JPH11219367A - METHOD AND APPARATUS FOR JOINING DIFFERENT DATA WITH ADDRESS INFORMATION - Google Patents

Abstract

(57) [Summary] [PROBLEMS] To combine two different types of data having address information by a computer at high speed and with high accuracy without performing Japanese processing. SOLUTION: A normalization processing unit 110 normalizes the resident name included in the data to be combined, and an address matching data combining pass / fail judgment unit 120 matches the degree of matching of the character of the resident name of the record whose address completely matches. Is evaluated, and if there is a degree of coincidence equal to or greater than a predetermined reference value, the two are linked as a pass. For records that did not have a matching degree equal to or greater than the reference value, the block matching data combination pass / fail judgment unit 130 expanded the evaluation range of the matching degree to the group of records that matched the street and the street (block). The degree of coincidence is determined more strictly than when it is performed, and the results are linked to each other.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION The present invention relates to two types of data including address-related information (town address, address, number, form, resident name, etc.) using a computer and referring to the address-related information. The present invention relates to a method and an apparatus for automatically and efficiently finding and linking (coupling) data of the same resident.

[0002]

2. Description of the Related Art For example, by combining customer data with detailed house map data having resident information for each building, it is possible to specify and display a building on a map from customer information such as a telephone number. Therefore, it is necessary to perform processing for combining different types of data based on address information. However, the address information of different types of data created separately includes fluctuations, incompleteness, and inaccuracy such as address information. For example, a telephone number book database (DB) and commercially available electronic When the completed house map DB is combined with perfect match, only about 40% is automatically combined (Ref.
chapter). If the remaining data are manually combined, for example, combining the customer information and the map data posted in the occupational telephone directory (approximately one million) in the 23 wards of Tokyo requires a great deal of man-hours.

[0003] The fluctuation of the notation in the address information may be, for example, written in kanji or katakana, abbreviated as "stock company" or "(stock)". It means that it may be written, full-width characters or half-width characters.

For this reason, conventionally, as a method for improving the automatic combining accuracy in a computer, two types of address information (DB,
Address and number are not strictly matched, and are used only for narrowing down the comparison data. The emphasis is placed on comparison of resident information. A method of extracting information and determining the degree of coincidence has been proposed (Reference Document 1 / Chapter 6). By using this method, the automatic connection rate by the computer can be increased to about 80%, and it is possible to greatly reduce manual work.

Reference 1: Yasuda, Matsumura, Mizumachi, Karasawa, "Map guidance system using telephone and facsimile", Proc. Of the 3rd Functional Graphic Information System Symposium, 1992/4, pp.81
-86.

[0006]

However, the above-mentioned method requires a huge amount of disk space for maintenance of a Japanese dictionary and the like, and requires a relatively large amount of computation in computer processing. For example, Tokyo 2
In the results of combining 1 million data in 3 districts, 5 to 24 hours in a row using a workstation (WS) etc.
It was necessary to calculate continuously for six days, and the load on the computer was very large, and the recombining process could not be easily performed with updating of data such as maps and telephone directories.

An object of the present invention is to provide a method of combining address matching data which can be automatically combined with high speed and high accuracy without performing Japanese processing, and an apparatus for realizing the method.

[0008]

According to the present invention, there is provided a normalization processing section for pre-normalizing data, and an address matching data connection success / failure judgment section for judging connection success / failure of a record whose address coincides with a town / chome / address / number. And a block matching data combination pass / fail determination unit that determines the pass / fail of records that match only up to the street / address.

Regarding the resident name information of the two types of DBs (here, DBa and DBb), the normalization processing unit converts "Hiragana" and "English characters" into "Katakana" in advance, and converts "Hiragana" and "Semi-voiced sound" Is "cleared", and symbol unification is performed. First, by performing this normalization processing on the two types of DBs to be processed, fluctuations of a simple notation are matched and matched.

Next, the normalized data is sent to an address matching data combination pass / fail determination unit, which determines the first D
The records are taken out one by one from Ba, and a record group of the second DBb having the address information that completely matches the address information (town address, address, number) is searched. When there is the corresponding address matching information, the matching degree between the characters of the resident name information of the target record of DBa and the characters of the resident name of the target record of DBb is evaluated based on the number of common characters, and the evaluation value exceeds the predetermined acceptance criterion value f1. If so, combine them.

When there are a plurality of address matching records, those having the highest matching evaluation value exceeding f1 are combined. If there is no address matching data,
The control is transferred to the block matching data combination pass / fail determination unit. Here, of the address information, a data group matching up to the town / street / street (block) is searched from the DBb, and the matching degree is evaluated for each of them in the same manner as the address matching data combination pass / fail determination unit.
Among those exceeding the predetermined acceptance criterion value f2, those having the highest evaluation value are combined. If there is no record having an evaluation value equal to or greater than f2, the connection is unsuccessful and is left unconnected. Here, the evaluation value f2 that matches only up to the address information is set larger than the evaluation value f1 that matches up to the address information, and by making a stricter determination,
It can reduce misconnection.

For example, a pass / fail evaluation value F based on the degree of coincidence is determined as follows. First, the number of characters common to the character strings constituting the resident name between the resident names of DBa and DBb is counted. If the number of characters is B and the total number of characters of the resident name in DBa is A, then F = B / A. Of course, depending on the characteristics of the two DBs to be combined, a method may be used in which a high score is given to a character string that is continuously matched for evaluation, or a method of evaluating the degree of coincidence for a character type.

In the above processing, not only the actual resident's name but also the book is considered, and in the book such as the building name, the degree of coincidence of characters is similarly determined in accordance with the degree of coincidence of the address.
Two types of data different from DBa and DBb may be efficiently linked by a computer. This makes it possible in some cases to obtain more practically favorable coupling results.

The operation of the present invention is as follows. In the present invention configured as described above, by performing evaluation by changing the criterion of the degree of coincidence of the character of the resident name in consideration of the degree of coincidence of the address, it is possible to perform automatic connection by fine evaluation. Moreover, character strings are not regarded as a set of words, but simply as a set of characters, and are processed by focusing only on the presence of common characters. It can be realized by simple processing.

[0015]

Next, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing the configuration of a main part of an apparatus for combining heterogeneous data based on address information according to the present invention. FIG. 2 is an example of the contents of each database shown in FIG. 1, and FIG. 3 is each normalized data shown in FIG. FIG. 4 shows an example of the contents of the database, FIG. 4 shows an example of the contents of the combined database shown in FIG. 1, and FIG. 5 is a diagram specifically showing an outline of the combining processing flow by the processing device shown in FIG.

The processing device 100 is a device comprising a CPU and a memory. As shown in FIG.
20, each of the processing units of the block matching data combination pass / fail determination unit 130 and the combined DB creation unit 140.

In this example, the first DBa 101 to be combined has data having contents as shown in FIG.
It is assumed that the second DBb 102 has data having contents as shown in FIG. The normalization processing unit 110 includes a first DBa 101 to be combined and a second DBb 102
And read the resident name in each record, for example, unify the notation of "stock company" and "(stock)" to "(stock)", "plants" and "brands"
Then, normalization such as clearing any fluctuations in notation such as “Franz” is performed, and a normalized DBa 103 is created from the first DBa 101 and a normalized DBb 104 is created from the second DBb 102.

The normalized DBa 103 has the contents as shown in FIG. 3A, and the normalized DBb 104 has the contents as shown in FIG. 3B. The address matching data combining pass / fail determination unit 120 determines whether the normalized DBa 103
The records (or records) of the normalized DBb 104 having the same address as that of the records are taken out, and the pass / fail is determined according to the processing of FIG.

Assuming that A is the total number of characters of the resident name of the record of interest in the normalized DBa 103, B is the number of matching characters, and F is the pass / fail judgment evaluation value, for example, "Chatela Shigaya Co., Ltd." Means A = 11, B =
8, F = 0.727, and A = 7, B = 5, F = 0.714 for "Shibuya City Library" and "Municipal Tomigaya Library". "Franz G" and "Cafe Lantern" are A =
5, B = 2, and F = 0.4. If the pass criterion value at the time of address matching is f1 = 0.6, the data can be combined as data of the same resident name in the preceding two examples, but the last example is rejected and determined to be impossible to combine.

The records that could not be combined by the address matching data combination determination unit 120 are sent to the block matching data combination determination unit 130. Here, the entire record having an address in the same block as the record of interest is the target of the combination pass / fail determination. For example, "Frantz G" of No. 1 is evaluated as A = 5, B = 5 and F = 1 as "G Franz" of No. 1 and "Cafe France" of No. 1 is A = 5, B
= 3, F = 0.6. If the pass criterion value (f2) at the time of address mismatch is f2 = 0.8, only the former is regarded as pass. If the pass / fail evaluation value F is 0.8
When there are a plurality of candidate records, the highest pass / fail judgment evaluation value F is passed (in the case of a tie, judgment is made based on a criterion such as giving priority to the one with the closest lot number (number) information). If the pass / fail evaluation value F is smaller than the reference value f2, there is no combined record (unconnected).

The merged DB creating unit 140 compares the records determined as pass by the address matching data combining pass / fail determination unit 120 and the block matching data combining pass / fail determination unit 130 with each other.
The combining flag is turned on, and the combined D that has the information of the second DBb 102 in addition to the information of the first DBa 101
Create B105. Specifically, the combined DB 105
Has the contents as shown in FIG.

The flow of the above combining process will be described with reference to FIG. First, the normalization processing unit 110 determines the D
A normalized DBa 103 and a normalized DBb 104 are created from the Ba 101 and the DBb 102, respectively (S
1).

Next, the address match data combination pass / fail judgment section 12
0 is a record extracted from the normalized DBa 103 one record at a time, and a normalized DBb 104 having the same address as the extracted record.
Of the pass / fail judgment evaluation value F (F = B /
A) is calculated (S2).

The evaluation value F is compared with the reference value f1 (S
3) If the evaluation value F is equal to or more than the reference value f1, it is determined that the combination is possible, and the process proceeds to step S10. If the evaluation value F is smaller than the reference value f1, the process proceeds to step S4.

The block matching data combination pass / fail determination unit 130
One piece of data of the normalized DBb 104 having an address in the same block as the target record of the normalized DBa 103 determined to be unmergeable by the address matching data combining pass / fail determination unit 120 is extracted (S4). The pass / fail evaluation value F
(F = B / A) is calculated, and the evaluation value F of the result is compared with a pass criterion value f2 at the time of address mismatch (S5). If the evaluation value F is equal to or more than the reference value f2, the record is recognized as a passing candidate (S6).

Steps S4 to S6 are referred to as normalized DBb
Repeat all records for 104 records in the same block (S
7) If all the items have been checked, it is determined whether there is a pass candidate (S8).

If there are no pass candidates, the combination is notified to the joined DB creating unit 140. If there are pass candidates, it is checked whether there are a plurality of pass candidates. The candidate record with the highest F is finally selected (S9), and the combination possibility is notified to the combined DB creation unit 140.

The merged DB creator 140 performs a merge success process (S10) with the merge flag turned on or a merge unsuccess process (S11) with the merge flag turned off, depending on whether the merge is possible. The completed DB 105 is created.

In the above, an example has been described in which the criterion for determining the degree of coincidence of a character is changed in consideration of the degree of coincidence of an address for a resident name.
When a library such as a building name is included, not only the resident's name but also the library may be used as a target for judging whether or not the character is matched in the same manner.

For example, when the format in the record of the first database is x1, the resident name is y1, and the format in the record of the second database is x2, and the resident name is y2, the format is the same as the resident name. And evaluation based on the degree of coincidence between the characters x1 and x2, evaluation based on the degree of coincidence between the characters x1 and y2, evaluation based on the degree of coincidence between the characters y1 and x2, and y1 and y
The evaluation may be performed based on the degree of coincidence of the two characters, and when it is determined that any one of the two characters can be combined, the two types of data may be combined.

[0031]

[Embodiment] Focusing on both the resident name and the form, and using this method to combine 1 million telephone directory DBs (town page data) in 23 wards of Tokyo with commercial housing map DB, Achieved about 90%, and the processing time was several hours using a personal computer. Therefore,
It has been demonstrated that the processing time can be significantly reduced compared to the conventional method using Japanese processing.

[0032]

As described above, according to the present invention,
By changing and evaluating the criterion for determining the degree of coincidence of the characters of the resident name information in consideration of the degree of coincidence of the address, automatic connection by fine evaluation becomes possible. Moreover, character strings are not regarded as a set of words, but simply as a set of characters, and are processed by focusing only on the presence of common characters. This can be realized by simple processing.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a main configuration of the present invention.

FIG. 2 is a diagram showing an example of the contents of each database shown in FIG. 1;

FIG. 3 is a diagram showing an example of the contents of each normalized database shown in FIG. 1;

FIG. 4 is a diagram showing an example of contents of a combined database shown in FIG. 1;

FIG. 5 is a diagram showing an outline of a combining processing flow by the processing apparatus shown in FIG. 1;

[Explanation of symbols]

 101 Database (DBa) 102 Database (DBb) 103 Normalized DBa 104 Normalized DBb 105 Combined DB 100 Processor 110 Normalization Processing Unit 120 Address Matching Data Combining Pass / Fail Determination Unit 130 Block Matching Data Combining Pass / Fail Determination Unit 140 Combining DB creation unit

Claims (2)

[Claims] 1. A method of connecting two different types of data having address information by a computer, wherein a process of normalizing a resident name or a format included in both data to prepare a representation of the data, and A process of evaluating the degree of coincidence of the resident name of the record or the letter of the book that completely matches, and if there is a degree of coincidence equal to or more than a predetermined reference value, as a pass, linking the two. With regard to the records that have been identified, it is determined that there is a possibility that the addresses do not match, and the evaluation range of the degree of match is extended to a group of records that match up to the block, the criteria are made stricter than when the addresses match, and the degree of match is determined. Combining the different types of data with the address information. 2. An apparatus for connecting two different types of data having address information by a computer, comprising first means for normalizing a resident name or a form included in both data to prepare a representation of the data. A second means for evaluating the degree of coincidence of a resident name or a letter of a letter of a record whose address completely matches, and if there is a degree of coincidence equal to or greater than a predetermined reference value, as a pass, connecting the two; For records that did not pass the judgment of the above means, it is assumed that the address may not match, and the evaluation range of the matching degree is expanded to the record group that matches the block, and the criteria are made stricter than when the address matches. And a third means for judging the degree of coincidence and connecting the two to each other.