JP5544693B2 - Data processing apparatus, data processing program, and data processing method - Google Patents

Description

  The present invention relates to a data processing device, a data processing program, and a data processing method.

  Conventionally, computer systems store and manage predetermined data such as addresses, names, and organization names in a database or the like. Since this type of data is often input by a system administrator or a user such as a user, the notation of the input character string may not be unified. Examples of inconsistent notation include partial omission of descriptions and the use of variant characters. For example, even if the same address is input, the input person A inputs “Kyomachi 1-chome, Chiyoda-ku, Tokyo”, but the input person B inputs “1 Koji-cho, Chiyoda-ku, Tokyo”. There are things to do.

  In such a case, the computer system is in a state of managing data originally showing the same contents as different data. This leads to a problem that the same data is originally recognized as different data when the computer system collates data.

  In recent years, several techniques for unifying data have been proposed. For example, an address registered in a predetermined address master and an address to be corrected are decomposed into key character strings, and the decomposed character strings are compared, and unified data under predetermined conditions A technique for displaying is proposed. Further, for example, a technique has been proposed in which an address to be corrected is divided into address hierarchies, an address having a matching building name is extracted from a predetermined address master, and the address to be corrected is corrected to the extracted address.

JP 2001-109751 A JP 2008-158738 A

  However, the conventional technique has a problem that the load in the process of extracting the unified data increases, and the process cannot be performed at high speed. Specifically, in the prior art, the address to be corrected is divided into hierarchies such as prefectures and municipalities, and each divided address is checked against an address registered in a predetermined address master. I went repeatedly. In general, since an address is often divided into five or more hierarchies, it has been necessary to perform collation processing five times or more in the related art. For this reason, in the prior art, the processing load on the apparatus that performs the data correction processing increases, and it takes time to process the data.

  The disclosed technology has been made to solve the above-described problems caused by the conventional technology, and is a data processing apparatus and data processing program capable of extracting data for correcting predetermined data at a low load and at high speed And it aims at providing a data processing method.

  In order to solve the above-described problems and achieve the object, a data processing device disclosed in the present application stores a predetermined character string and a character string identifier for identifying the predetermined character string. A character string element storage means for storing a character string element which is a character string included in the predetermined character string, and a set of character string identifiers indicating the predetermined character string including the character string element, Extraction means for extracting a set of character string identifiers stored in association with character string elements included in the character string to be processed from the character string element storage means, and a set of character string identifiers extracted by the extraction means And a first specifying means for specifying a character string identifier most often included in a character string identifier indicating a corresponding character string that is a character string that matches or is similar to the character string to be processed. And

  It should be noted that a method, an apparatus, a system, a computer program, a recording medium, a data structure, etc., in which any component, expression, or any combination of components disclosed in the present application is also effective as another aspect. is there.

  According to the data device disclosed in the present application, it is possible to extract data for correcting predetermined data at a low load and at a high speed.

  Hereinafter, embodiments of a data processing apparatus, a data processing program, and a data processing method disclosed in the present application will be described in detail with reference to the drawings. In the following embodiments, the data processing device, the data processing program, and the data processing method disclosed in the present application modify character string data representing an address whose data is not unified into character string data whose notation is unified. An example of (cleansing) will be described. However, the data processing apparatus, data processing program, and data processing method disclosed in the present application may correct data other than addresses such as name, organization name, corporation name, and branch name to data with a unified notation. it can. In particular, the data processing device, the data processing program, and the data processing method disclosed in the present application can correct data having a hierarchical structure to data having a unified notation.

  First, an outline of data correction processing by the data processing apparatus 100 according to the first embodiment will be described. The data processing apparatus 100 stores character string data (hereinafter referred to as “regular address data”) representing addresses whose notations are unified in a predetermined storage unit. When the data processing apparatus 100 receives character string data representing a predetermined address (hereinafter, referred to as “processing target address data”) for which it is unknown whether or not the notation is unified, the data processing apparatus 100 receives the data from the predetermined storage unit. The regular address data corresponding to the processing target address data is acquired. Then, the data processing device 100 rewrites the processing target address data with the acquired regular address data.

  Here, “character string data representing an address whose notation is unified” indicates address data described according to a notation rule predetermined by a system administrator or the like. The “regular address data corresponding to the processing target address data” indicates the regular address data that matches the processing target address data, or the regular address data that is most similar to the processing target address data. Hereinafter, “regular address data corresponding to the processing target address data” is referred to as “correction candidate address data”.

  An outline of data correction processing by the data processing apparatus 100 according to the first embodiment will be specifically described with reference to FIG. FIG. 1 is a diagram for explaining an overview of data correction processing performed by the data processing apparatus 100 according to the first embodiment. The data processing apparatus 100 includes an address storage unit 121 and an address element storage unit 122. The address storage unit 121 stores therein regular address data whose notation is unified and an address ID for identifying the regular address data in association with each other.

  The address element storage unit 122 includes address data elements (hereinafter referred to as “address elements”) such as prefectures, municipalities, ordinance-designated towns and villages that form address data, and addresses of regular address data corresponding to the address elements. The ID is stored in association with each other. For example, in the example illustrated in FIG. 1, the address element “Kanagawa” is stored in association with the address IDs “1” to “499” in the regular address data stored in the address storage unit 121. Included in legitimate address data. In such a case, the address element storage unit 122 stores the address element “Kanagawa” and the address IDs “1” to “499” in association with each other.

  The structures of the address storage unit 121 and the address element storage unit 122 illustrated in FIG. 1 are merely examples, and detailed structures of the address storage unit 121 and the address element storage unit 122 will be described later.

  When the data processing device 100 receives the processing target address data, the data processing device 100 sequentially substitutes the processing target address data for the automaton formed by the address elements stored in the address element storage unit 122. Thereby, the data processing device 100 performs character string matching between the address element stored in the address element storage unit 122 and the address element included in the processing target address data. As a result of the character string matching, the data processing device 100 acquires the address ID stored in association with the address element included in the processing target address data from the address element storage unit 122.

  In the example shown in FIG. 1, the data processing apparatus 100 accepts “Nakahara Shimoda 1-chome, Kawasaki City, Kanagawa Prefecture” as the processing target address data. In such a case, the data processing apparatus 100 applies the character strings “god”, “na”, “river”, “prefecture”, “river” to the automaton formed by the address elements stored in the address element storage unit 122. ”,“ Saki ”,“ city ”,“ middle ”,“ hara ”,“ bottom ”,“ small ”,“ field ”,“ middle ”,“ 1 ”,“ cho ”,“ eyes ” Collate.

  When the data processing device 100 sequentially substitutes the character strings “god”, “na”, “river”, and “prefecture” for the automaton, the address element “ Detects a match with Kanagawa Prefecture. Subsequently, the data processing apparatus 100 acquires the address ID “1-499” stored in the address element storage unit 122 in association with the address element “Kanagawa”. Similarly, the data processing apparatus 100 reads from the address element storage unit 122 the address ID “1-100” corresponding to the address element “Kawasaki City” and the address ID “5-9” corresponding to the address element “Shimoodanaka”. And the address ID “1: 5: 101:...: 500:...” Corresponding to the address element “1 chome”.

  Subsequently, the data processing apparatus 100 specifies the address ID indicating the correction candidate address data by calculating the logical product of the address IDs acquired from the address element storage unit 122. In the example illustrated in FIG. 1, the data processing apparatus 100 specifies the address ID “5” as the address ID indicating the correction candidate address data as a result of the logical product operation of the address ID. Subsequently, the data processing apparatus 100 acquires from the address storage unit 121 regular address data “1-chome Shimoodanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” corresponding to the identified address ID “5”.

  Subsequently, the data processing apparatus 100 rewrites the processing target address data “Nakahara Shimo Odanaka 1-chome, Kawasaki City, Kanagawa Prefecture” with the acquired regular address data “1 Shimo Oda Naka, Nakahara-ku, Kawasaki City, Kanagawa Prefecture”. In other words, in the address data to be processed “Nakahara Shimoda 1-chome, Kawasaki City, Kanagawa Pref.”, The character string “ku” was missing after “Nakahara”. However, the data correction processing by the data processing apparatus 100 resulted in “Kawasaki City, Kanagawa Pref. "Nakahara-ku Shimo-Odanaka 1-chome"

  As described above, the data processing apparatus 100 according to the first embodiment uses the automaton formed by the address elements stored in the address element storage unit 122 to use the address elements included in the processing target address data and the address element storage. Character string matching with the address element stored in section 122 is performed. Thereby, the data processing apparatus 100 can acquire the address ID stored in association with the address element included in the processing target address data from the address element storage unit 122 by one character string matching process. .

  In addition, the data processing apparatus 100 narrows down the address ID by calculating the logical product of the address IDs acquired from the address element storage unit 122. Therefore, the address ID indicating the correction candidate address data only by performing one calculation process. Can be specified.

  That is, the data processing apparatus 100 can specify the correction candidate address data by performing only one character string matching process and one logic operation process. As a result, the data processing apparatus 100 can correct the processing target address data to the correction candidate address data with low load and high speed.

  In the example illustrated in FIG. 1, the data processing apparatus 100 uniquely identifies the correction candidate address data by calculating the logical product of the address IDs. However, depending on the processing target address data, the address may be A plurality of address IDs may be specified without being able to uniquely specify the ID. In such a case, the data processing device 100 searches for correction candidate address data from a plurality of regular address data indicated by a plurality of identified address IDs. Such search processing will be described later.

  Next, the configuration of the data processing apparatus 100 according to the first embodiment will be described. FIG. 2 is a diagram illustrating the configuration of the data processing apparatus 100 according to the first embodiment. As shown in FIG. 2, the data processing apparatus 100 includes a target data input / output unit 110, a storage unit 120, and a control unit 130.

  The target data input / output unit 110 outputs the processing target address data to a predetermined processing unit, and receives correction candidate address data from the predetermined processing unit. For example, the target data input / output unit 110 acquires address data one record at a time from a predetermined storage unit in which address data whose notation is not unified is stored, and sequentially outputs the address data to the reception unit 131. Further, for example, the target data input / output unit 110 receives processing target address data whose notation is not unified from another information processing apparatus via the network, and outputs the received processing target address data to the reception unit 131. To do. Then, the target data input / output unit 110 receives from the rewriting unit 134 correction candidate address data for correcting the processing target address data output to the reception unit 131.

  The storage unit 120 is a storage device that stores various types of information, and includes an address storage unit 121, an address element storage unit 122, a configuration information storage unit 123, and a log storage unit 124. As described above, the address storage unit 121 mainly stores the regular address data and the address ID for identifying the regular address data in association with each other.

  An example of the address storage unit 121 is shown in FIG. As illustrated in FIG. 3, the address storage unit 121 includes items such as an address ID, an address, a postal code, and a reading. The item “address ID” stores an identifier for identifying an address. The item “address” stores regular address data whose notation is unified. The item “zip code” stores the zip code of the regular address data stored in the corresponding item “address”. The item “Reading” stores the reading (reading pseudonym) of the regular address data stored in the corresponding item “Address”.

  That is, in the first line of the address storage unit 121 shown in FIG. 3, the regular address data of the address ID “1” is “1st Kamiodanaka, Nakahara-ku, Kawasaki City, Kanagawa Prefecture”, and the postal code is “211-0053”. It is shown that the reading is “Kanagawa Kenkawa Saskina Kahalak…”. In the second row of the address storage unit 121 shown in FIG. 3, the regular address data of the address ID “2” is “2-chome Kamiodanaka, Nakahara-ku, Kawasaki City, Kanagawa Prefecture”, and the postal code is “211-0053”. It is shown that the reading is “Kanagawa Kenkawa Saskina Kahalak…”.

  As described above, the address element storage unit 122 mainly includes an address element that is an element of address data divided hierarchically (for each prefecture, city, county, etc.) and regular address data corresponding to the address element. Are stored in association with each other.

  An example of the address element storage unit 122 is shown in FIG. As shown in FIG. 4, the address element storage unit 122 includes items such as an address element, an address ID, and a type. The item “address element” stores elements forming address data such as prefectures, municipalities, government-designated towns, town names, and chome characters. The item “address ID” corresponds to the item “address ID” included in the address storage unit 121 illustrated in FIG. 3, and stores an address ID indicating regular address data corresponding to the address element. The item “type” is information indicating whether the address element stored in the corresponding item “address element” corresponds to a prefecture, a municipality, a government-designated town, a town name, a chome character, or the like. Remember. Note that “NM” written in the address ID in FIG. 4 indicates the address IDs “N” to “M”. Further, “N: M” written in the address ID in FIG. 4 indicates the address IDs “N” and “M”.

  That is, the first line of the address element storage unit 122 shown in FIG. 4 is that the regular address data corresponding to the address element “Kanagawa” has the address IDs “1” to “499” and the address element “Kanagawa” "Indicates that the type is" prefecture ". Further, the 12th line of the address element storage unit 122 shown in FIG. 4 indicates that the regular address data corresponding to the address element “1 chome” has the address IDs “1”, “5”, “101”,. , “500”,..., And the address element “1 chome” indicates that the type is “chome character”.

  The configuration information storage unit 123 mainly stores an address ID and an address element type forming regular address data indicated by the address ID in association with each other. An example of the configuration information storage unit 123 is shown in FIG. As illustrated in FIG. 5, the configuration information storage unit 123 includes items such as an address ID and configuration information. The item “address ID” corresponds to the item “address ID” included in the address storage unit 121 illustrated in FIG. 3. The item “configuration information” stores information indicating whether the regular address data indicated by the corresponding address ID is formed by prefectures, municipalities, government-designated towns, town names, chome characters, or the like. In the configuration information storage unit 123 illustrated in FIG. 5, prefectures, municipalities, government-designated towns, town names, chome characters, and the like are separated by “|” and stored in the item “configuration information”.

  That is, in the first line of the configuration information storage unit 123 shown in FIG. 5, the address data indicated by the address ID “1” is formed by prefectures, municipalities, government-designated municipalities, town names, and chome characters. It shows that. Further, the sixth line of the configuration information storage unit 123 shown in FIG. 5 indicates that the address data indicated by the address ID “500” is formed by prefectures, municipalities, government-designated municipalities, and chome characters. .

  The log storage unit 124 stores log information and is, for example, a text file or a database. In the log storage unit 124, various log information related to the data correction process is stored by the rewriting unit 134 described later.

  Here, a method of generating the address element storage unit 122 described above will be described with reference to FIG. FIG. 6 is a diagram for explaining a method for generating the address element storage unit 122. As shown in FIG. 6, the data processing apparatus 100 first assigns an address ID to each address like various information stored in the address storage unit 121 (step S <b> 11).

  Subsequently, the data processing apparatus 100 decomposes each address data into address elements. Then, as illustrated in FIG. 6, the data processing device 100 extracts the range of the address ID indicating the address data including the address element for each address element (Step S <b> 12). Then, the data processing apparatus 100 generates the address element storage unit 122 as shown in FIG. 4 by associating each address element with the extracted address ID. Here, the data processing apparatus 100 has been described as generating the address element storage unit 122, but it may be created externally and given to the data processing apparatus 100.

  The control unit 130 controls the data processing apparatus 100 as a whole, and includes a reception unit 131, a primary search unit 132, a secondary search unit 133, and a rewrite unit 134. The accepting unit 131 accepts the processing target address data output from the target data input / output unit 110.

  The primary search unit 132 searches for correction candidate address data for correcting the processing target address data received by the reception unit 131. Specifically, the primary search unit 132 includes an extraction unit 132a and a primary specification unit 132b.

  The extraction unit 132a extracts the address ID stored in association with the address element included in the processing target address data from among the address IDs stored in the address element storage unit 122. Specifically, the extraction unit 132a performs character string matching by sequentially substituting the processing target address data for the automaton formed by the address elements stored in the address element storage unit 122. Then, the extraction unit 132a extracts, from the address element storage unit 122, an address ID in which the address element stored in the address element storage unit 122 matches the address element included in the processing target address data.

  For example, the processing target address data received by the receiving unit 131 is “1st Shimoodanaka, Nakahara-ku, Kawasaki City, Kanagawa Prefecture”, and various information stored in the address element storage unit 122 is in the state shown in FIG. It shall be. In this case, the extraction unit 132a extracts the address ID “1-499” stored in association with “Kanagawa Prefecture” included in the processing target address data from the address element storage unit 122. Similarly, the extraction unit 132a stores the address ID “1-100” stored in association with “Kawasaki City” and the address ID stored in association with “Nakahara Ward” from the address element storage unit 122. “1-20” is extracted. In addition, the extraction unit 132a stores the address ID “5-9” stored in association with “Shimoodanaka” and the address ID “1chome” stored in association with “1 chome” from the address element storage unit 122. 1: 5: 101: ...: 500: ... ".

  Thus, since the extraction unit 132a performs the character string matching process using the automaton, the address ID can be extracted from the address element storage unit 122 by one character string matching process. The extraction unit 132a performs the character string matching process using, for example, a character string matching engine “SIGMA”.

  The primary specification part 132b specifies address ID which shows the correction candidate address data for correcting process target address data. Specifically, the primary specifying unit 132b specifies an address ID by calculating a logical product of a set of address IDs extracted by the extracting unit 132a. In other words, the primary specifying unit 132b specifies the address ID that is most frequently included in the set of address IDs extracted by the extracting unit 132a. Then, when the identified address ID is one, the primary identification unit 132b outputs the address ID to the rewriting unit 134. On the other hand, when there are a plurality of specified address IDs, the primary specifying unit 132b outputs the plurality of address IDs to the secondary search unit 133.

  Here, the address ID specifying process by the primary specifying unit 132b will be specifically described with reference to FIG. FIG. 7 is a diagram for explaining the address ID specifying process by the primary specifying unit 132b. In the example shown in FIG. 7, it is assumed that the processing target address data received by the receiving unit 131 is “1-chome Shimo-Odanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” as in the above example. The upper part of FIG. 7 shows the address ID extracted by the extraction unit 132a. Here, for convenience of explanation, an address element and a type are shown in addition to the address ID.

  In the example illustrated in FIG. 7, the primary identification unit 132b includes the address IDs “1-499”, “1-100”, “1-20”, “5-9”, and “1:” extracted by the extraction unit 132a. 5: 101: ...: 500: ... "is calculated. In the lower part of FIG. 7, the range of address IDs corresponding to each address element is indicated by the width of a rectangle with diagonal lines. As illustrated in the lower part of FIG. 7, the primary specifying unit 132b specifies the address ID “5” as the address ID that is most frequently included in the set of address IDs extracted by the extracting unit 132a as a result of the AND operation.

  The secondary search unit 133 searches for correction candidate address data from a plurality of address data indicated by a plurality of address IDs input from the primary specifying unit 132b. Specifically, the secondary search unit 133 searches for correction candidate address data by the N-gram method (also referred to as “N-character index method”), and includes a dividing unit 133a and a secondary specifying unit 133b.

  The dividing unit 133a divides the processing target address data every predetermined number of characters. In the first embodiment, the secondary search unit 133 uses a bigram which is a kind of N-gram method. Further, the dividing unit 133a divides the processing target address data so that each divided character string overlaps the preceding and following character strings one character at a time. That is, the dividing unit 133a divides the processing target address data into two character units while overlapping each character.

  The dividing process of the processing target address data by the dividing unit 133a will be specifically described with reference to FIG. FIG. 8 is a diagram for explaining the division processing of the processing target address data by the division unit 133a. In the example illustrated in FIG. 8, it is assumed that the processing target address data is “1 Chome, Shimooda, Nakahara-ku, Kawasaki City, Kanagawa Prefecture”. In such a case, as shown in FIG. 8, the dividing unit 133a converts the processing target address data into “Kana”, “Nagawa”, “Kawa Prefecture”,..., “Ta 1”, “1 Chome”, “Chome”. ”.

  The secondary specifying unit 133b specifies correction candidate address data from a plurality of regular address data indicated by a plurality of address IDs input from the primary specifying unit 132b. Specifically, the secondary specifying unit 133b acquires, for each address ID, the regular address data stored in association with the plurality of address IDs input from the primary specifying unit 132b from the address storage unit 121. Subsequently, the secondary specifying unit 133b sequentially substitutes the regular address data acquired from the address storage unit 121 for the automaton formed by the character strings divided by the dividing unit 133a. Thereby, the secondary identification unit 133b sequentially collates the character string divided by the dividing unit 133a with the character string included in the regular address data acquired from the address storage unit 121.

  Subsequently, the secondary specifying unit 133b specifies the normal address data having the largest number of character strings that match the character strings divided by the dividing unit 133a among the normal address data acquired from the address storage unit 121. Then, the secondary specifying unit 133b outputs the address ID corresponding to the regular address data specified by the matching process (bigram) to the rewriting unit 134.

  Here, the address data specifying process by the secondary specifying unit 133b will be specifically described with reference to FIG. FIG. 9 is a diagram for explaining address data specifying processing by the secondary specifying unit 133b. In FIG. 9, as in the example shown in FIG. 8, it is assumed that the processing target address data “1-chome Shimooda, Nakahara-ku, Kawasaki-shi, Kanagawa” is divided by the dividing unit 133a. Also, it is assumed that the secondary identification unit 133b has received the address IDs “1” and “5” from the primary identification unit 132b. That is, the secondary specifying unit 133b acquires the regular address data “1 Kamiodanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” and “1-chome Shimo-Odanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” from the address storage unit 121.

  In such a case, the secondary specifying unit 133b sequentially substitutes the regular address data “Kamiodachi 1-chome, Nakahara-ku, Kawasaki-shi, Kanagawa” for the automaton formed by the character string divided by the dividing unit 133a. As a result, the secondary specifying unit 133b sequentially collates the character string divided by the dividing unit 133a with the character string included in the legitimate address data “Kamiodaku 1-chome, Nakahara-ku, Kanagawa Prefecture”. In the example illustrated in FIG. 9, the secondary identification unit 133 b includes 12 character strings (“Kana”, “Nagawa”, “Kawa Prefecture”, “Kenagawa”) among the character strings divided by the dividing unit 133 a. , “Kawasaki”, “Saki City”, “Ichichu”, “Nakahara”, “Hara-ku”, “Oda”, “1”, “Chome”) is the official address data “Nakahara-ku, Kawasaki-shi, Kanagawa It is detected that it matches the character string included in “Odanaka 1-chome”.

  Subsequently, the secondary specifying unit 133b sequentially substitutes the regular address data “1-chome Shimo-Odanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” for the automaton formed by the character string divided by the dividing unit 133a. Thereby, the secondary specific | specification part 133b collates sequentially the character string divided | segmented by the division | segmentation part 133a, and the character string contained in address data "Kamozaki-shi, Nakahara-ku, Shimo-Odanaka 1-chome". In the example shown in FIG. 9, the secondary specifying unit 133 b includes 14 character strings (“Kana”, “Nagawa”, “Kawa Prefecture”, “Kenagawa”) among the character strings divided by the dividing unit 133 a. , “Kawasaki”, “Saki City”, “Munich”, “Nakahara”, “Hara Ward”, “Ward Shimo”, “Shimoko”, “Oda”, “1”, “Chome”) are regular It is detected that it matches the character string contained in the address data “Kamiodachi 1-chome, Nakahara-ku, Kawasaki-shi, Kanagawa”

  Subsequently, in the secondary identification unit 133b, the regular address data "1 Shimo-Odanaka 1-chome, Nakahara-ku, Kawasaki-shi, Kanagawa" is more divided than the regular address data "1-chome Nakagami-ku, Kawasaki-shi, Kanagawa" 133a It is determined that the number of character strings that match the character string divided by is large. Then, the secondary specifying unit 133b specifies the regular address data “1st Shimoodanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” as the correction candidate address data, and outputs the corresponding address ID “5” to the rewriting unit 134.

  Thus, since the secondary specific | specification part 133b performs a character string collation process using an automaton, it can identify correction candidate address data by one character string collation process. In addition, the secondary specific | specification part 133b performs the said character string collation process using the character string collation engine "SIGMA" similarly to the extraction part 132a, for example.

  The rewriting unit 134 rewrites the processing target address data with the regular address data specified by the primary specifying unit 132b or the secondary specifying unit 133b, and stores various log information related to the data correction processing in the log storage unit 124.

  Specifically, when the rewriting unit 134 receives an address ID from the primary specifying unit 132b, the rewriting unit 134 acquires the regular address data stored in association with the address ID from the address storage unit 121. Subsequently, the rewrite unit 134 rewrites the processing target address data stored in the predetermined storage unit to the regular address data (correction candidate address data) acquired from the address storage unit 121. At this time, the rewriting unit 134 logs the date and time (year / month / day / hour / minute / second) when the address data rewriting process is executed, the processing target address data, the correction candidate address data, the difference between the processing target address data and the correction candidate address data, and the like. The data is stored in the storage unit 124.

  Moreover, the rewriting part 134 determines the number of received address ID, when address ID is received from the secondary specific | specification part 133b. When the number of one address ID is received from the secondary specifying unit 133b, the rewriting unit 134 converts the processing target address data stored in the predetermined storage unit into the address data (corrected) received from the secondary specifying unit 133b. (Candidate address data) and various log information related to the address data rewriting process are stored in the log storage unit 124.

  On the other hand, when a plurality of address IDs are received from the secondary specifying unit 133b, the rewriting unit 134 performs the date and time of the address data rewriting process, the processing target address data, and the secondary specifying unit 133b without performing the data correction process. Are stored in the log storage unit 124. Thereby, the system administrator or the like can immediately determine to which correction candidate address data the processing target address data is to be corrected based on the log information.

  Note that the rewriting unit 134 may rewrite the address data by outputting the correction candidate address data to the target data input / output unit 110. For example, when the processing target address data is stored in a predetermined storage unit included in another information processing apparatus, the rewrite unit 134 outputs the processing target address data to the target data input / output unit 110 by outputting the address data. It becomes possible to rewrite the correction candidate address data. The target data input / output unit 110 may output via a network.

  Further, the rewrite unit 134 may cause the log storage unit 124 to store configuration information in which a difference between the processing target address data and the correction candidate address data exists. In such a case, the rewrite unit 134 acquires the configuration information of the correction candidate address data from the configuration information storage unit 123. Then, the rewrite unit 134 compares the configuration information acquired from the configuration information storage unit 123 with the configuration information forming the processing target address data, so that there is a difference between the processing target address data and the correction candidate address data. Identify configuration information. Note that the rewrite unit 134 may calculate a difference between the configuration information of the correction candidate address data and the configuration information forming the processing target address data by calculating a logical product of the configuration information of the correction candidate address data.

  Further, the rewriting unit 134 may compare the processing target address data with the correction candidate address data, and may perform the address data rewriting process when both the address data do not match. As a result, the rewriting unit 134 does not perform the address data rewriting process when both the address data match, so the address data rewriting process can be performed at a lower load and at a higher speed.

  Further, the rewriting unit 134 may perform a process of storing the processing target address data and the correction candidate address data in the log storage unit 124 without performing the address data rewriting process. In such a case, the system administrator or the like can determine whether or not to perform the address data rewriting process based on the log information stored in the log storage unit 124. When the system administrator or the like determines that the address data rewriting process is to be performed, the system administrator can perform the address data rewriting process.

  Further, the rewrite unit 134 may control display of various log information related to the data correction process on a predetermined display unit. For example, when the user inputs an address into a predetermined input form (such as a browser), the control unit 130 receives the input address data and the control unit 130 performs the data correction process described above. Do. Then, the rewriting unit 134 controls the display of the correction candidate address data on the display unit when the address data input by the user is different from the correction candidate address data. Thereby, the user can confirm the address where the notation is unified in real time when inputting the address. Further, the data processing apparatus 100 can store the address data with the same notation in the storage unit without performing the correction process on the address data stored in the predetermined storage unit.

  Next, a procedure of data correction processing by the data processing apparatus 100 according to the first embodiment will be described. FIG. 10 is a flowchart illustrating the data correction processing procedure performed by the data processing apparatus 100 according to the first embodiment. Note that the data correction processing procedure shown in FIG. 10 operates as a batch process at a predetermined date and time and while the data processing apparatus 100 is executing another process (for example, a Web application activation process). Or run in the background.

  FIG. 10 illustrates an example in which the data processing apparatus 100 performs data correction processing for one piece of processing target address data. When performing data correction processing for a plurality of processing target address data, the data processing apparatus 100 repeats the processing procedure shown in FIG. 10 by the number of processing target address data.

  As shown in FIG. 10, the target data input / output unit 110 of the data processing apparatus 100 acquires processing target address data from a predetermined storage unit (step S101). The target data input / output unit 110 may receive processing target address data from another information processing apparatus via a network. Subsequently, the receiving unit 131 receives processing target address data from the target data input / output unit 110.

  Subsequently, the extraction unit 132a performs character string matching by sequentially substituting the processing target address data received by the reception unit 131 for the automaton formed by the address elements stored in the address element storage unit 122. Perform (step S102). Then, the extraction unit 132a extracts the address ID stored in association with the address element included in the processing target address data from the address element storage unit 122 (step S103).

  Subsequently, the primary specifying unit 132b specifies the address ID by calculating the logical product of the set of address IDs extracted by the extracting unit 132a (step S104). When the address ID specified by the primary specifying unit 132b is one (Yes at Step S105), the rewrite unit 134 acquires the regular address data stored in association with the address ID from the address storage unit 121. (Step S106). Subsequently, the rewriting unit 134 rewrites the processing target address data stored in the predetermined storage unit to the regular address data (correction candidate address data) acquired from the address storage unit 121 (step S107).

  In addition, the rewriting unit 134 stores various log information related to the address data rewriting process in the log storage unit 124 (step S108). When the data processing apparatus 100 receives the processing target address data from another information processing apparatus via the network, the rewrite unit 134 acquires the processing target address data via the network in the processing procedure of step S106. Rewritten to the registered regular address data.

  On the other hand, when the address ID specified by the primary specifying unit 132b is not one (No at Step S105), the dividing unit 133a divides the processing target address data every predetermined number of characters (Step S109). Subsequently, the secondary specifying unit 133b acquires, for each address ID, the regular address data stored in association with the plurality of address IDs specified by the primary specifying unit 132b from the address storage unit 121 (Step S110). .

  Subsequently, the secondary specifying unit 133b performs character string collation by sequentially substituting the regular address data acquired in step S110 with respect to the automaton formed by the character string divided by the dividing unit 133a ( Step S111). Subsequently, the secondary identification unit 133b includes the address ID corresponding to the regular address data having the largest number of character strings that match the character strings divided by the dividing unit 133a among the regular address data acquired in step S110. Is specified (step S112).

  Subsequently, when the address ID specified by the secondary specifying unit 133b is one (Yes at Step S113), the rewriting unit 134 converts the processing target address data stored in the predetermined storage unit to the secondary specifying unit. The regular address data specified by 133b is rewritten (step S114). In addition, the rewriting unit 134 stores various log information related to the address data rewriting process in the log storage unit 124 (step S108).

  On the other hand, when the address ID specified by the secondary specifying unit 133b is not one (No at Step S113), the rewriting unit 134 uses the date and time when the address data rewriting process is executed, the processing target address data, the secondary specifying unit 133b. A plurality of specified regular address data and the like are stored in the log storage unit 124 (step S115).

  Next, an example of data correction processing by the data processing apparatus 100 will be described with reference to FIGS. FIGS. 11 to 13 are diagrams for explaining an example of data correction processing by the data processing apparatus 100 according to the first embodiment. In the three examples described below, various types of information stored in the address storage unit 121, the address element storage unit 122, and the configuration information storage unit 123 are as shown in FIGS. 3, 4, and 5, respectively. It shall be.

  First, the data correction processing by the data processing apparatus 100 when the processing target address data is “1st Shimo-Odanaka 1-chome, Kawasaki City, Kanagawa Prefecture” will be described with reference to FIG. The correction candidate address data for correcting this processing target address data “1st Shimoodanaka, Kawasaki City, Kanagawa” is “1st Shimoodanaka, Nakahara-ku, Kawasaki City, Kanagawa Prefecture”. That is, “Nakahara-ku” is missing in the address data to be processed “1 Shimo-Odanaka 1-chome, Kawasaki-shi, Kanagawa” as compared with the correction candidate address data whose notation is unified.

  In this case, the extraction unit 132a of the data processing device 100 receives the address IDs “1-499” and “1-100” from the address element storage unit 122 as a result of the character string matching process using the automaton, as shown in FIG. ”,“ 5-9 ”and“ 1: 5: 101:...: 500:.

  Subsequently, the primary specifying unit 132b specifies an address ID “5” from the extracted address IDs by calculating a logical product of the extracted address IDs. Subsequently, the rewriting unit 134 specifies the address data “Nakahara, Kawasaki-shi, Kanagawa, from the address storage unit 121 because the primary identification unit 132b has identified one address ID. Acquired “Kita Shimo-Odanaka 1-chome”. Then, the rewriting unit 134 rewrites the processing target address data “1st Shimoodanaka, Kawasaki City, Kanagawa” to “1st Shimoodanaka, Nakahara-ku, Kawasaki City, Kanagawa”.

  Further, the rewriting unit 134 acquires the configuration information “prefecture | city / city / county / government / town / town name | chome character” stored in association with the address ID “5” from the configuration information storage unit 123. . Then, the rewriting unit 134 determines whether or not the acquired configuration information matches the configuration information that forms the processing target address data. Here, the rewriting unit 134 determines that the configuration information “political ordinance-ward town and village” does not match.

  Then, the rewrite unit 134 stores log information in the log storage unit 124. At this time, the rewriting unit 134 causes the log storage unit 124 to store, for example, log information indicating that the configuration information “Government-designated ward / town / village” has been rewritten or that the configuration information “political-designated ward / village” has been supplemented. Further, for example, the rewriting unit 134 stores the difference between the processing target address data “1st Shimoodanaka, Kawasaki City, Kanagawa” and the correction candidate address data “1st Shimododa, Nakahara-ku, Kawasaki City, Kanagawa Prefecture” in the log storage unit 124. Remember me.

  As described above, the data processing apparatus 100 can perform one character string matching process and one time even when the configuration information (in the example of FIG. Correction candidate address data can be specified by the arithmetic processing. That is, the data processing apparatus 100 can perform the data correction process at a low load and at a high speed even when the configuration information is missing from the processing target address data.

  Next, the data correction processing by the data processing device 100 when the processing target address data is “1 Shimoodanaka, Nakahara-ku, Yokokawasaki-shi, Kanagawa” will be described with reference to FIG. The correction candidate address data for correcting the processing target address data “1st Shimoodanaka, Nakahara-ku, Yokokawasaki-shi, Kanagawa” is “1chome Shimododa, Nakahara-ku, Kawasaki-shi, Kanagawa-ken”. In other words, the address data to be processed “1-chome, Shimo-Odanaka, Nakahara-ku, Yokokawasaki-shi, Kanagawa” is given an extra “horizontal” one character before “Kawasaki-shi” compared to the address data with the same notation. Has been.

  In such a case, the extraction unit 132a of the data processing apparatus 100 receives the address IDs “1-499”, “851-855”, “1-100” from the address element storage unit 122 as a result of the character string matching process using the automaton. , “1-20”, “5-9” and “1: 5: 101:...: 500:. The address ID “851-855” is the address ID of the address data including the town name character “Yokogawa”.

  Subsequently, the primary specifying unit 132b specifies an address ID “5” from the extracted address IDs by calculating a logical product of the extracted address IDs. Subsequently, the rewriting unit 134 acquires from the address storage unit 121 address data “1-chome Shimoodanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” stored in association with the address ID “5”. Then, the rewriting unit 134 rewrites the processing target address data “1-chome Shimo-Odanaka, Nakahara-ku, Yokokawasaki-shi, Kanagawa” to “1-chome Shimo-Odanaka, Nakahara-ku, Kawasaki-shi, Kanagawa”.

  Further, the rewriting unit 134 acquires the configuration information “prefecture | city / city / county / government / town / town name | chome character” stored in association with the address ID “5” from the configuration information storage unit 123. . Then, the rewriting unit 134 determines whether or not the acquired configuration information matches the configuration information that forms the processing target address data. Here, the rewrite unit 134 determines that the configuration information acquired from the configuration information storage unit 123 matches the configuration information forming the processing target address data.

  Then, the rewrite unit 134 stores log information in the log storage unit 124. At this time, the rewriting unit 134 logs, for example, the difference between the processing target address data “1-chome Shimo-Odanaka, Nakahara-ku, Yokokawasaki-shi, Kanagawa” and correction candidate address data “1-chome Shimo-Odanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” The data is stored in the storage unit 124. In addition, the rewrite unit 134 identifies configuration information in which such a difference exists, and stores the identified configuration information in the log storage unit 124.

  As described above, the data processing apparatus 100 can correct the correction candidate address data by performing one character string matching process and one operation process even when an extra character string is added to the processing target address data. Can be specified. That is, the data processing apparatus 100 can perform the data correction process with low load and high speed even when an extra character string is added to the processing target address data.

  Next, the data correction processing by the data processing apparatus 100 when the processing target address data is “1 Odanaka, Nakahara-ku, Kawasaki City, Kanagawa Prefecture” will be described with reference to FIG. It is assumed that the candidate address data for correcting the processing target address data “1 Odanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” is “1 Ochinaka Shimo-oda, Nakahara-ku, Kawasaki-shi, Kanagawa”. That is, the address data to be processed “1 Odanaka 1-chome, Nakahara-ku, Kawasaki-shi, Kanagawa” is missing “lower” one character before “Odanaka” compared to the address data whose notation is unified.

  In such a case, the extraction unit 132a of the data processing apparatus 100 obtains the address IDs “1-499”, “1-100”, “1-20” from the address element storage unit 122 as a result of the character string matching process using the automaton. And “1: 5: 101:...: 500:...” Are extracted.

  Subsequently, the primary specifying unit 132b specifies address IDs “1” and “5” from the extracted address IDs by calculating a logical product of the extracted address IDs. This is because the most frequently included address IDs among the address IDs extracted by the extraction unit 132a are “1” and “5”.

  Subsequently, the dividing unit 133a divides the processing target address data into units of two characters while overlapping each character “Odanaka 1-chome, Nakahara-ku, Kawasaki City, Kanagawa Prefecture” character by character. Specifically, the dividing unit 133a converts the address data to be processed into “Kan”, “Nagawa”, “Kawa Prefecture”, “Kenagawa”, “Kawasaki”, “Saki City”, “Middle City”, “Nakahara”, “Hara Ward”, “ “Oda” “Tanaka” “Middle 1” “1 Chome” “Chome”.

  Subsequently, the secondary specifying unit 133b stores the address data “Kamiodachi 1-chome, Nakahara-ku, Kawasaki-shi, Kanagawa” and the address ID “5” stored in the address storage unit 121 in association with the address ID “1”. The address data “1-chome Shimo-Odanaka, Nakahara-ku, Kawasaki-shi, Kanagawa”, which is stored in association with, is acquired. Subsequently, the secondary specifying unit 133b uses the automaton formed by the character strings divided by the dividing unit 133a to perform character string matching between the address data acquired from the address storage unit 121 and the divided character strings. Do.

  Here, as shown in FIG. 13, the secondary specifying unit 133b includes 14 character strings out of the character strings divided by the dividing unit 133a, and the address data “Nakahara, Kawasaki City, Kanagawa Prefecture”. It is detected that it matches the character string included in “Kamikami Odanaka 1-chome”. Similarly, the secondary identifying unit 133b includes 14 character strings out of the character strings divided by the dividing unit 133a in the address data “Shomoodanaka 1-chome, Nakahara-ku, Kawasaki-shi, Kanagawa”. Detects that it matches the contained string.

  That is, in the example illustrated in FIG. 13, the address data with the address ID “1” and the address data with the address ID “5” have the number of character strings that match the character strings divided by the dividing unit 133 a. equal. Therefore, the rewriting unit 134 does not rewrite the processing target address data, the date and time when the address data rewriting process is executed, the processing target address data, the address data with the address ID “1”, and the address data with the address ID “5”. And the like are stored in the log storage unit 124.

  As described above, the data processing apparatus 100 causes the log storage unit 124 to store the plurality of specified correction candidate address data even when the correction candidate address data cannot be uniquely specified. As a result, the system administrator or the like can obtain candidates for determining which correction candidate address data to rewrite the processing target address data based on the log information.

  In addition, the data processing apparatus 100 is based on various information memorize | stored in the structure information memory | storage part 123, when the municipality of a processing target address data, a government-designated municipality, etc. are replaced. It is possible to detect replacement of towns and villages. The case where the processing target address data is “1-chome Shimoodanaka, Kawasaki City, Nakahara-ku, Kanagawa Prefecture” will be described as an example. In such a case, the data processing device 100 specifies “5” as the address ID of the correction candidate address data for correcting the processing target address data.

  At this time, the data processing apparatus 100 obtains the configuration information “prefecture | city / city / county / government / town / city name / chome character” stored in association with the address ID “5” from the configuration information storage unit 123. get. Then, the data processing apparatus 100 compares the acquired configuration information with the configuration information “prefecture | decrement | decorative town / city | city / city | town name | chome character” of the address data to be processed. Thereby, the data processing apparatus 100 can detect that the municipality and the government-designated municipality of the processing target address data are interchanged. The data processing apparatus 100 may store the replacement information of such municipalities and government-designated municipalities in the log storage unit 124.

  As described above, the data processing apparatus 100 according to the first embodiment is included in the address element and the processing target address data using the automaton formed by the address elements stored in the address element storage unit 122. Perform string matching with address elements. Then, the data processing device 100 specifies the address ID by calculating the logical product of the address IDs acquired from the address element storage unit 122. Thereby, the data processing apparatus 100 can specify the correction candidate address data by performing one character string matching process and one calculation process. As a result, the data processing apparatus 100 can specify the correction candidate address data with low load and high speed, and can perform data correction processing with low load and high speed.

  In addition, when a plurality of address IDs are specified as a result of the logical product operation, the data processing apparatus 100 specifies the correction target address data using the N-gram method. Thereby, the data processing device 100 can specify the correction target address data by performing the character string matching process twice and the calculation process once. As a result, the data processing apparatus 100 can specify the correction target address data with low load and high speed, and can perform data correction processing with low load and high speed.

  In addition, when a plurality of address data is specified as a result of the character string matching process using the N-gram method, the data processing apparatus 100 stores the specified plurality of address data in the log storage unit 124. Thereby, the system administrator or the like can obtain candidates for determining which address data to rewrite the processing target address data based on the log information.

  In the first embodiment, the example in which the address element storage unit 122 stores the address elements whose notation is unified (address elements included in the address data stored in the address storage unit 121) is shown. The address element storage unit 122 may store address elements whose notations are not unified. For example, the address element storage unit 122 stores address elements whose notation is likely to be inconsistent, so that the data processing apparatus 100 has the notation of address data including address elements whose notation is likely to be inconsistent. It can be easily corrected to address data.

  This will be specifically described below with reference to FIGS. 14 and 15. FIG. 14 is a diagram illustrating an example of an address element storage unit 122 that stores address elements whose notation is not unified. In the example shown in FIG. 14, “+” written in the type indicates an address element whose notation is not unified. A case where a record in which “+” is written in such a type is added is, for example, a case where there is an address element in which the notation is likely to be inconsistent.

  Specifically, in the address element storage unit 122 shown in FIG. 14, as a character string in which the notation of the address element “Kashiwamachi” (11th line in FIG. 14) whose notation is unified is likely to be inconsistent. A variant of “Kashiwamachi” (12th line in FIG. 14) is added. Similarly, in the address element storage unit 122 shown in FIG. 14, “Kojimachi” (13th line in FIG. 14) in which “Kashiwacho” is written in hiragana is added.

  Next, an example of data correction processing by the data processing apparatus 100 using the address element storage unit 122 that stores address elements whose notation is not unified will be described. FIG. 15 is a diagram for explaining an example of the data correction process when the address element storage unit 122 that stores address elements whose notation is not unified is used.

  In the example shown in FIG. 15, it is assumed that the processing target address data is “Kojicho 1-chome, Chiyoda-ku, Tokyo”. The correction candidate address data for correcting this processing target address data “Kojicho 1-chome, Chiyoda-ku, Tokyo” is “1-chome Kojimachi, Chiyoda-ku, Tokyo”. That is, in the address data to be processed “Kojicho 1-chome, Chiyoda-ku, Tokyo”, the character string “麹” is written in Hiragana compared to the address data whose notation is unified.

  In this case, the extraction unit 132a of the data processing apparatus 100 receives the address IDs “500-1500” and “500-599” from the address element storage unit 122 as a result of the character string matching process using the automaton, as shown in FIG. ”,“ 500-510 ”and“ 1: 5: 101:...: 500:.

  Subsequently, the primary specifying unit 132b specifies the address ID “500” from the extracted address IDs by calculating a logical product of the extracted address IDs. Subsequently, the rewriting unit 134 acquires the address data “1-chome, Sakaimachi, Chiyoda-ku, Tokyo” stored in association with the address ID “500” from the address storage unit 121. Then, the rewriting unit 134 rewrites the processing target address data “Kojimachi 1-chome, Chiyoda-ku, Tokyo” to “1 Chome-cho, Chiyoda-ku, Tokyo”.

  Then, the rewrite unit 134 stores log information in the log storage unit 124. At this time, since the rewrite unit 134 includes “+” in the type corresponding to the address element “Kojimachi” acquired from the address element storage unit 122, the log indicating that the configuration information “Government-designated city” has been rewritten. Information is stored in the log storage unit 124.

  As described above, by storing address elements whose notation is not unified in the address element storage unit 122, the data processing apparatus 100 unifies the address data including address elements whose notation is likely to be ununiform. It can be easily corrected to the address data.

  Incidentally, in the first embodiment, the example in which the primary identification unit 132b of the data processing apparatus 100 identifies the address ID by calculating the logical product of the set of address IDs extracted by the extraction unit 132a has been described. In other words, in the first embodiment, the example in which the primary specifying unit 132b specifies the address ID most frequently included in the set of address IDs extracted by the extracting unit 132a by calculating a logical product.

  However, the data processing device may give importance to the address elements stored in the address element storage unit. Then, when the processing target address data includes a highly important address element, the data processing apparatus may specify the address data including the address element as the correction candidate address data. Further, the data processing apparatus may exclude address elements with low importance from the logical product operation. Therefore, in the second embodiment, an example in which importance is given to an address element stored in the address element storage unit will be described.

  First, the configuration of the data processing apparatus 200 according to the second embodiment will be described. FIG. 16 is a diagram illustrating the configuration of the data processing device 200 according to the second embodiment. As illustrated in FIG. 16, the data processing device 200 includes an address element storage unit 222 instead of the address element storage unit 122 and replaces the primary identification unit 132 b as compared with the data processing device 100 illustrated in FIG. 2. Has a primary identification unit 232b.

  An example of the address element storage unit 222 is shown in FIG. As illustrated in FIG. 17, the address element storage unit 222 has a new item “importance” as compared to the address element storage unit 122 illustrated in FIG. 4. The item “importance” stores the importance of information stored in the corresponding “address element”.

  In the example illustrated in FIG. 17, the address element storage unit 222 stores “0” as the importance of the address elements “Kanagawa” and “Tokyo” whose type is “prefecture”. Here, the importance “0” indicates that the importance is low. The importance “0” indicates that it may be excluded from the logical product operation executed by the primary specifying unit 232b described later.

  Such importance “0” is given to an address element that is unnecessary for specifying an address. For example, as in the example illustrated in FIG. 17, the importance “0” is assigned to the type “prefecture”. This is because, in general, even if the prefecture is unknown, the address can be specified if the municipality, government-designated city, town name, and chome character are clear.

  In the example illustrated in FIG. 17, the address element storage unit 222 stores “1” as the importance of the address element “XX hospital” whose type is “specific name”. Here, the importance level “1” indicates that the importance level is high. Then, when the corresponding address element (in the example of FIG. 17, “XX hospital”) is included in the processing target address data, the importance “1” is assigned to the corresponding address ID by the primary specifying unit 232b described later. (In the example of FIG. 17, “101”) may be specified.

  Such importance “1” is given to an address element (for example, a building name, a building name, or a facility name) that can uniquely identify an address. For example, as in the example illustrated in FIG. 17, importance “1” is assigned to “XX hospital”. This is because the address can be uniquely identified if “XX hospital” becomes clear.

  The primary specifying unit 232b specifies an address ID by calculating a logical product and a logical sum for the set of address IDs extracted by the extracting unit 132a. At this time, the primary identification unit 232b excludes the address ID stored in the address element storage unit 222 in association with the importance “0” from the address ID extracted by the extraction unit 132a, and performs a logical product. Calculate. Further, the primary specifying unit 232b calculates the logical product of the address IDs for which the importance level is not set, and calculates the logical sum of the logical product calculation result and the address ID having the importance level “1”.

  Here, an example of data correction processing by the data processing device 200 will be described with reference to FIGS. 18 and 19. 18 and 19 are diagrams for explaining an example of the data correction process by the data processing apparatus 200 according to the second embodiment. In the two examples described below, it is assumed that various information stored in the address storage unit 121 and the address element storage unit 222 are in the states illustrated in FIGS. 3 and 17, respectively.

  First, the data correction processing by the data processing apparatus 200 when the processing target address data is “1st Shimoodanaka, Nakahara-ku, Kawasaki-shi, Tokyo” will be described with reference to FIG. The correction candidate address data for correcting this processing target address data “1 Chome Okanaka, Nakahara-ku, Kawasaki-shi, Tokyo” is “Chome Odanaka 1-chome, Nakahara-ku, Kawasaki City, Kanagawa Prefecture”. That is, the address data to be processed “Kanagawa Prefecture” and “Tokyo” are different from the address data in which the notation is unified in the address data “Shokuodanaka 1-chome, Nakahara-ku, Kawasaki-shi, Tokyo”.

  In this case, the extraction unit 132a of the data processing device 200 receives the address IDs “500-1500” and “1-100” from the address element storage unit 222 as a result of the character string matching process using the automaton, as shown in FIG. ”,“ 1-20 ”,“ 5-9 ”and“ 1: 5: 101:...: 500:.

  Subsequently, the primary specifying unit 232b calculates a logical product of the extracted address IDs. At this time, the primary identification unit 232b calculates a logical product by excluding the address ID “500-1500” having the importance of “0”. That is, the primary specifying unit 232b calculates the logical product of the address IDs “1-100”, “1-20”, “5-9”, and “1: 5: 101:...: 500:. To do. Thereby, the primary specific | specification part 232b specifies address ID "5". Subsequently, the rewriting unit 134 acquires from the address storage unit 121 address data “1-chome Shimoodanaka, Nakahara-ku, Kawasaki-shi, Kanagawa” stored in association with the address ID “5”. Then, the rewriting unit 134 rewrites the processing target address data “1-chome Shimo-Odanaka, Nakahara-ku, Kawasaki-shi, Tokyo” to “1-chome Shimo-Odanaka, Nakahara-ku, Kawasaki-shi, Kanagawa”.

  As described above, the data processing apparatus 200 calculates the logical product by excluding the address ID corresponding to the address element having low importance, and thus can execute the calculation process at a higher speed. That is, the data processing device 200 can specify the correction target address data with a lower load and higher speed.

  Next, data correction processing by the data processing device 200 when the processing target address data is “Yokohama City, Kanagawa Prefecture XX Hospital” will be described with reference to FIG. The correction candidate address data for correcting this processing target address data “Yokohama City ○○ Hospital, Kanagawa Prefecture” is “1 Hospital, Shin-Yokohama 1-chome, Kohoku-ku, Yokohama City, Kanagawa Prefecture”. In other words, the address data to be processed “Yokohama City, Kanagawa Prefecture ○○ Hospital” is missing “Shin-Yokohama 1-chome, Kohoku Ward” compared to address data whose notation is unified.

  In this case, the extraction unit 132a of the data processing device 200 receives the address IDs “1-499” and “101-200” from the address element storage unit 222 as a result of the character string matching process using the automaton, as shown in FIG. ”And“ 101 ”are extracted.

  Subsequently, the primary specifying unit 232b calculates a logical product for the extracted address IDs for which the importance level is not set, and calculates a logical sum for the address ID for which the importance level is set. . In the example illustrated in FIG. 19, the primary specifying unit 232 b calculates (“1-499” AND “101-200”) OR “101”. And the primary specific | specification part 232b specifies address ID of correction candidate address data to address ID "101" as a result of this arithmetic processing.

  Subsequently, the rewriting unit 134 acquires from the address storage unit 121 address data “Hospital in Shin-Yokohama 1-chome, Kohoku-ku, Yokohama-shi, Kanagawa” stored in association with the address ID “101”. Then, the rewrite unit 134 rewrites the processing target address data “Yokohama City, Kanagawa Prefecture ○○ Hospital” to “1 Hospital, Shin-Yokohama, Kohoku-ku, Yokohama City, Kanagawa Prefecture”.

  In this way, the data processing device 200 preferentially specifies the address ID corresponding to the address element having a high importance as the correction candidate address data. Thereby, the data processing device 200 can specify the correction candidate address data with high accuracy when the address element having high importance is included in the processing target address data.

  In the second embodiment, two importance levels (“0” or “1”) have been described. However, the data processing apparatus 200 may assign three or more importance levels to the address element storage unit 222. Good. In such a case, the primary identification unit 232b preferentially identifies the address ID corresponding to the address element as the correction candidate address data as the importance of the address element included in the processing target address data is higher. For example, the primary specifying unit 232b excludes address IDs whose importance is lower than a predetermined threshold and performs a logical sum operation on address IDs whose importance is higher than a predetermined threshold.

  Further, the configurations of the data processing devices 100 and 200 shown in FIGS. 2 and 16 can be variously changed without departing from the gist. For example, a function equivalent to that of the data processing apparatus 100 can be realized by mounting the function of the control unit 130 of the data processing apparatus 100 as software and executing the function by a computer. An example of a computer that executes a data processing program 1071 in which functions of various processing units of the data processing apparatus 100 are installed as software will be described below.

  FIG. 20 is a diagram illustrating a computer 1000 that executes the data processing program 1071. The computer 1000 includes a CPU (Central Processing Unit) 1010 that executes various arithmetic processes, an input device 1020 that receives input of data from a user, a monitor 1030 that displays various information, and a medium that reads a program from a recording medium. A bus 1080 includes a reading device 1040, a network interface device 1050 that exchanges data with other computers via a network, a RAM (Random Access Memory) 1060 that temporarily stores various information, and a hard disk device 1070. Connected and configured.

  The hard disk device 1070 stores a data processing program 1071 having the same function as that of the control unit 130 shown in FIG. The hard disk device 1070 stores data processing related data 1072 corresponding to various data (address storage unit 121, address element storage unit 122, and configuration information storage unit 123) stored in the storage unit 120 shown in FIG. Is done. The hard disk device 1070 stores a log file 1073 corresponding to the log storage unit 124 illustrated in FIG. The data processing related data 1072 or the log file 1073 can be appropriately distributed and stored in another computer connected via the network.

  Then, the CPU 1010 reads out the data processing program 1071 from the hard disk device 1070 and develops it in the RAM 1060, whereby the data processing program 1071 functions as the data processing process 1061. The data processing process 1061 expands information read from the data processing related data 1072 and the like in an area allocated to itself on the RAM 1060 as appropriate, and executes various data processing based on the expanded data and the like. Then, the data processing process 1061 outputs predetermined information to the log file 1073.

  Note that the data processing program 1071 does not necessarily have to be stored in the hard disk device 1070, and the computer 1000 may read and execute this program stored in a storage medium such as a CD-ROM. . The computer 1000 stores the program in another computer (or server) connected to the computer 1000 via a public line, the Internet, a LAN (Local Area Network), a WAN (Wide Area Network), or the like. You may make it read and run a program from these.

  The following supplementary notes are further disclosed with respect to the embodiments including the above examples.

(Supplementary Note 1) Character string storage means for storing a predetermined character string and a character string identifier for identifying the predetermined character string;
A character string element storage means for storing a character string element that is a character string included in the predetermined character string; and a set of character string identifiers indicating the predetermined character string including the character string element;
Extraction means for extracting a set of character string identifiers stored in association with the character string elements included in the character string to be processed from the character string element storage means;
A character string identifier that is most frequently included in the set of character string identifiers extracted by the extracting unit is specified as a character string identifier that indicates a corresponding character string that is a character string that matches or is similar to the character string to be processed. A data processing apparatus comprising: a first specifying unit.

(Supplementary Note 2) When there are a plurality of character string identifiers specified by the first specifying means, a dividing unit that divides the character string to be processed by a predetermined size;
Among the plurality of character strings indicated by the character string identifier specified by the first specifying means, the character string containing the largest number of divided character strings that are character strings divided by the dividing means is specified as the corresponding character string. The data processing apparatus according to appendix 1, further comprising: a second specifying unit that performs the following.

(Additional remark 3) The said extraction means uses the automaton formed by the character string element memorize | stored in the said character string element memory | storage means, The character string element contained in the said character string to be processed, The said character string element A set of character string identifiers stored in association with the character string elements included in the character string to be processed from the character string element storage means by collating with the character string elements stored in the storage means The data processing apparatus according to appendix 1 or 2, characterized in that:

(Supplementary note 4) The first specifying means specifies a character string identifier indicating the corresponding character string by calculating a logical product of a set of character string identifiers extracted by the extracting means. The data processing device according to any one of appendices 1 to 3.

(Supplementary Note 5) The character string element storage unit further stores the importance of the character string element in association with the character string element and the set of character string identifiers,
The first specifying unit includes a character string identifier having a higher importance level stored in the character string element storage unit in the set of character string identifiers extracted by the extraction unit, and indicating the corresponding character string. The data processing device according to any one of appendices 1 to 4, wherein the data processing device is specified as a column identifier.

(Supplementary note 6) The first specifying means is a set of character string identifiers obtained by excluding a set of character string identifiers whose importance is lower than a predetermined threshold from a set of character string identifiers extracted by the extraction means. The data processing apparatus according to appendix 5, wherein a character string identifier that is included in a large amount is specified as a character string identifier that indicates the corresponding character string.

(Additional remark 7) Said 1st specific means calculates the logical product of the set of the character string identifier whose said importance is lower than a predetermined threshold among the character string identifiers extracted by said extraction means, and performs logical product operation A character string identifier indicating the corresponding character string is specified by calculating a logical sum of the result of the above and a set of character string identifiers having a degree of importance higher than a predetermined threshold. The data processing apparatus described in 1.

(Supplementary Note 8) When a character string identifier is uniquely specified by the first specifying means, the character string stored in the character string storage means is associated with the character string identifier in association with the character string identifier to be processed. Rewriting means for rewriting to a string, and when there are a plurality of character string identifiers specified by the first specifying means, the rewriting means for rewriting the character string to be processed to the corresponding character string specified by the second specifying means The data processing device according to any one of appendices 1 to 7, further comprising:

(Supplementary note 9) The data according to supplementary note 8, wherein the rewriting means rewrites the processing target character string to the corresponding character string when the processing target character string is different from the corresponding character string. Processing equipment.

(Supplementary Note 10) Log output means for outputting the corresponding character string, the character string to be processed, and the difference between the corresponding character string and the character string to be processed to a predetermined display unit or a predetermined storage unit The data processing device according to any one of appendices 1 to 9, further comprising:

(Supplementary Note 11) Character string element storage for storing a character string element which is a character string included in a predetermined character string and a set of character string identifiers for identifying the predetermined character string including the character string element An extraction procedure for extracting a set of character string identifiers stored in association with character string elements included in the character string to be processed from the means;
A character string identifier that is most frequently included in the set of character string identifiers extracted by the extraction procedure is specified as a character string identifier indicating a corresponding character string that is a character string that matches or is similar to the character string to be processed. A data processing program that causes a computer to execute the first specific procedure.

(Supplementary Note 12) When there are a plurality of character string identifiers specified by the first specifying procedure, a dividing procedure for dividing the character string to be processed by a predetermined size;
Among the plurality of character strings indicated by the character string identifier specified by the first specifying procedure, the character string containing the largest number of divided character strings that are character strings divided by the dividing procedure is specified as the corresponding character string. The data processing program according to appendix 11, further causing the computer to execute the second specific procedure.

(Supplementary note 13) The character string element storage means further stores the importance of the character string element in association with the character string element and the set of character string identifiers,
In the first specific procedure, a character string identifier having a higher importance stored in the character string element storage unit of the set of character string identifiers extracted by the extraction procedure is a character indicating the corresponding character string. 13. The data processing program according to appendix 11 or 12, characterized by being specified as a column identifier.

(Supplementary Note 14) When a character string identifier is uniquely specified by the first specifying procedure, from the character string storage means for storing the predetermined character string and the character string identifier of the predetermined character string, The character string stored in association with the character string identifier specified by one specific procedure is acquired, the character string to be processed is rewritten to the acquired character string, and is specified by the first specific procedure Additional remarks 11-13, wherein when there are a plurality of character string identifiers, the computer further executes a rewriting procedure for rewriting the character string to be processed into the corresponding character string specified by the second specifying procedure. A data processing program according to any one of the above.

(Supplementary Note 15) A log output procedure for outputting the corresponding character string, the character string to be processed, and the difference between the corresponding character string and the character string to be processed to a predetermined display unit or a predetermined storage unit The data processing program according to any one of appendices 11 to 14, further causing the computer to execute.

(Supplementary Note 16) The data processing device is
Processing from a character string element storage means for storing a character string element that is a character string included in the predetermined character string and a set of character string identifiers for identifying the predetermined character string including the character string element. An extraction step of extracting a set of character string identifiers stored in association with character string elements included in the target character string;
A character string identifier that is most frequently included in the set of character string identifiers extracted in the extraction step is specified as a character string identifier that indicates a corresponding character string that is a character string that matches or is similar to the character string to be processed. A data processing method comprising: a first specific step.

(Supplementary Note 17) When there are a plurality of character string identifiers specified by the first specifying step, a dividing step of dividing the processing target character string into predetermined sizes;
Among the plurality of character strings indicated by the character string identifier specified by the first specifying step, the character string containing the largest number of divided character strings that are character strings divided by the dividing step is specified as the corresponding character string. The data processing method according to appendix 16, further including a second specific step.

(Supplementary Note 18) The character string element storage means further stores the importance of the character string element in association with the character string element and the set of character string identifiers,
In the first specifying step, a character string identifier having a higher importance level stored in the character string element storage unit of the set of character string identifiers extracted in the extraction step is a character indicating the corresponding character string. 18. The data processing method according to appendix 16 or 17, wherein the data is specified as a column identifier.

(Supplementary note 19) When a character string identifier is uniquely specified by the first specifying step, from the character string storage means for storing the predetermined character string and a character string identifier of the predetermined character string, A character string stored in association with the character string identifier specified by one specifying step is acquired, the processing target character string is rewritten to the acquired character string, and the first specifying step specifies Any one of supplementary notes 16 to 18, further comprising a rewriting step of rewriting the character string to be processed with the corresponding character string specified in the second specifying step when there are a plurality of character string identifiers. The data processing method as described in any one.

(Supplementary Note 20) A log output step of outputting the corresponding character string, the character string to be processed, and the difference between the corresponding character string and the character string to be processed to a predetermined display unit or a predetermined storage unit The data processing method according to any one of supplementary notes 16 to 19, further comprising:

It is a figure for demonstrating the outline | summary of the data correction process by the data processor which concerns on Example 1. FIG. 1 is a diagram illustrating a configuration of a data processing apparatus according to a first embodiment. It is a figure which shows an example of an address memory | storage part. It is a figure which shows an example of an address element memory | storage part. It is a figure which shows an example of a structure information storage part. It is a figure for demonstrating the method of producing | generating an address element memory | storage part. It is a figure for demonstrating the address ID specific process by a primary specific part. It is a figure for demonstrating the division | segmentation process of the process target address data by a division part. It is a figure for demonstrating the address data specific process by a secondary specific part. 3 is a flowchart illustrating a data correction processing procedure by the data processing apparatus according to the first embodiment. FIG. 6 is a diagram for explaining an example of a data correction process performed by the data processing apparatus according to the first embodiment. FIG. 6 is a diagram for explaining an example of a data correction process performed by the data processing apparatus according to the first embodiment. FIG. 6 is a diagram for explaining an example of a data correction process performed by the data processing apparatus according to the first embodiment. It is a figure which shows an example of the address element memory | storage part which memorize | stores the address element which is not unified. It is a figure for demonstrating an example of the data correction process at the time of using the address element memory | storage part which memorize | stores the address element which is not unified. FIG. 6 is a diagram illustrating a configuration of a data processing device according to a second embodiment. It is a figure which shows an example of an address element memory | storage part. FIG. 10 is a diagram for explaining an example of data correction processing by a data processing apparatus according to the second embodiment. FIG. 10 is a diagram for explaining an example of data correction processing by a data processing apparatus according to the second embodiment. It is a figure which shows the computer which executes a data processing program.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Data processor 110 Target data input / output part 120 Storage part 121 Address storage part 122 Address element storage part 123 Configuration information storage part 124 Log storage part 130 Control part 131 Reception part 132 Primary search part 132a Extraction part 132b Primary specification part 133 2 Next search unit 133a Division unit 133b Secondary identification unit 134 Rewriting unit 200 Data processing device 222 Address element storage unit 232b Primary identification unit 1000 Computer 1010 CPU
1020 Input device 1030 Monitor 1040 Media reader 1050 Network interface device 1060 RAM
1061 Data processing process 1070 Hard disk device 1071 Data processing program 1072 Data processing related data 1073 Log file 1080 Bus

Claims (8)

Character string storage means for storing a plurality of character strings composed of a plurality of character string elements in association with character string elements that are character strings included in each of the plurality of character strings;
Extraction means for identifying a plurality of character string elements included in the input character string from the input character string, and extracting a plurality of character strings including at least one of the specified character string elements from the character string storage means When,
Corresponding character string corresponding to the input character string from the extracted character strings based on the correspondence relationship between the specified character string elements and the character string elements included in the extracted character strings and a first specifying means for specifying,
The extraction means performs extraction of the plurality of character strings by a single character string matching process between a character string element included in the input character string and a character string element stored in the character string storage means,
The data processing apparatus according to claim 1, wherein the first specifying unit specifies the corresponding character string by a single specifying process between the extracted character strings . A dividing unit that divides the input character string by a predetermined size when there are a plurality of corresponding character strings specified by the first specifying unit;
Second identifying means for identifying the corresponding character string that includes the largest number of divided character strings that are character strings divided by the dividing means among a plurality of corresponding character strings;
The data processing apparatus according to claim 1, further comprising: The character string storage means further stores the importance of the character string element in association with the character string element,
The first specifying means specifies a character string including a character string element having a higher importance among the plurality of character strings extracted by the extracting means as the corresponding character string. Or the data processing apparatus of 2. The specific process, the data processing apparatus according to any one of claims 1 to 3, characterized in that a logical product operation process.   It further comprises log output means for outputting the corresponding character string, the input character string, and the difference between the corresponding character string and the input character string to a predetermined display unit or a predetermined storage unit. The data processing device according to any one of claims 1 to 4. A plurality of character string elements included in the input character string are identified from the input character string, and a plurality of character strings including at least one of the identified plurality of character string elements are configured by a plurality of character string elements. An extraction procedure for extracting a plurality of character strings from a character string storage unit that stores the character strings in association with character string elements that are character strings included in each of the plurality of character strings;
Corresponding character string corresponding to the input character string from the extracted character strings based on the correspondence relationship between the specified character string elements and the character string elements included in the extracted character strings a first specifying step of specifying, a cause the computer to execute a
In the extraction procedure, extraction of the plurality of character strings is performed by a single character string matching process between a character string element included in the input character string and a character string element stored in the character string storage unit,
In the first identification procedure, the corresponding character string is identified by one identification process between the extracted character strings . A dividing procedure for dividing the input character string into predetermined sizes when there are a plurality of corresponding character strings specified by the first specifying procedure;
A plurality of corresponding character strings, a second specifying procedure for specifying, in the corresponding character string, a character string that is the most divided character string divided by the dividing procedure;
The data processing program according to claim 6, further causing a computer to execute. The extraction means included in the computer specifies a plurality of character string elements included in the input character string from the input character string, and a plurality of character strings including at least one of the specified plurality of character string elements An extraction step of extracting a plurality of character strings composed of character string elements from character string storage means for storing in association with character string elements that are character strings included in each of the plurality of character strings;
The specifying means provided in the computer is configured to input the input from the extracted character strings based on a correspondence relationship between the specified character string elements and the character string elements included in the extracted character strings. and the specific process that identifies the corresponding character string corresponding to the character string, only including,
In the extraction step, extraction of the plurality of character strings is performed by a single character string matching process between a character string element included in the input character string and a character string element stored in the character string storage unit,
In the specifying step, the corresponding character string is specified by a single specifying process between the extracted character strings .

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