control that is easy for the user to understand and understand.

  Hereinafter, an embodiment in which the present invention is applied to an electronic dictionary which is a kind of information display control device will be described in detail with reference to the drawings with reference to FIGS. 1 to 18, but the present invention is applicable. The thing is not limited to this.

  The electronic dictionary incorporates various electronic dictionary data (dictionary database) such as Japanese language dictionary, English-Japanese dictionary, Japanese-English dictionary, proverb dictionary. In this dictionary database (hereinafter, the database is referred to as “DB”), explanatory data such as character data, image data, moving image data, audio data, and the like for explaining the headword is stored in association with the headword. Is done. By selecting a dictionary type and inputting a word, the user can display an explanation of the word. In the following description, the electronic dictionary includes an English-Japanese dictionary DB.

  FIG. 1 shows an overview of the electronic dictionary 1. As shown in the figure, the electronic dictionary 1 includes a display 3 and various key groups 5. Here, each key constituting the various key groups 5 is assigned with a unique function, and the user operates the electronic dictionary 1 by pressing these keys. Specifically, various key groups 5 are provided with a character input key, a dictionary type selection key, a jump key to a designated word, an example display key for a designated word, and the like. The function assigned to the key can be executed. For example, when the English-Japanese dictionary button is pressed, the mode is switched to the English-Japanese dictionary mode, and a search in the English-Japanese dictionary DB can be executed.

  FIG. 2 is a block diagram showing the configuration of the electronic dictionary 1. As shown in the figure, the electronic dictionary 1 is composed of a CPU (Central Processing Unit) 10, a ROM (Read Only Memory) 20, a RAM (Random Access Memory) 30, an input unit 40, and a display unit 50. .

  The CPU 10 executes processing based on a predetermined program in accordance with an input instruction, and transfers instructions and data to each function unit. Specifically, the CPU 10 reads a program stored in the ROM 20 in accordance with an operation signal input from the input unit 40, and executes processing according to the program. Then, a display signal for displaying the processing result is appropriately output to the display unit 60 to display the corresponding display information.

  The CPU 10 executes an example sentence search process in accordance with an example sentence search program 24 described later stored in the ROM 20. The details of the example sentence search process will be described later, but the outline is as follows. First, the CPU 10 causes the display unit 50 to display an input screen for inputting a search term and a condition for extracting example sentences. Then, when a search phrase composed of a plurality of words and a condition for extracting an example sentence are input by the user, an example sentence including the search phrase is searched from the English-Japanese dictionary DB 22, and the example sentence is displayed on the display unit 50 according to the input condition. indicate.

  The ROM 20 stores an initial program for performing various initial settings, hardware inspections, loading of necessary programs, and the like. The CPU 10 sets the operating environment of the electronic dictionary 1 by executing this initial program when the electronic dictionary 1 is powered on.

  The ROM 20 stores various processing programs for the operation of the electronic dictionary 1 such as menu display processing, various setting processing, various search processing, and programs for realizing various functions provided in the electronic dictionary 1. In addition, an English-Japanese dictionary DB 22 is stored. In addition, an example sentence search program 24 is stored as a program.

  The English-Japanese dictionary DB 22 includes a headword table 222, an example sentence table 224, a word example sentence table 226, a variation table 228, and a word level table 230. In addition, the example sentence search program 24 stores a headword limitation program 242, a word level designation program 244, an example sentence difficulty designation program 246, and a collocation importance designation program 248.

  FIG. 3A is a diagram showing an example of the data configuration of the headword table 222. The headword table 222 includes a headword 222a (for example, “get”) and explanatory information 222b indicating the meaning of the headword (for example, “[transition] 1a <person> obtains <thing / thing>”. "..." and example sentence number 222c, which is identification information for identifying example sentences included in the explanation information, are stored in association with each headword.

  The headword table 222 is a data table in which basic data of the English-Japanese dictionary DB 22 is stored. When a search word is input in the English-Japanese dictionary mode, a headword that matches the search word is read and the headword is stored in the headword. Displayed with corresponding explanation information. For example, in FIG. 3A, the description information “[transition] 1a <person> obtains <things / things>, obtain ...” of the headword “get” is displayed on the display unit 50. If there is an example corresponding to the displayed headword, an example sentence of the example is read and displayed in accordance with a predetermined operation. In FIG. 3A, the example sentences with the example sentence numbers “172” and “198” are read and displayed.

  FIG. 4A is a diagram illustrating an example of a data configuration of the example sentence table 224. The example sentence table 224 stores an example sentence number, an example sentence corresponding to the example sentence number, a source entry word, an example sentence difficulty level, and a collocation importance level in association with each other. Also, the meaning of example sentences is stored.

  The source headword indicates which headword in the headword table 222 is associated with the example sentence. For example, the example sentence “It looks [sounds] like the...” Of the example sentence number “126” is stored in association with the entry word “like” in the entry word table 222.

  The example sentence difficulty level is information indicating the difficulty level of the example sentence. The example sentence at the easiest level is A, the example sentence at the next easiest level is B, and the following is in alphabetical order. In addition, when comparing level A and level B, level A is treated as being larger, and hereinafter, it is assumed that B, C, D,... For example, when comparing the example sentence of the example sentence number “153” with the example sentence of the example sentence number “156”, the example sentence difficulty level of the example sentence number “153” is “A”, and the example sentence difficulty level of the example sentence number “156” is Since it is “B”, the example sentence number “153” is larger in the magnitude relation. However, it goes without saying that the electronic dictionary 1 may be configured with the magnitude relationship reversed.

  The collocation importance indicates the level of importance of collocations included in the example sentence. Each example sentence is stored in order from the most important one, and no value is stored when there is no collocation. For example, in the example sentence number “024”, there are two collocations “so that” and “look like”, but since “look like” is stored second, the collocation importance is “B”. On the other hand, since the example sentence number “126” is stored first, the collocation importance is “A”. In addition, when comparing level A and level B, level A is treated as being larger, and hereinafter, it is assumed that B, C, D,... However, it goes without saying that the electronic dictionary 1 may be configured with the magnitude relationship reversed.

  FIG. 4B is a diagram showing an example of the data configuration of the word example sentence table 226. The word example sentence table 226 stores a word and an example sentence number of an example sentence including the word in association with each other.

  FIG. 3B is a diagram showing an example of the data configuration of the variation table 228. The variation table 228 stores a variation associated with each original word. Here, the original word may be an original word or a changed word such as a past word. In addition, the variation forms differ depending on the part of speech of the original word, such as a verb, adjective, and pronoun. For example, in the case of a verb, the original form of the verb, the third person singular form with the third person singular “s” added to the original form of the verb, the past form, the past participle form, the present progressive form, etc. are stored. For example, as shown in FIG. 3B, in the case of “get”, “get, gets, got, getting, gotten” and the like are associated and stored. The relationship between the original word associated here and the modified word is referred to as an “equivalent” relationship. For example, “get” and “got” are equivalent words.

  FIG. 3C is a diagram showing an example of the data configuration of the word level table 230. The word level table 230 stores a word and a level indicating the difficulty level of the word in association with each other. The level of difficulty increases in alphabetical order as A, B, C,. In addition, when comparing level A and level B, level A is treated as being larger, and hereinafter, it is assumed that B, C, D,...

  The example sentence search program 24 is a program for causing the CPU 10 to execute an example sentence search process in which an example sentence is searched from the English-Japanese dictionary DB 22 based on a search term and a specified condition input by a user and displayed on the display unit 50.

  The headword limiting program 242 is a subroutine program included in the example sentence search program 24, and selects, from the example sentences once extracted, an example sentence in which the search word included in the search phrase and the source headword of the example sentence are equivalent. This is a program for causing the CPU 10 to execute a possible headword limiting process. Here, the search word means each word when a plurality of words are input as a search phrase. A group of a plurality of input search words is called a plurality of search terms. The term “search phrase” simply refers to a phrase that is input for a search by the user, and includes both a case where the word is composed of a single word and a case where the word is composed of a plurality of words (that is, a plurality of search phrases).

  The word level designation program 244 is a subroutine program included in the example sentence search program 24, and causes the CPU 10 to execute a word level designation process for extracting example sentences based on a designated word level from once extracted example sentences. It is a program.

  The example sentence difficulty level designation program 246 is a subroutine program included in the example sentence search program 24, and executes, in the CPU 10, an example sentence difficulty level designation process for selecting an example sentence from extracted example sentences according to the difficulty level of the designated example sentence. It is a program to make it.

  The collocation importance level designation program 248 is a subroutine program included in the example sentence search program 24, and executes a collocation importance level designation process for selecting an example sentence from extracted example sentences according to the importance level of the designated collocations. It is a program to make it.

  The RAM 30 includes a memory area that temporarily holds various programs executed by the CPU 10 and data related to the execution of these programs. In the present embodiment, a search phrase storage area 302, an example sentence number storage area 304, a first work area 306, a second work area 308, and a third work area 310 are provided.

  The search phrase storage area 302 stores the search phrase input by the input unit 40. The example sentence number storage area 304 stores a list of extracted example sentence numbers. In the first work area 306, the second work area 308, and the third work area 310, data temporarily used in each program is stored.

  The input unit 40 is an input device having a key group necessary for character input such as kana and alphabets, function selection, and the like, and outputs a pressed key signal to the CPU 10. By means of key input in the input unit 40, input means such as input of a search phrase, selection of a dictionary mode, and search execution instruction are realized. The input unit 40 corresponds to the key group 5 shown in FIG. The input unit 40 is not limited to the key group 5, and may be a touch panel or the like.

  The display unit 50 displays various screens based on display signals input from the CPU 10, and is configured by an LCD (Liquid Crystal Display) or the like. The display unit 50 corresponds to the display 3 shown in FIG.

Next, the operation of the electronic dictionary 1 will be described.
FIG. 5 is a flowchart for explaining the operation of the example sentence search process executed by the CPU 10 according to the example sentence search program 24, and the flow of the example sentence search process will be described with reference to FIG.

  First, when a search phrase is input by the user into the search phrase input area P100 (step A12; Yes), the input search phrase is stored in the search phrase storage area 302 (step A14).

  Then, the first search word of the input search phrase is selected (step A16), and the example sentence number corresponding to the search word is extracted from the word example sentence table 226 and stored in the first work area 306 (step A18). Next, when the search word still remains (step A20; No), the next search word is selected (step A22), and the same processing is performed. After extraction of example sentence numbers for all search words is completed (step A20; Yes), common numbers of example sentence numbers for each search word are extracted and stored in the example sentence number storage area 304 (step A24).

  For example, when “look & like” is input as a search phrase, the first search word is “look” and the next search word is “like”. First, the CPU 10 extracts “..., 6,..., 24,. Next, “..., 24,..., 48,...” That are example sentence numbers corresponding to “like” are extracted from the word table 266 and stored in the first work area 306. Information stored in the first work area 306 at this time is as shown in FIG.

  Next, the CPU 10 extracts example sentence numbers common to all search words from the example sentence numbers stored in the first work area 306 for the search words, and stores the example sentence numbers in the example sentence number storage area 304. . For example, from the state of the first work area 306 shown in FIG. 7A, an example sentence number common to each of “like” and “look” is extracted. Here, “24,126,153,156,315,...” Is extracted and stored in the example sentence number storage area 304. Information stored in the example sentence number storage area 304 at this time is as shown in FIG.

  Next, CPU10 performs the process according to the process selected by the user (step A26). Here, as a process selected by the user, a headword limiting process (step A28; FIG. 6), a word level designation process (step A30; FIG. 12), an example sentence difficulty designation process (step A32; FIG. 14), There is a multiple word importance designation process (step A34; FIG. 16). Details of each processing content will be described later.

  An example of the input screen in step A26 is shown in FIG. In FIG. 8A, when the user inputs a search phrase into the search phrase input area P100 and selects one of the execution buttons B100, B102, B104, and B106, the CPU 10 executes the selected process. . Specifically, the headword limitation process is performed when the execution button B100 is selected, the word level designation process is performed when the execution button B102 is selected, and the example sentence difficulty level designation process is performed when the execution button B104 is selected. When the execution button B106 is selected, the multiple word importance designation process is executed.

  Next, when there is an overlapping number in the example sentence number stored in the example sentence number storage area 304, the CPU 10 deletes the remaining one number (step A36). In this state, it waits for a user instruction to display an example sentence number or to repeat the processing of steps A28 to A34. At this time, an instruction input may be waited for by window display. When an instruction to repeat the process is input (step A38; Yes), the CPU 10 shifts the process to step A26 and performs the processes of steps A26 to A38 again.

  On the other hand, when an instruction not to repeat is input (step A38; No), the CPU 10 stores the example sentence tables 224 in the order in which the example sentences corresponding to the example sentence numbers stored in the example sentence number storage area 304 are stored. The character string portion equivalent to the search word / phrase stored in the search word / phrase storage area 302 in the character string of the read example sentence is specially displayed and displayed on the display unit 50.

  For example, when the example sentence number “24” is stored in the example sentence number storage area 304, the example sentence table 224 is searched, and “The water...” That is the example sentence of the example sentence number “24” is displayed on the display unit 50. At that time, special display is performed on the character string portion equivalent to the search term. This special display may be in any form as long as the display form is visually different from other parts such as underlining, changing the font, and performing color change display.

  Next, the operation of the electronic dictionary 1 when the user selects the headword limiting process in step A26 of the example sentence search process (FIG. 5) will be described. Specific examples will be described as appropriate using examples of data stored in each storage area of the RAM 30 and display screen examples.

  In step A26 of the example sentence search process (FIG. 5), the search word / phrase is input to the search word / phrase storage area P100 and the execution button B100 is selected on the input screen of FIG. The execution of the program 242 is started, and the headword limiting process is executed.

  In FIG. 6, first, the CPU 10 copies the example sentence number stored in the example sentence number storage area 304 to the second work area 308 (step B10). Next, the first search word is read from the search phrases stored in the search phrase storage area 302 (step B12). Then, one of the example sentence numbers stored in the second work area 308 is selected (step B14). Next, the CPU 10 reads the source entry word of the example sentence corresponding to the selected example sentence number with reference to the example sentence table 224 (step B16), and checks whether the search word and the source entry word are equivalent (step B18). . For example, as described above, the headword limiting process is executed using “look” and “like” as search terms. Then, first, an example sentence number as shown in FIG. 7B is stored in the example sentence number storage area 304.

  The CPU 10 copies the example sentence number stored in the example sentence number storage area 304 to the second work area 308 (step B10). FIGS. 7C and 7I show examples of example sentence numbers stored in the second work area 308 in this state. In the second work area 308, “24, 126, 153, 156, 315,...”, Which are example sentence numbers common to the search word numbers “look” and “like”, are stored. Next, the first search word is read out. Here, since “look” and “like” are input, the first search word is “look”. Next, one of the example sentence numbers stored in the second work area 308 “24” is selected, and the source entry word of the example sentence is read with reference to the example sentence table 224. According to FIG. 4A, the source headword of the example sentence with the example sentence number “24” is “calm”. Then, the CPU 10 compares whether or not the search word “like” is equivalent to the source headword “calm”.

  Returning to FIG. Next, the CPU 10 determines whether or not the search word and the source headword are equivalent with reference to the word level table 230 (step B18). If the search word and the source headword are equivalent (step B18; YES), the corresponding example sentence number is additionally copied at the end of the third work area 310 (step B20). If the search word and the headword are different, the process is not performed (step B18; No).

  If all the example sentence numbers have not been determined (step B22; No), the CPU 10 selects the next example sentence number stored in the second work area 308 and moves to the next example sentence (step B24). ), Steps B16 to B22 are repeated. When the processing has been completed for all example sentence numbers (step B22; Yes), the CPU 10 determines whether or not all search words have been compared. If the search word remains (step B26; No), the CPU 10 repeats the process of steps B14 to B26 for the next search word (step B28), and performs the process for all the search words. (Step B26; Yes), the example sentence number storage area 304 is updated with the example sentence number stored in the third work area 310 (step B30), and the entry word limiting process is terminated.

  When the second work area 308 and the third work area 310 are in the state shown in FIGS. 7C and 7I, “24, 126, 153, 156, 315” is stored in the second work area 308. Does not contain anything. In this state, the CPU 10 first determines whether or not the first search word “look” is equivalent to the source headword. According to the example sentence table 224 of FIG. 4, the example entry numbers “153” and “156” are added to the third work area 310 because the source headwords of the example sentence numbers “153” and “156” are equal to “look”. ((Ii) in FIG. 7C).

  Next, the CPU 10 determines whether or not the search word “like” is equivalent to the source headword. Then, since the source headword of the example sentence number “126” is equal, the example sentence number “126” is added to the end of the third work area 310 ((iii) in FIG. 7C). Then, by using the contents of the third work area 310, the example sentence number storage area 304 is updated (step B30), and the headword limiting process is terminated. Thereafter, the example sentence search process is restarted from step A36. FIG. 8B shows an example of a screen displayed on the display unit 50 as a result at this time. In FIG. 8B, in the order of the input search word, an example sentence of the source headword “look” equivalent to the search word “look” is displayed first, and a source headword “like” equivalent to the search word “like” is displayed. "Is displayed later. In addition, a character string portion equivalent to the search words “look” and “like” is specially displayed T1.

  Next, an example in which “got” and “up” are inputted as search terms and the headword limiting process is executed is shown in FIG. 9B as an example of the example sentence table 224 shown in FIG. Description will be made with reference to an example of the word example sentence table 230.

  Before the headword limiting process, the example sentence number using the search words “got” and “up” is stored in the first work area 306 by the example sentence search process, and the common example sentence number is stored in the example sentence number storage area 304. It is stored (FIGS. 10A and 10B).

  First, in the headword limiting process, the CPU 10 copies the example sentence number stored in the example sentence number storage area 304 to the second work area 308. The figure showing the state at this time is a figure of FIG.10 (c) (i). “36,172,210” is stored in the second work area 308, and nothing is stored in the third work area 310.

  Next, it is determined whether or not the search word is equivalent to the source headword. The determination of whether or not they are equivalent is made with reference to the variation table 226. Specifically, for example, in FIG. 3B showing an example of the variation table 226, “get” is stored as a variation for the original word “got”. Therefore, it is determined that “got” and “get” are equivalent.

  Then, the state of the third work area 310 when the example sentence number having “get” equivalent to the search word “got” as the source entry word is selected with reference to the example sentence table 224 of FIG. 9A is shown. The figure is shown in FIGS. 10 (c) (ii). Next, FIG. 10C and FIG. 10C show a state in which an example sentence number having “up” equivalent to the search word “up” as a source headword is added to the third work area. Then, the CPU 10 updates the example sentence number storage area 304 with the example sentence number stored in the third work area 310. FIG. 11 shows a screen example in which an example sentence is displayed on the display unit 50 using the example sentence number stored in the example sentence number storage area 304. In FIG. 11, an example sentence of the source headword “get” equivalent to the search word “got” is displayed first in the order of the input search words, and an example sentence of the source headword “up” equivalent to the search word “up” is displayed. Is displayed later. A character string portion equivalent to the search words “got” and “up” is specially displayed T1.

  As described above, according to the headword limiting process, only example sentences having search words as source headwords can be displayed, and can be displayed based on the order of the search words. Therefore, it is possible to display an example sentence that is strongly related to the input search word and matches the source entry word of the example sentence, and an appropriate example sentence display can be realized.

  Next, the operation of the electronic dictionary 1 when the word level designation process is selected by the user in step A26 of the example sentence search process (FIG. 5) will be described. Further, as an example of data stored in each storage area of the RAM 30 and an example of a display screen, a case where “look & like” is input in the search phrase input area P100 of FIG. To do.

  In step A26 of the example sentence search process (FIG. 5), after the search word “look & like” is input on the input screen of FIG. 8A, the word level is specified in the pull-down menu P104, and the execution button B102 is selected. Thus, the CPU 10 starts execution of the word level specifying program 244 and executes word level specifying processing. In the word level designation process, the word level to be designated is a level displayed as a junior high school student level, a high school student level, a university student level, etc. in the pull-down menu P104, and the levels “A”, “B”, Level “C”... Is set. In addition, the word level table 230 stores the word level of each word in association with each other. The pull-down menu refers to a menu that allows one item to be selected from a plurality of items.

  In FIG. 12, first, the CPU 10 copies the example sentence number stored in the example sentence number storage area 304 to the second work area 308 (step C10). An example of the contents stored in the second work area 308 at this time is shown in FIGS. Next, the level designated by the user is read (step C12). For example, in the pull-down menu P104 of FIG. 8, since the word level is designated as “high school student”, it is determined that the level “B” corresponding to the high school student level is the level designated by the user. Hereinafter, the level designated by the user is referred to as a designated level.

  Next, the CPU 10 selects one of the example sentence numbers stored in the second work area 308 (step C14), and determines the example sentence word level (step C16). Here, the example word level refers to the difficulty level of the example sentence determined from the word level of each word included in the example sentence, and refers to the smallest word level among the words included in the example sentence. . For example, as shown in FIG. 13B, in the case of the example sentence with the example sentence number “24”, the level read from the word level table 230 is assigned to each word included in the example sentence. Here, calm is at the word level “B”, but all other words are at the word level “A”, so the example sentence word level of this example sentence number “24” is set to “B”. Further, in the case of the example sentence number “153”, since the word level of all the words is “A”, the example sentence word level of this example sentence number “153” is “A”. In the present embodiment, among the word levels of words included in the example sentence, the lowest word level is set as the example sentence word level, but the highest word level may be set as the example sentence word level.

  Next, the CPU 10 compares the example sentence word level with the designated level (step C18). If the example sentence word level is smaller than the designated level, the CPU 10 selects the example sentence number stored in the second work area 308. The selected example sentence number determined to be small is deleted (step C20; Yes). For example, when the user designates the high school student level (level B), the example sentence whose example word level is the university student level (level C) is not displayed.

  Then, the CPU 10 determines whether or not the processing has been performed for all the example sentence numbers. If not (step C22; No), the CPU 10 selects the next example sentence number stored in the second work area 308. The process proceeds to the next example sentence (step C24), and the processes of steps C14 to C22 are repeated. When processing is completed for all example sentence numbers (step C22; Yes), the example sentence numbers stored in the second work area 308 are sorted at the example sentence word level (step C26), and the example sentence number storage area 304 is stored in the example sentence number storage area 304. Update (step C28). For example, even if example sentence numbers are stored in the second work area 308 in the order as shown in FIGS. 13A and 13I in step C10, they are sorted at the example sentence word level in step C26. The example sentence numbers stored in the second work area 308 are updated in the order as shown in FIGS.

  FIG. 13C shows an example of a screen displayed as a processing result based on the updated example sentence number storage area 304. Similar to the processing result screen of the headword limiting process shown in FIG. 8, the character string portion equivalent to the search word is specially displayed T1.

  Note that the determination in step C18 may be “example sentence word level ≠ designated level”, so that the example sentence number of the example sentence that does not have the designated example word level is deleted from the second work area 308. In that case, only example sentences at a specified level can be displayed.

  Thus, according to the word level designation process, an appropriate example sentence can be displayed based on the designated word level. That is, since an example sentence in which a word difficult for the user is used is not displayed, an appropriate example sentence according to the user's intention can be displayed. Also, since the displayed example sentences are also displayed in order of example word levels, for example, the used words are displayed from plain example sentences, and even when a plurality of example sentences are displayed at once. The content confirmation work for each example sentence becomes easy.

  Next, the example sentence difficulty level designation process will be described with reference to the flowchart of FIG. Further, as an example of data stored in each storage area of the RAM 30 and an example of a display screen, a case where “look & like” is input in the search term input area P100 of FIG.

  In step A26 of the example sentence search process (FIG. 5), after the search term “look & like” is input on the input screen of FIG. 8A, the example sentence difficulty level is designated in the pull-down menu P106, and the execution button B104 is selected. As a result, the CPU 10 starts execution of the example sentence difficulty specifying program 246, and execution of the example sentence difficulty specifying process is started. Here, the example sentence difficulty level is a level displayed as A, B, C..., Etc. in the pull-down menu P106, and is set to level “A”, level “B”, level “C”. Has been. Each example sentence difficulty level is stored in association with each example sentence as “example sentence difficulty level” as shown in the example sentence table 224 of FIG.

  In FIG. 14, first, the CPU 10 copies the example sentence number stored in the example sentence number storage area 304 to the second work area 308 (step D10). An example of the contents stored in the second work area 308 at this time is shown in FIGS. Next, the difficulty level designated by the user is read (step D12). For example, in the pull-down menu P106 of FIG. 8, since the example sentence difficulty level is designated as “B”, it is determined that the difficulty level “B” is the difficulty level designated by the user. Hereinafter, the difficulty level designated by the user is referred to as a designated difficulty level.

  Next, the CPU 10 selects one of the example sentence numbers stored in the second work area 308 (step D14) and reads the example sentence difficulty (step D16). Specifically, for example, for the example sentence with the example sentence number “24”, the example sentence difficulty “B” is read with reference to the example sentence table 224 of FIG.

  Next, the CPU 10 compares the example sentence difficulty level with the designated difficulty level, and if the example sentence difficulty level is smaller than the designated difficulty level (step D18; Yes), it is stored in the second work area 308. The selected example sentence number determined to be smaller is deleted from the example sentence numbers (step D20). For example, when the designated difficulty level is “B”, the example sentence with the example sentence difficulty level “C” or “D” is not displayed.

  Then, the CPU 10 determines whether or not all the example sentence numbers have been processed. If not (step D22; No), the CPU 10 selects the next example sentence number stored in the second work area 308. The process proceeds to the process for the next example sentence (step D24), and the processes of steps D14 to D33 are repeated. When the processing is completed for all example sentence numbers (step D22; Yes), the example sentence numbers stored in the second work area 308 are sorted by the example sentence difficulty (step D26), and the example sentence number storage area 304 is stored in the example sentence number storage area 304. Update (step D28). For example, even if example sentence numbers are stored in the second work area 308 in the order shown in FIGS. 15A and 15I in step D10, they are sorted in step D26 at the level of example sentence difficulty. Therefore, the example sentence numbers stored in the second work area 308 are updated in the order as shown in FIGS.

  FIG. 15B shows an example of a screen displayed as a processing result based on the updated example sentence number storage area 304. Similar to the processing result screen of the headword limiting process shown in FIG. 8, the character string portion equivalent to the search word is specially displayed T1.

  Note that, by setting the determination in step D18 as “example sentence difficulty level ≠ designated difficulty level”, it is possible to perform processing for deleting example sentence numbers of example sentences whose example sentence difficulty levels are not designated difficulty levels from the second work area 308. . In that case, it is possible to display only example sentences of the designated difficulty level.

  Thus, according to the example sentence difficulty level designation process, an appropriate example sentence can be displayed based on the designated example sentence difficulty level. That is, since an example sentence that is difficult for the user is not displayed, it is possible to display an example sentence suitable for the user's intention. In addition, since the displayed example sentences are also displayed in the order of the example sentence difficulty levels, for example, the example sentence difficulty levels are displayed from simple example sentences. Even when a plurality of example sentences are displayed at once, The contents confirmation work of each example sentence becomes easy.

  Next, the collocation importance level designation processing will be described with reference to the flowchart of FIG. Further, as an example of data stored in each storage area of the RAM 30 and an example of a display screen, a case where “look & like” is input in the search term input area P100 of FIG.

  In step A26 of the example sentence search process (FIG. 5), after the search word “look & like” is input on the input screen of FIG. 8A, the collocation importance is specified in the pull-down menu P108, and the execution button B106 is selected. As a result, the CPU 10 starts execution of the collocation importance degree designation program 248 and starts execution of the collocation importance degree designation processing. Here, the collocation importance is a level displayed as A, B, C..., Etc. in the pull-down menu P108, and is internally set to level “A”, level “B”, level “C”. Has been. Further, as shown in the example sentence table 224 of FIG. 4A, each collocation importance degree is stored in association with each collocation included in each example sentence as “cold word importance”. Then, among the stored collocation importance, the collocation importance that matches the search word is set as the collocation importance of the corresponding example sentence for the search word.

  In FIG. 16, first, the CPU 10 copies the example sentence number stored in the example sentence number storage area 304 to the second work area 308 (step E10). An example of the contents stored in the second work area 308 at this time is shown in FIGS. Next, the importance specified by the user is read (step D12). For example, in the pull-down menu P108 of FIG. 8, since the collocation importance is designated as “B”, it is determined that the importance “B” is the importance designated by the user. Hereinafter, the importance designated by the user is referred to as designated importance.

  Next, the CPU 10 selects one of the example sentence numbers stored in the second work area 308 (step E14) and refers to the example sentence table 224 to determine the collocation importance of the example sentence (step E16). ). Specifically, for example, for the example sentence with the example sentence number “24”, referring to the example sentence table 224 in FIG. 4A, “look” and “like” input as search phrases are the importance levels for the corresponding example sentence. It is stored as “B”. Therefore, the collocation importance of the corresponding example sentence is determined as “B”.

  Next, the CPU 10 compares the collocation importance of the example sentence with the designated importance, and if the collocation importance of the example sentence is smaller than the designation importance (step E18; Yes), the CPU 10 enters the second work area 308. The selected example sentence number determined to be smaller is deleted from the stored example sentence numbers (step E20). For example, when the designated importance level is “B”, an example sentence whose consecutive word importance level is “C” or “D” is not displayed.

  Then, the CPU 10 determines whether or not all the example sentence numbers have been processed. If not (step E22; No), the CPU 10 selects the next example sentence number stored in the second work area 308. Then, the process proceeds to the process for the next example sentence (step E24), and the processes of steps E14 to E22 are repeated. When the processing is completed for all the example sentence numbers (step E22; Yes), the example sentence numbers stored in the second work area 308 are sorted by the collocation importance of the example sentences (step E26), and the example sentence number storage area 304 is updated (step E28). For example, in step E10, even if example sentence numbers are stored in the second work area 308 in the order as shown in FIGS. 17A and 17I, sorting is performed at the level of the collocation importance of example sentences in step E26. Therefore, the example sentence numbers stored in the second work area 308 are updated in the order as shown in FIGS.

  FIG. 17B shows an example of a screen displayed as a processing result based on the updated example sentence number storage area 304. Similar to the processing result screen of the headword limiting process shown in FIG. 8, the character string portion equivalent to the search word is specially displayed T1.

  It should be noted that by making the determination in step E18 “cold word importance ≠ designated importance”, it is possible to perform processing for deleting example sentence numbers of example sentences whose collocation importance is not designated importance from the second work area 308. . In that case, only example sentences with the specified importance can be displayed.

  Thus, according to the collocation importance level designation process, it is possible to display an appropriate example sentence based on the designated collocation importance level. That is, based on the collocation importance specified by the user, the grammar including the collocation that is not important in the grammar is not displayed, so that it is possible to display an appropriate grammar according to the user's intention. In addition, since the displayed example sentences are also displayed in the order of the collocation importance, for example, the example sentences are displayed more importantly than the search words, and the user can easily confirm the contents of the example sentences. Is possible.

  Although the embodiments of the present invention have been described above, the present invention is not limited to the contents of the above-described embodiments, and can be appropriately changed without departing from the spirit of the present invention. For example, in order to realize a search for example sentences including collocations or phrases that use the words “look” and “like” in succession, an input with a space between “look” and “like” may be possible.

  For example, FIG. 18A is an example of a screen displayed on the display unit 50 in step A12 of the example sentence search process. Here, “look like” and a search term separated by a space are entered in the search term input area P300. When the search term separated by the space is input, the CPU 10 extracts only the example sentence number in which the search words “look” and “like” are used in succession in step B18, and the corresponding example sentence number is extracted. By adding to the end of the third work area 310, it is possible to search for example sentences in which search words are continuously used. FIG. 18B shows an example of the search result screen at this time. In the same figure, unlike the screen example of FIG. 8B displayed by inputting “look & like”, only example sentences in which “look” and “like” are used in succession are displayed. For this reason, it is possible to search and display the example sentence suitable for the purpose.

It is a figure which shows the electronic dictionary of this Embodiment. It is a figure which shows the structural example of the electronic dictionary of this Embodiment. It is a figure which shows an example of a data structure of (a) headword table, (b) change form table, and (c) word level table. It is a figure which shows an example of a data structure of (a) example sentence table and (b) word example sentence table. It is a figure which shows the operation | movement flow of an example sentence search process. It is a figure which shows the operation | movement flow of a headword limitation process. It is a figure which shows an example of the work area | region in a headword limitation process. It is a figure which shows the screen for designating the input and extraction conditions of a search word, and the figure which shows the example of a display when performing a headword limitation process. It is a figure which shows an example of a data structure of (a) headword table and (b) word example sentence table. It is a figure which shows an example of the work area | region in a headword limitation process. It is a figure which shows the example of a display when performing a headword limitation process. It is a figure which shows the operation | movement flow of a word level designation | designated process. (A) An example of a work area in a word level designation process, (b) a diagram for explaining steps for determining example sentence word levels, and (c) a diagram showing a display example when the word level designation process is executed. is there. It is a figure which shows the operation | movement flow of an example sentence difficulty level designation | designated process. It is a figure which shows an example of a work area in (a) example sentence difficulty designation | designated processing, and a display example when (b) example sentence difficulty designation | designated processing is performed. It is a figure which shows the operation | movement flow of a multiple word importance designation | designated process. It is a figure which shows an example of the work area in (a) collocation importance designation | designated processing, and a display example when (b) collocation importance designation | designated processing is performed. (A) The figure which shows the screen for designating the input and extraction conditions of a search term, (b) The figure which shows the example of a display when performing a headword limitation process.

Explanation of symbols

1 Electronic dictionary 10 CPU
20 ROM
22 English-Japanese Dictionary DB
222 Headword table 224 Example sentence table 226 Word example sentence table 228 Variation table 230 Word level table 24 Example sentence search program 242 Headword limitation program 244 Word level designation program 246 Example sentence difficulty designation program 248 Conjunction importance designation program 30 RAM
302 Search phrase storage area 304 Example sentence number storage area 306 First work area 308 Second work area 310 Third work area 40 Input section 50 Display section

Claims (7)

Dictionary information storage means for storing an entry word and explanation information of the entry word in association with each other;
First input means for inputting a word in response to a user operation;
Dictionary information display control means for performing control to extract and display the description information having the word input by the first input means as a headword from the dictionary information storage means;
In an information display control device comprising:
Example sentence storage means for storing an example sentence in association with the source headword of the example sentence;
Example sentence word storage means for storing a word in association with an example sentence stored in the example sentence storage means including the word;
Word level storage means for storing a preset level of each word;
A second input means for inputting a plurality of words in response to a user operation ;
Extraction means for extracting the example sentence including all the plurality of words inputted from the example sentence stored in correspondence with the example sentence word storage means by the second input means,
Processing button display control means for performing control to display a button corresponding to each of a plurality of processes;
A selection means for selecting an arbitrary button whose display is controlled by the processing button display control means according to a user operation;
When the button corresponding to the word level assigning process by the selection means is selected, according to the order of the highest level or the lowest level of the level of each word included in each example sentence extracted by the extraction means, to display Word level order display control means for controlling the order of example sentences ;
An information display control device comprising: The word level order display control means includes:
A word level specifying means for specifying a word level in response to a user operation ;
Control to display the example sentence other than example sentence exceeds the level of the word top level or bottom level of the level of each word included in each example sentence extracted by the extraction means is designated by said word-level specifying means Word level designation display control means to perform ,
The information display control device according to claim 1, comprising: Example sentence level storage means for storing the level of each example sentence stored in association with the example sentence word storage means;
An example sentence level specifying means for specifying an example sentence level in response to a user operation ,
The word level order display control means includes:
When a button corresponding to the example sentence level designation process is further selected by the selection means, the level of each example sentence extracted by the extraction means is read from the example sentence level storage means, and the read level is designated by the example sentence level designation means Example sentence level narrowing means for performing control to display example sentences other than the example sentence exceeding the level of the given example sentence;
Example sentence level order display control means for controlling the order of example sentences to be displayed according to the order of the levels of each example sentence narrowed down by the example sentence level narrowing means ;
Information display control device according to claim 1 or 2, further comprising a. Collocation storage means for storing the collocations included in each example sentence stored in the example sentence storage means and the level of the collocation in association with each other;
Collocation level designation means for designating the collocation level in response to a user operation,
The word level order display control means includes:
When the button corresponding to the collocation level designation process is further selected by the selection means, the collocation words included in each example sentence extracted by the extraction means are a plurality of words input from the second input means. Collocation level narrowing means for reading collocations including collocations from the collocations stored in the collocation storage means and narrowing the read collocation levels to examples other than grammars including collocations exceeding the collocation level specified by the collocation level designation means;
Example sentence level order display control means for controlling the order of example sentences to be displayed in accordance with the order of the level of the conjunctions included in each example sentence narrowed down by the conjunction word level narrowing means ;
Information display control device according to any one of claim 1 to 3, further comprising a. The example sentence storage means further stores identification information in association with each example sentence,
For each word, it further comprises example sentence identification information storage means for storing identification information of an example sentence including the word,
Said extracting means, for each word input from the second input means, the example sentence identification information of an example sentence containing the word is read from the example sentence identification information storage means, the example sentence identification information common to the respective word the association was sentence is a means for extracting from the example sentence storage means, the information display control device according to any one of claim 1 to 4, characterized in that. The second input means includes delimiter input means for delimiting and inputting a plurality of words with predetermined characters,
The extraction means is means for extracting an example sentence in which at least the plurality of words appear in the input order when a plurality of words are input by being divided by the predetermined character by the separation input means. The information display control device according to any one of claims 1 to 5 . Dictionary information storage means for storing a headword and explanation information of the headword in association with each other, example sentence storage means for storing an example sentence in association with the source headword of the example sentence, and a word including the word In a computer comprising example sentence word storage means for storing in association with the example sentence stored in the example sentence storage means, and word level storage means for storing a preset level of each word,
A first input function for inputting a word in response to a user operation;
Dictionary information display control function for performing control to extract and display the description information having the word input by the first input function as a headword from the dictionary information storage means;
A second input function for inputting a plurality of words in response to a user operation ;
An extraction function for extracting an example sentence including all of the plurality of words input by the second input function from example sentences stored in association with the example sentence word storage unit;
A process button display control function for performing control to display a button corresponding to each of a plurality of processes;
A selection function for selecting an arbitrary button whose display is controlled by the processing button display control function according to a user operation;
When the button corresponding to the word level assigning process by the selected function is selected, in order of the highest level or the lowest level of the level of each word included in each example sentence extracted by the extraction function, and displays A word level order display control function for controlling the order of example sentences ;
A program to realize

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