JPH08329165A - Text extraction processing device and text extraction processing method - Google Patents

Abstract

(57) [Summary] [Purpose] A character string containing numerical data is automatically extracted from a document arbitrarily created by the user, and the numerical data is classified into each item from the character string and aggregated. [Configuration] When a document to be processed is input (301 to 30
3) The character string having a specific pattern is extracted from the document as numeric data (304), and the character string based on a certain rule existing before and after the numeric data is extracted as numeric character string data (305). ). Noun data is extracted from the numeric character string data, the noun data is classified into predetermined items, and the numeric data is associated (306). The numerical data of each item obtained in this way is totaled for each predetermined period such as one month (307), and the totaled result data is displayed (303).
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Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention extracts a numerical character string from plain text created by a word processor or the like, performs numerical processing, etc., and finally classifies the data, aggregates numerical data, etc. The present invention relates to a text extraction processing device and a text extraction processing method that perform processing.

[0002]

2. Description of the Related Art Conventionally, spreadsheet software is generally used as a method of totalizing numerical data classified by item. This is an application software that is used for a wide range of purposes such as creating a quotation / invoice, centering on tabulation / calculation.

In this type of spreadsheet software,
Enter data such as characters, numbers and formulas in cell units. A cell is one of the partitions created by the intersection of rows and columns, and is the basic unit of calculation. By inputting an item name or a numerical value in this cell, it is possible to obtain a calculation result according to a calculation formula designated in advance.

[0004]

As described above, in the method using the conventional spreadsheet software, it is necessary to input the data such as the item name and the numerical value in the designated area. Therefore, the special input operation is learned. However, there is a drawback that it is not flexible.

Further, in such spreadsheet software, even if the amount of revenue or the amount of expenditure is expressed as a numeric character string in a document created by using a word processor or the like, it is used. There is no function that automatically calculates the total amount of daily spending. for that reason,
It was necessary to re-enter the spreadsheet data.

The present invention has been made in view of the above points, and automatically extracts a character string including numerical data from a document arbitrarily created by a user and classifies the numerical data of the character string into each item. However, it is an object of the present invention to provide a text extraction processing device and a text extraction processing method capable of performing a totalization process.

[0007]

A text extraction processing apparatus according to the present invention includes a document input means for inputting document data to be processed, and a numerical value for extracting numerical data from the document data input by the document input means. Data extracting means, numeric character string data extracting means for extracting numeric character string data corresponding to the numeric data extracted by the numeric data extracting means, and the numeric character string extracted by the numeric character string data extracting means Noun data extraction means for extracting noun data from the data and the noun data extracted by the noun data extraction means are classified into predetermined items, and the numerical data related to the noun data is classified for each item. Corresponding data structuring means and the numerical data associated with each item by this data structuring means A data collecting unit that aggregates at predetermined time intervals, characterized by comprising a display means for displaying the counting result data obtained by the data collecting unit.

[0008]

According to the above construction, by inputting the document data to be processed, a character string having a specific pattern is extracted from the document data as numerical data. A character string existing before and after this numerical data based on a certain rule is extracted as numerical character string data, and noun data existing therein is extracted. By classifying the noun data for each predetermined item, the numerical data related to the noun data is associated with each item, and is aggregated for each predetermined period such as one month.

[0009]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing the configuration of a text extraction processing device according to an embodiment of the present invention. This device
It has an input device 11, a control device 12, an external storage device 13, a display device 14, and a clock device 15.

The input device 11 is composed of a pointing device such as a keyboard and a mouse, and is used for inputting data and performing various instructions for performing a text extraction operation.

The control device 12 is composed of, for example, a microprocessor and controls the entire device, and has a control unit 21 and a memory unit 22 as shown in FIG.
Executes text extraction processing.

The external storage device 13 is, for example, an HDD (hard disk device) or FDD (floppy disk device).
It stores various information such as document data. The display device 14 is, for example, a CRT (Cathode Ray Tube) or L.
It consists of a CD (Liquid Crystal Display) and displays a menu screen for displaying document data and extracting text.

The clock device 15 is composed of, for example, a crystal oscillator, and performs interrupt processing at regular time intervals to detect current date and time data. In addition, each of the above-mentioned devices 11, 13, 1
Reference numerals 4 and 15 are connected to the control device 12 via a system bus (not shown), and under the control of the control device 12, it is possible to send data to each other.

FIG. 2 is a diagram showing a detailed configuration example of the control device 12. The control device 12 includes a control unit 21 and a memory unit 22.
It consists of The control unit 21 is a unit that executes various controls and processes. Here, the main processing unit 21a, the document input unit 21b, the numerical data extraction storage unit 21c, the numerical character string data extraction storage unit 21d, and the noun data classification storage unit 21.
e, a data totaling unit 21f, and a totaling result display unit 21g.

The main processing section 21a controls the entire apparatus. The main processing section 21a branches the control flow, calls each module after the data input section, and performs processing for generating a table in the external storage device.

The document input section 21b performs an input process of document data to be processed. Numerical data extraction storage unit 21c
Performs extraction processing of numerical data from the document data input as the processing target.

The numerical character string data extraction / storing section 21d extracts numerical character string data corresponding to the numerical data from the document data. The noun data classification storage unit 21e performs a process of extracting noun data from the numeric character string data, and a process of storing numerical data associated with the noun data in association with each other.

The data totaling unit 21f performs a totaling process of numerical data. The tally result display unit 21g performs a display process of tally result data. The memory unit 22 is a unit for storing various data, and here, a numeric character string data storage buffer 22a, a noun data storage buffer 22b, a numeric data storage buffer 22c, an item classification character string data storage buffer 22d, and a data aggregation result storage. Various buffers such as the buffer 22e, the document data storage buffer 22f, and the date / time storage buffer 22g for temporarily storing data necessary for processing, and working for temporarily storing data necessary for the control unit 21 to operate. It has an area 22h.

The numeric character string data storage buffer 22a is
It is a buffer for storing the numerical character string data extracted by the numerical character string data extraction storage unit 21d. The noun data storage buffer 22b is a buffer for storing the noun data extracted by the noun data classification storage unit 21e.

The numerical data storage buffer 22c is a buffer for storing the numerical data extracted by the numerical data extraction storage unit 21c. The item classification character string data storage buffer 22d is a buffer for storing the character string data (FIG. 8) set for each predetermined classification.

The data totalization result storage buffer 22e is a buffer for storing the totalization result data obtained by the data totalization unit 21f. The document data storage buffer 22f is a buffer for storing the document data to be processed obtained by the document input unit 21b.

The date / time storage buffer 22g is a buffer for storing the current date / time data obtained by the clock device 15 of FIG. Next, the operation of the embodiment will be described with reference to the flowcharts shown in FIGS.

FIG. 3 is a flow chart showing the overall flow of the text extraction processing in this embodiment. FIG. 4 is a flow chart showing the numerical data extraction storage process (specific process of step 304 of FIG. 3) in the same embodiment.
FIG. 5 is a noun theta classification storage process (FIG. 3) in the same embodiment.
Is a flowchart showing a specific process of step 306).

(1) First, the type of document is selected. Note that, here, a “household account book” is prepared as a document type in advance, and the case where the user selects this will be described (step 301).

(2) When the user clicks the "document button" provided on the operation screen (not shown), the memory unit 22
The current date and time data is taken out from the inside date and time storage buffer 22g, and the dated document of the day (“household account book”) is opened. Here, when the user clicks the "date button" and selects an arbitrary date, a document on another date can be opened (step 302). FIG. 6 shows an example of the input document.

(3) The user inputs arbitrary document data through the input device 11 (step 303). This input document data is stored in the document data storage buffer 22f provided in the memory unit 22 of the control device 12.

(4) The control device 12 processes the document data stored in the document data storage buffer 22f,
Numerical data is extracted from the document data and stored in the numerical data storage buffer 22c (step 30).
4).

Specifically, as shown in the flow chart of FIG. 4, the data is sequentially read one character at a time from the beginning of the document data (step 401), a numeral (Chinese numeral, Arabic numeral, Roman numeral) or "¥". Search for ".
Then, start with that letter (number or "\"),
A character string whose ending is a character other than the character "yen" or the character just mentioned is extracted as numerical data (steps 402 to 409).

In this case, since the extracted character strings are character data one by one, all the numerical characters existing therein are converted into numerical values, which are then stored in the numerical data storage buffer 22c.
(Steps 410 and 411).

(5) When the character string as the numerical data is extracted from the document data to be processed as described above, the control device 12 next extracts the numerical character string data from the same document data, and extracts this numerical character string. The data is stored in the data storage buffer 22a (step 305).

Specifically, the character immediately after the punctuation mark or number that appears before the character string (numerical data) extracted in (4) above or the beginning of the sentence is the beginning, and the character immediately before the punctuation mark or number that appears next is the character. The character string to be the ending is extracted as numeric character string data, stored in the numeric character string data storage buffer 22a, and associated with the numeric data.

FIG. 7 shows an example of extracting the numeric character string data at this time. For example, it is assumed that the document data “I bought 200 yen of pork and 2000 yen of glass today” as shown in FIG. 7A is input as a processing target.

In such a case, as a result of the processing of (4) and (5), as shown in FIG. 7B, the numerical data is "200" and the corresponding numerical character string data is "Today's pork. 200 yen is extracted. Similarly, “2000” is extracted as the numerical data, and “I bought a glass of 2000 yen.” Is extracted as the corresponding numerical character string data.

The processes (4) and (5) are repeated until the end of the input document data. (6) Next, the control device 12 extracts a noun from the numeric character string data stored in the numeric character string data storage buffer 22a, classifies it into a predetermined item, and stores it in the noun data storage buffer 22b. At the same time, the numerical data associated therewith are stored in the buffer 22b in association with each other (step 306).

Specifically, as shown in the flowchart of FIG. 5, the character string extracted as the numerical character string data by the process of (5) is subjected to morphological analysis (steps 501 to 501).
503), and based on the analysis result, the noun part of the same character string is extracted (step 504). Then, by comparing the dependent noun of the related numerical data, the noun of the object, or the unique noun with the item classification character string (FIG. 8) itemized according to the purpose of use (step 505),
The data is stored in the noun data storage buffer 22b belonging to the matched item (step 507). The item classification character string shown in FIG. 8 can be arbitrarily changed by the user.

Here, the classification items are "income", "temporary income", "savings", "tax", "housing cost", "electric hot water cost", "main meal cost", "side meal cost", "outdoor meal cost". , “Luxury item cost”, “Clothing cost”, “Education cost”, “Health and hygiene cost”, “Educational and entertainment cost”, “Communication communication cost”, and “Occupation cost”. At that time, the numerical data related to the noun data is made to belong to the item data (step 508). The data classification storage sequence in this case is shown in FIG.

(7) When the noun data for each item and the numerical data corresponding thereto are obtained in this way, the control device 12 totalizes the numerical data on a monthly basis, for example. The total period at this time can be arbitrarily set by the user. The control device 12 adds all the numerical data in each item, and adds this to the data totaling result storage buffer 22.
It is stored in e (step 307).

FIG. 1 shows an example of collecting data in this way.
It shows in 0. When the user clicks on the "detailed tabulation result button", the tabulation result is displayed on the display device 14 in a predetermined format, and the contents can be confirmed.

(8) Further, when the user clicks on the "total button", the control device 12 adds the item price data of the income item and the temporary income item, subtracts the item price data of the other items, and subtracts the item price data of the other month. Calculate the balance. Based on this calculation result, the amount of money used for each item for one month, the balance of the month, and the comparison with the previous month are displayed. This display example is shown in FIG. At this time, if the user has previously set a budget for the month, the comparison with that is also displayed (step 308).

In this way, the numerical data for each item is automatically extracted for the document data arbitrarily created by the user, and the totaling process using these numerical data is executed. In this case, it is not necessary to input data such as item names and numerical values as in conventional spreadsheet software, so that anyone can easily collect data.

The present invention is not limited to the above embodiment. That is, although the type of document is "household account book" in the above-mentioned embodiment, it can be applied to other documents such as "working hours" and "accounting of company". Further, the data is not limited to the document created by one person, and the documents created by a plurality of people may be used to aggregate the data according to various criteria such as date and item.

[0042]

As described above, according to the present invention, the user can automatically obtain the numerical data categorized by each item only by inputting the created document. It is possible to perform the aggregation process using.

Therefore, there is no need to input data in a predetermined format as in the prior art, and as a result, it is possible to save a lot of time to get used to the input procedure and time required to classify the items, which is a great practical amount. The effect can be obtained.

[Brief description of drawings]

FIG. 1 is a block diagram showing the configuration of a text extraction processing device according to an embodiment of the present invention.

FIG. 2 is a diagram showing a detailed configuration of the control device of FIG.

FIG. 3 is a flowchart showing the overall flow of text extraction processing in the embodiment.

FIG. 4 is a flowchart showing a numerical data extraction / storing process in the embodiment.

FIG. 5 is a flowchart showing a noun data classification storing process in the embodiment.

FIG. 6 is a diagram showing an example of an input document in the embodiment.

FIG. 7 is a diagram showing an example of numeric character string data extraction in the same embodiment.

FIG. 8 is a diagram showing an example of an item classification character string in the same embodiment.

FIG. 9 is a diagram showing an example of data classification storage in the embodiment.

FIG. 10 is a diagram showing a data classification storage example in which numerical data are associated with each other in the same embodiment.

FIG. 11 is a diagram showing a display example of a counting result in the embodiment.

[Explanation of symbols]

 11 ... Input device, 12 ... Control device, 13 ... External storage device, 14 ... Display device, 15 ... Clock device.

Claims (5)

[Claims] 1. A document input means for inputting document data to be processed, a numerical data extraction means for extracting numerical data from the document data input by the document input means, and a numerical data extraction means for extracting numerical data. Numerical character string data extracting means for extracting numerical character string data corresponding to the numerical data from the document data, and noun data from the numerical character string data extracted by the numerical character string data extracting means. Noun data extraction means, data structuring means for classifying the noun data extracted by the noun data extraction means into predetermined items, and associating the numerical data related to the noun data with each item, Data that summarizes the above numerical data associated with each item by the structured case means for each predetermined period A meter unit, text extraction processing apparatus characterized by comprising a display means for displaying the counting result data obtained by the data collecting unit. 2. The text extraction processing apparatus according to claim 1, wherein the numerical data extracting means extracts a character string having a specific pattern from the document data as numerical data. 3. The numerical character string data extracting means extracts a character string existing before and after the numerical data based on a certain rule from the same document data as numerical character string data. Text extraction processor. 4. Numerical data is extracted from the document data to be processed, numeric character string data corresponding to this numeric data is extracted from the same document data, and noun data is extracted from this numeric character string data, This noun data is classified for each predetermined item, the numerical data related to the noun data is associated with each item, and the numerical data for each item is totaled for each predetermined period. Text extraction processing method. 5. A character string having a specific pattern is extracted as numerical data from document data to be processed, and a character string based on a certain rule existing before and after the numerical data is converted into numerical character string data from the same document data. Noun data is extracted from the numeric character string data, the noun data is classified into predetermined items, and the numerical data related to the noun data is associated with each item. A text extraction processing method characterized in that the above-mentioned numerical data for each time is totaled for each predetermined period.