JP3972309B2 - Information conversion apparatus and program - Google Patents

Description

  The present invention relates to an information conversion apparatus and program, and in particular, every time a character string composed of a plurality of words combined to represent a predetermined object is input, the input character string is input to the program. The present invention relates to an information conversion device for converting into identification information given to a predetermined object presumed to be represented by a character string, and an information conversion program for causing a computer to function as the information conversion device.

  If a financial transaction such as remittance to an account of a different financial institution is requested, a message in which the name of the customer related to the financial transaction (for example, the name of the holder of the remittance account) is set as a character string is financial Messages are sent and received between institutions. On the other hand, a financial institution assigns a customer code (this customer code is called, for example, CIF (Customer Information File)) to each customer, and the computer system in the financial institution is the customer code. Since it is configured to identify customers based on codes and execute instructed financial transactions, when a message is received from another financial institution, a character string representing the customer name set in the received message Needs to be converted to the corresponding customer code.

In relation to the above, Patent Document 1 discloses that a customer code table in which a combination of a plurality of words specifying a customer code and a corresponding customer code is registered in a storage device in advance and converted from input data. There is disclosed a technique for extracting a plurality of words, comparing the extracted plurality of words with a plurality of words registered in a customer code table, and converting them into a customer code if they match.
JP 2002-56005 A

  However, for the customer name set in the above message, the name specified by the client who requested the execution of the financial transaction is set as a character string as it is, so an extra word is added to the regular name, for example. In some cases, the proper name is not set correctly, for example, some of a plurality of words constituting the regular name are missing. In particular, among financial institution customers, a relationship in which a name obtained by adding a specific word to the name of the first specific customer matches the name of the second specific customer (hereinafter, this relationship is referred to as an inclusion relationship). (For example, “NAKAMORI ELECTRIC CO., LTD” and “NAKAMORI ELECTRIC CO., LTD”, etc.). If the character string set in the message matches or substantially matches the customer name having an inclusion relationship, the character string has an extra word added to the regular name, or the word In consideration of the possibility that a part of the character string is missing, it is difficult to automatically determine which of the plurality of customer names having the inclusion relationship the character string represents. In such a case, conventionally, there is no solution other than leaving it to the operator's judgment, and the actual situation is that a great burden is placed on the operator.

  The present invention has been made in consideration of the above facts, and a predetermined object presumed to represent a character string composed of a plurality of words combined to represent the predetermined object. It is an object to obtain an information conversion apparatus and an information conversion program that can improve the probability that conversion to identification information assigned to the item can be automatically performed without bothering the operator.

  A character string that is set for the purpose of representing a specific target (for example, a specific customer) but is different from the regular name of the specific target is an extra word for the regular name as described above. The extra words added to this type of string, for example, "NAKAMORI ELECTRIC CO., LTD" has an extra word "MARUNOUCHI" added to it. In many cases, the word is a fixed word for each object. The inventor of the present application pays attention to the above facts, and identifies a character string formed by combining a plurality of words to represent a predetermined object, given to the predetermined object estimated to be represented by the character string. When converting to information, if an extra word (unnecessary word) added to a character string that has been converted to identification information in the past is stored and used to convert a new character string, the character string The present invention has been made on the assumption that it is possible to improve the probability of appropriate automatic conversion to identification information.

  Based on the above, the information conversion apparatus according to the first aspect of the present invention provides an input character string each time a character string configured by combining a plurality of words to represent a predetermined object is input. An information conversion apparatus for converting into identification information given to the predetermined object presumed to be represented by the inputted character string, and for each object to which identification information is given, A first storage means for storing a name dictionary registered by associating a combination of the identification information and a word constituting a character string representing an individual object, and a word constituting the inputted character string By comparing each combination with a combination of words registered in the name dictionary, a combination of words constituting the input character string and a combination of words that completely or partially match in units of words are obtained. A search means for searching; A conversion for determining an object presumed to be represented by the input character string and converting the input character string into identification information given to the determined object based on a search result by the search means A combination of words excluding specific words from a plurality of words constituting the input character string is included in the combinations of words extracted by the search by the means and the search means; and When the conversion means determines that the input character string represents a specific object corresponding to a combination of words excluding the specific word, the specific word is converted to the specific object. Unnecessary word registration means for registering as an unnecessary word of the specific target in an unnecessary word dictionary stored in the second storage means, in association with the identification information given to the identification information. If a combination of words excluding a specific word from a plurality of words constituting the input character string is included in the combination of words extracted by the search by The specific identification information registered in the name dictionary associated with the excluded word combination is searched for whether or not the specific identification information associated with the specific word is registered in the unnecessary word dictionary, When specific identification information is associated with the specific word and registered in the unnecessary word dictionary, it is determined that the input character string represents an object to which the specific identification information is assigned. It is characterized by doing.

  The information conversion device according to the first aspect of the present invention provides an input character string that is input to a character string that is formed by combining a plurality of words to represent a predetermined object. It converts into the identification information given to the predetermined object estimated that the column represents. As the above character string, for example, a character string representing the name of a customer set in a message sent and received between financial institutions is suitable, but is not limited to this, and a plurality of characters are represented to represent a predetermined target. The character string may be a combination of words. In the invention described in claim 1, each individual object to which identification information is assigned is associated with a combination of identification information given to the individual object and a word constituting a character string representing the individual object. The registered name dictionary is stored in the first storage means. Further, the search means compares each combination of words constituting the input character string with each combination of words registered in the name dictionary, thereby combining the combination of words constituting the input character string. Searching for a combination of words that are completely matched or partially matched in units of words, the conversion means determines an object that is assumed to be represented by the input character string based on the search result by the search means, and is input The character string is converted into identification information given to the determined object.

  Here, in the invention described in claim 1, a combination of words excluding a specific word from a plurality of words constituting the inputted character string in a combination of words extracted by the search by the search means ( A combination of words constituting the input character string and a combination of words partially matching in units of words) and the input character string is excluded from the specific word by the conversion means When it is determined that it represents a specific object corresponding to the combination of the above, the specific word is associated with the identification information given to the specific object, and the unnecessary word dictionary stored in the second storage means Unnecessary word registration means for registering as an unnecessary word for a specific target is provided. Thereby, a character string in which an extra word is added to a combination of words (a combination of words registered in the name dictionary) constituting a regular character string representing a specific target is input, and the character Each time it is determined that the column represents the specific target, the extra word is associated with the identification information given to the specific target and registered as an unnecessary word in the unnecessary word dictionary.

  The conversion means according to the invention described in claim 1 includes a word that excludes a specific word from a plurality of words constituting the input character string in the combination of words extracted by the search by the search means. When a combination is included, specific identification information associated with a combination of words excluding a specific word and registered in the name dictionary is associated with the specific word in the unnecessary word dictionary. Search for whether or not it is registered, and when the specific identification information is associated with the specific word and registered in the unnecessary word dictionary, the input character string is the target to which the specific identification information is given It is judged that it represents. Thus, the word once registered in the unnecessary word dictionary as the unnecessary word of the specific target by the above-described unnecessary word registration means is used for determining whether or not the input character string represents the specific target. When the character string with the above unnecessary word added to the combination of words constituting the regular character string representing the specific object is input again, the input character string represents the specific object It can be automatically determined to be a character string.

  Therefore, according to the first aspect of the present invention, a character string formed by combining a plurality of words to represent a predetermined object is given to the predetermined object estimated to be represented by the character string. It is possible to improve the probability that conversion to identification information can be automatically performed without bothering the operator. Further, according to the first aspect of the present invention, since unnecessary words are automatically registered in the unnecessary word dictionary, it is not necessary for the operator to perform complicated operations such as unnecessary word registration.

In the invention described in claim 1, the conversion means is, for example, as described in claim 2,
The combination of words extracted by the search by the search means includes a combination of words excluding a specific word from a plurality of words constituting the input character string, and the specific word is When the specific identification information registered in the name dictionary associated with the excluded word combination is not registered in the unnecessary word dictionary in association with the specific word, the input character string is By displaying on the display device, the operator determines the target represented by the input character string, and determines the target represented by the input character string based on the determination result input by the operator via the input device. It can be constituted as follows. Also in the invention according to claim 2, when the operator determines that the input character string represents the specific object to which the specific identification information is given, the unnecessary word registration means performs the specific Since a word is registered in the unnecessary word dictionary as an unnecessary word of a specific target, when the same character string is input again, the input character string is a character string representing the specific target Can be automatically determined.

  By the way, among the individual objects to which the identification information is given, a combination of a specific word added to a combination of words constituting the character string representing the first object is a character string representing the second object. There is a case where there is an object having an inclusion relationship that matches a combination of a plurality of words constituting. When a combination of words that completely matches the combination of words constituting the input character string is extracted by the search by the search means, and a specific word is extracted from the plurality of words that constitute the input character string. When a combination of excluded words is extracted, an unnecessary word according to the present invention is used if there is no other target having an inclusion relationship with a specific target corresponding to the extracted word combination. Although the accuracy of determination is slightly lower than in the case, it is also possible to uniformly determine that the input character string represents the specific target without using unnecessary words according to the present invention. However, when there is another target having an inclusion relationship with the specific target, there is a possibility that the target represented by the input character string is erroneously determined unless the unnecessary word according to the present invention is used.

Considering this, in the invention described in claim 1, for example, as described in claim 3, the unnecessary word registering unit includes the character string input in the combination of words extracted by the search by the search unit. A combination of words excluding a specific word from a plurality of words constituting the word is included, and a character string input by the conversion means corresponds to a specific combination of words excluding the specific word When it is determined that the target is represented, only when there is another target having an inclusion relationship with the specific target, the specific word is registered as an unnecessary word of the specific target in the unnecessary word dictionary, The conversion means extracts a combination of words that completely matches the combination of words constituting the input character string and a plurality of words that constitute the input character string by the search by the search means. Special If a combination of words excluding the word is extracted, and there is no other target having an inclusion relationship with the specific target corresponding to the extracted word combination, the input character string is A combination of words that excludes a specific word from a plurality of words that constitute an input character string among combinations of words that are determined to represent a specific object and are extracted by a search by a search means. If it is included, if there is another target having an inclusion relationship with the specific target corresponding to the combination of words excluding the specific word, the unnecessary word dictionary may be searched. .

  In the invention described in claim 3, since processing such as registration / retrieval of unnecessary words is not performed for an object that does not have an inclusion relationship, the load applied to the information conversion apparatus according to the present invention is reduced and the processing speed is increased. In addition, since the number of unnecessary words registered in the unnecessary word dictionary is reduced, the storage capacity of the second storage means necessary for storing the unnecessary word dictionary can be reduced.

  Further, in the invention described in claim 3, it is possible to determine whether or not there is another target having an inclusion relationship with the specific target by searching a name dictionary. As described in the above, whether or not there is another object having an inclusion relationship in the name dictionary stored in the first storage means, with information corresponding to each object to which the identification information is assigned as a unit. Is included, and the unnecessary word registration means and the conversion means, based on the inclusion identification information registered in the name dictionary, are there other objects having an inclusion relationship with the specific object? It is preferable to determine whether or not. In the invention described in claim 4, although it is necessary to register inclusion identification information in the name dictionary, the name dictionary is searched for whether there is another object having an inclusion relationship with a certain object. Since the determination can be made only by referring to the inclusion identification information, the load applied to the information conversion apparatus according to the present invention can be reduced and the processing speed can be increased.

  Further, in the invention described in claim 1, the unnecessary word registering unit instructs the operator to delete a specific unnecessary word registered in the unnecessary word dictionary via the input device as described in claim 5, for example. In such a case, the designated unnecessary word and the unnecessary word dictionary are deleted from the unnecessary word dictionary and the name dictionary is searched using the identification information associated with the designated unnecessary word on the unnecessary word dictionary as a key. The word combination registered in the name dictionary associated with the same identification information as the unnecessary word is extracted, and the word obtained by adding the unnecessary word to the extracted word combination is re-registered in the name dictionary. You may make it comprise. In this case, for example, when a specific unnecessary word is added at a very high frequency to a character string representing a specific target, the specific unnecessary word registered as the unnecessary word of the specific target is extracted from the unnecessary word dictionary. In addition to deleting, it is possible to easily add the specific word to a combination of words constituting the character string representing the specific object registered in the name dictionary.

  Further, in the invention according to any one of claims 1 to 5, for example, as described in claim 6, character strings corresponding to individual words constituting an input character string and given to individual words A third storage means for storing a basic word dictionary registered in advance with a corresponding logical index, and a basic word dictionary with character strings corresponding to individual words constituting the input character string as keys And a word conversion means for converting the input character string into a logical index in units of individual words constituting the character string by performing each of the search, and the name dictionary as a combination of words A combination of logical indexes is registered, a logical index is registered as an unnecessary word in the unnecessary word dictionary, and the search means, conversion means, and unnecessary word registration means are input as an input character string. It is preferred that the string is configured to perform the processing by using a combination of logical indexes obtained by being converted word by word by word conversion means.

  In general, text data representing a character string has a larger amount of data than the amount of information (for example, text data represented using a character code representing one character as data of 2 bytes is the number of characters × 2 bytes of data). When a character string is processed as text data, the load applied to the information conversion apparatus according to the present invention and processing delay are increased, and the storage capacity required for storing the basic word dictionary and the unnecessary word dictionary also increases. . On the other hand, in the invention according to the sixth aspect, the character strings corresponding to the individual words constituting the input character string and the logical index (word code information) assigned to the individual words are associated with each other in advance. Each registered basic word dictionary is stored in the third storage means, and the word conversion means searches the basic word dictionary by using the character strings corresponding to the individual words constituting the inputted character strings as keys. By doing so, the input character string is converted into a logical index in units of individual words constituting the character string, so that the data amount of the input character string (character string to be converted) can be reduced. it can. Also, by registering a combination of logical indexes as a combination of words in the name dictionary and registering a logical index as an unnecessary word in the unnecessary word dictionary, a storage capacity necessary for storing these dictionaries Can also be reduced. Then, each of the search means, the conversion means, and the unnecessary word registration means uses a combination of logical indexes obtained by converting the input character string in units of words by the word conversion means as the input character string. By performing the processing, it is possible to reduce the load applied to the information conversion apparatus according to the present invention and to speed up the processing.

  The information conversion program according to the invention described in claim 7 is an information conversion program, wherein each time a character string composed of a plurality of words combined to represent a predetermined object is input, the input character string is An information conversion program for causing a computer to function as an information conversion device for converting into identification information assigned to the predetermined object presumed to be represented by the input character string, wherein the computer is provided with identification information. A first storage means for storing each registered name dictionary in association with identification information given to each object and a combination of words constituting a character string representing each object And a second storage means for storing an unnecessary word dictionary, and the computer includes a combination of words constituting the inputted character string and a combination of words registered in the name dictionary, respectively. By comparing, a search means for searching for a combination of words constituting the input character string and a word combination that completely or partially matches in units of words, the input based on a search result by the search means A target that is presumed to be represented by the character string that has been represented, a conversion unit that converts the input character string into identification information assigned to the determined target, and a search performed by the search unit The combination of words includes a combination of words excluding a specific word from a plurality of words constituting the input character string, and the input character string is converted by the conversion means. Is determined to represent a specific object corresponding to a combination of words excluding the specific word, the specific word is associated with identification information given to the specific object, (2) It functions as an unnecessary word registration means for registering as an unnecessary word of the specific target in the unnecessary word dictionary stored in the storage means, and the conversion means is a combination of words extracted by the search by the search means. If a combination of words excluding a specific word from a plurality of words constituting the input character string is included, it is associated with a combination of words excluding the specific word It is searched whether the specific identification information registered in the name dictionary is associated with the specific word and registered in the unnecessary word dictionary, and the specific identification information corresponds to the specific word. When it is attached and registered in the unnecessary word dictionary, it is determined that the input character string represents an object to which the specific identification information is given.

  An information conversion program according to claim 7 is a computer comprising the first storage means for storing a name dictionary and the second storage means for storing an unnecessary word dictionary. Since the above-described computer executes the information conversion program according to the seventh aspect of the invention, the computer functions as the information conversion apparatus according to the first aspect. As in the first aspect of the present invention, a character string composed of a plurality of words combined to represent a predetermined object is given to the predetermined object estimated to be represented by the character string. It is possible to improve the probability that conversion to identification information can be automatically performed without bothering the operator.

  As described above, according to the present invention, for each object to which identification information is assigned, a combination of identification information given to each object and a word constituting a character string representing each object is associated. A combination of words excluding a specific word from a plurality of words constituting the input character string is registered in the name dictionary in each registered name dictionary, and the input character string is the specific word. If it is determined that it represents a specific target corresponding to a combination of words excluding the word, the specific word is registered in the unnecessary word dictionary in association with the identification information given to the specific target, and is input. When a combination of words excluding a specific word from a plurality of words constituting the character string is registered in the name dictionary, the name dictionary is associated with the combination of words excluding the specific word. Registered specific If the identification information is associated with the specific word and registered in the unnecessary word dictionary, and if the specific identification information is associated with the specific word and registered in the unnecessary word dictionary, Since it is determined that the input character string represents a target to which specific identification information is given, a character string formed by combining a plurality of words to represent a predetermined target is It has an excellent effect that it is possible to improve the probability that conversion to identification information given to a predetermined target presumed to be represented by a character string can be performed automatically without bothering the operator. .

  Hereinafter, an example of an embodiment of the present invention will be described in detail with reference to the drawings. FIG. 1 shows a computer system 10 according to the present embodiment. The computer system 10 includes a computer 12 installed in an information center of a specific financial institution. The computer 12 is composed of a mainframe computer and includes a CPU 12A, a ROM 12B, a RAM 12C, and an input / output port 12D, which are connected to each other via a bus 12E such as an address bus, a data bus, and a control bus. A communication control device 14, a display 16, a mouse 18, a keyboard 20, and an HDD (hard disk drive) 22 are connected to the input / output port 12D as various input / output devices.

  The HDD 22 stores a basic word dictionary, a name dictionary, and an unnecessary word dictionary (details will be described later), and the HDD 22 corresponds to the first storage means and the second storage means according to the present invention. This also corresponds to the third storage means described. The computer 12 is preinstalled in the HDD 22 with a customer code conversion program for performing customer code conversion processing, which will be described later, and an unnecessary word deletion program for performing unnecessary word deletion processing. The customer code conversion program and the unnecessary word deletion program correspond to the information conversion program according to claim 7, and the computer 12 executes the above programs so that the computer 12 can execute the information conversion apparatus according to the present invention. Function as. The computer functioning as the information conversion apparatus according to the present invention is not limited to the mainframe computer, and any computer such as a personal computer or a microprocessor can be applied.

  The communication control device 14 of the computer 12 is connected to a computer network 26 built in a specific financial institution. The computer network 26 is configured by connecting a large number of computers to each other via a communication line. In addition, among a large number of computers constituting the computer network 26, there are included computers for performing financial transactions instructed by the computer 12 (for example, deposit processing to the instructed account). Further, the communication control device 14 of the computer 12 is connected to a computer 30 of another overseas financial institution via a network 28 (international network for message exchange between banks). Hereinafter, the specific financial institution in which the computer 12 is installed is referred to as a first financial institution, and the financial institution in which the computer 30 is installed is referred to as a second financial institution.

  Next, the operation of this embodiment will be described. When requesting a foreign remittance to a financial institution, the remittance requester specifies information such as the name of the financial institution, branch name, account holder name, account number, and amount of remittance of the remittance destination account. In the second financial institution, when a request for remittance to the specific account established in the first financial institution is requested by the remittance requester, a message for requesting the first financial institution to deposit money is created. However, each piece of information designated by the remittance requester is set in this electronic message, and information such as the name of the holder of the remittance destination account is set in the electronic message as a character string (text data). When the creation of the message is completed, the second financial institution transmits the created message to the first financial institution computer 12 via the network 28 by the computer 30. When the computer 12 of the first financial institution receives a message from another financial institution via the network 28, the name of the name of the remittance destination account (name of the customer of the first financial institution) set in the received message. Processing for extracting text data of a character string to be represented and converting the text data of the extracted character string into a customer code (identification information) assigned to each customer by the first financial institution to identify each customer (Customer code conversion processing described later) is performed. The basic word dictionary, the name dictionary, and the unnecessary word dictionary stored in the HDD 22 of the computer 12 are provided to realize the customer code conversion process.

  That is, the character string representing the customer name is formed by combining a plurality of words. However, in the first financial institution, a multi-digit numerical value is added to each word constituting the character string representing each customer name. In the customer code conversion process, a character string to be converted representing a customer name extracted from the received message is assigned to each word constituting the character string. Processing is performed after conversion to a combination (logical index set) of corresponding logical indexes. For this reason, as shown in FIG. 2A as an example, the basic word dictionary is associated with text data representing individual words and numerical data corresponding to the logical index assigned to each word. Each information is registered (in FIG. 2A, information such as part of speech, attribute (name) and attribute (code) is also added to each word). Further, as shown in FIG. 2B as an example, the name dictionary described above associates the names of individual customers, the logical index set corresponding to the names, and customer codes assigned to the individual customers. Each registered.

  By the way, among the names of the individual customers, a combination of a specific word added to a combination of words constituting the character string representing the name of the first customer is a character string representing the name of the second customer. There is a name having a relationship (this relationship is called an inclusion relationship) that matches the combination of the words that constitute. As an example, as shown in FIG. 2B, the character string “NAKAMORI CO, .LTD” representing the name of customer B is composed of two words “NAKAMORI” and “CO, .LTD” (see FIG. 2). If the logical index shown in FIG. 2 (B) is used, the logical index set of the above character string is “105,107”), but the combination of words obtained by adding the specific word “ELECTRIC” to this combination of words is the customer C Matches the combination of words constituting “NAKAMORI ELECTRIC CO, .LTD” (the logical index set of this character string is “105,106,107”). When the character string to be converted is a character string corresponding to a customer name having an inclusion relationship, it uniquely identifies which of the plurality of customer names having an inclusion relationship the character string to be converted represents There is a problem that it cannot be judged. For example, when the character string to be converted is “NAKAMORI CO, .LTD”, the character string to be converted is likely to represent the name of the customer B described above, but the character string to be converted is the customer C's name. The specific word “ELECTRIC” in the character string “NAKAMORI ELECTRIC CO, .LTD” (hereinafter referred to as non-inclusive word) is missing for some reason, and the character string to be converted is the name of customer C We cannot deny the possibility that it represents.

  Therefore, in the customer code conversion process, it is necessary to perform different processing depending on whether the character string to be converted represents a name having an inclusion relationship or a name having an inclusion relationship. For this reason, out of the customer information registered in the name dictionary, the customer information whose name has an inclusion relationship has an inclusion relationship as shown in FIG. 2B as an example. An inclusion code (inclusion identification information) indicating that the Specifically, the same inclusion code is added to the information of a plurality of customers whose names have an inclusion relationship (the first customer and the second customer described above), and the same inclusion code is added. Among the customers, the logical index of the non-inclusive word is added to the inclusion code of the customer (second customer) in which the non-inclusive word is added to the name (in FIG. 2 (B), the name is “NAKAMORI ELECTRIC In this example, the logical index “106” of the non-inclusive word “ELECTRIC” is added to the inclusion code of the customer C, “CO, .LTD”).

  Although the details of the unnecessary word dictionary will be described later, the conversion target character string representing the name of the specific customer having the inclusion relationship is replaced with a plurality of words represented by the logical index set of the specific customer registered in the name dictionary. If the character string has an extra word added, the extra word is associated with the customer code of the specific customer and registered in the unnecessary word dictionary as an unnecessary word of the specific customer.

  Subsequently, after extracting text data of a character string representing a customer name from a message received from another financial institution, the customer code conversion process performed by the computer 12 by the CPU 12A of the computer 12 executing the customer code conversion program. This will be described with reference to FIG. This customer code conversion process is executed every time a telegram including text data of a character string representing a customer name is received from another financial institution.

  In step 50, the conversion target character string extracted from the received electronic message is divided into a plurality of words with a space existing in the conversion target character string as a delimiter. In step 52, text data of an unprocessed word is extracted from the plurality of words obtained by dividing the character string in step 50. In the next step 54, a basic word dictionary is created using the text data of the extracted word as a key. Search for. In this search, the text data of the retrieved word is stored in a memory (such as the RAM 12C), the basic word dictionary is read from the HDD 22 and expanded in the memory, and then the basic word in which the text data of the word to be searched is expanded in the memory. This may be done by sequentially comparing the text data of individual words registered in the dictionary, or the text data of a single word is read from the HDD 22 and stored in the memory, and the text data stored in the memory is stored. It is also possible to perform the comparison with the text data of the search target word by repeating until text data matching the text data of the search target word appears.

  In step 56, it is determined whether or not the search target word is extracted from the basic word dictionary by the search in step 54, that is, whether or not the search target word is registered in the basic word dictionary. If the determination is affirmative, the process proceeds to step 64, where the logical index (numerical data) associated with the extracted word to be searched and registered in the basic word dictionary is extracted, and the words constituting the conversion target character string The process proceeds to step 66 after being stored in the memory as a logical index. On the other hand, if the determination in step 56 is negative, the process proceeds to step 58 where the logical index assigned to the search target word is determined so as not to overlap with the logical index already registered in the basic word dictionary. In step 60, the text data of the search target word is registered in the basic word dictionary in association with the logical index (numerical data) determined in step 58. Further, in step 62, the logical index determined in step 58 is stored in the memory as a logical index of words constituting the conversion target character string, and then the process proceeds to step 66.

  In step 66, it is determined whether all words have been extracted from the conversion target character string. If the determination is negative, the process returns to step 52, and steps 52 to 66 are repeated until the determination of step 66 is affirmed. As a result, each word constituting the conversion target character string is converted into a logical index, and the logical index set of the conversion target character string is stored in the memory. Steps 52 to 66 correspond to the word conversion means described in claim 6.

  If the determination in step 66 is affirmative, the process proceeds to step 68, where information on a single customer is extracted from the name dictionary, and the logical index set included in the extracted information is compared with the logical index set of the conversion target character string. The comparison of the logical index sets may be performed after the entire name dictionary is read from the HDD 22 and expanded in the memory, or the single customer information is read from the HDD 22 and stored in the memory repeatedly. It is also possible. In the next step 70, the logical index set of the conversion target character string includes a logical index set extracted from the name dictionary (each logical index constituting the logical index set extracted from the name dictionary is converted to the logical index set of the conversion target character string). Whether all exist in the index set).

  If the determination is denied, the process proceeds to step 74 without performing any processing. If the determination is affirmed, the process proceeds to step 72, and the customer code is obtained from the single customer information extracted from the name dictionary in step 68. And the number of logical indexes (number of mismatched words) not included in the logical index set extracted from the name dictionary among the logical indexes constituting the logical index set of the conversion target character string is counted and extracted. After the customer code and the counted number of mismatched words are stored in the memory in association with the logical index set extracted from the name dictionary, the process proceeds to step 74. In step 72, if the single customer information extracted from the name dictionary includes an inclusion code, the inclusion code is also extracted and stored in the memory.

  In step 74, it is determined whether all the logical indexes registered in the name dictionary have been extracted (compared with the logical index set of the character string to be converted). If the determination is negative, the process returns to step 68, and steps 68 to 74 are repeated until the determination of step 74 is affirmed. As a result of the search processing of step 68 to step 74, a single logical index set is normally extracted as a logical index set that matches the determination condition of step 70, and the conversion target character string has an inclusion relationship and is an uninclusive word. A character string corresponding to a customer name including the character string (for example, “NAKAMORI ELECTRIC CO, .LTD” in the above example) or a character string in which a word different from the non-inclusion word is added to the character string (for example, “NAKAMORI ELECTRIC CO, .LTD SHINZYUKU "etc.), a plurality of logical index sets to which the same inclusion code is added are extracted. Steps 68 to 74 described above correspond to the search means according to the present invention.

  If the determination in step 74 is affirmed, the process proceeds to step 76, and a customer code determination process is performed. This customer code determination process will be described with reference to FIG. In step 80, it is determined whether or not a logical index set that matches the determination condition in step 70 has been extracted by the search processing in steps 68 to 74 described above. If this determination is negative, it can be determined that there is a serious error in the conversion target character string extracted from the received message, so the process moves to step 82 and the operator is called by displaying a predetermined message on the display 16 or the like. The process is terminated, and the decision of the customer name and customer code represented by the conversion target character string is left to the operator.

  On the other hand, if the determination in step 80 is affirmed, the process proceeds to step 84, and among the logical index sets stored in the memory by the search in the previous step 68 to step 74, the logical index set with the smallest number of unmatched words (hereinafter referred to as the logical index set) This logical index set is referred to as “first logical index set” for convenience). When only a single logical index set is extracted (stored in the memory) by the search in steps 68 to 74, this logical index set is treated as the first logical index set in the following processing. In step 86, based on whether or not an inclusion code corresponding to the first logical index set is stored in the memory, it is determined whether or not the customer name corresponding to the first logical index set has an inclusion relationship. If this determination is negative, the process proceeds to step 90, and the customer code corresponding to the first logical index set is output as the customer code corresponding to the conversion target character string. In the next step 92, it is determined whether or not the name of the customer to whom the output customer code is assigned has an inclusion relationship. In this case, the determination is denied and the processing is terminated.

  For example, in the example shown in FIG. 2, the conversion target character string is “AKASAKA BANK CO., LTD” (logical index set is “100, 101, 107”) or “AKASAKA BANK CO., LTD MARUNOUCHI” (logical index set is “100, 101, 107, 110”). If there is, the logic corresponding to the character string “AKASAKA BANK CO., LTD” representing the name of the customer A is obtained as a logical index set that matches the determination condition of step 70 by the processing of the previous steps 68 to 74. The index set “100, 101, 107” is extracted from the name dictionary. The inclusion code corresponding to the extracted logical index set (first logical index set) is not registered in the name dictionary (see FIG. 2B), and the name of customer A has no inclusion relationship. Therefore, it can be determined that the conversion target character string represents the name of the customer A regardless of whether the conversion target character string is “AKASAKA BANK CO., LTD” or “AKASAKA BANK CO., LTD MARUNOUCHI”. In such a case, the determination in step 86 is affirmed as described above, and in step 90, the customer code “1230000” corresponding to the first logical index set is used as the customer code corresponding to the character string to be converted. Will be output.

  On the other hand, if the determination in step 86 is affirmative, the process proceeds to step 88, where the logical index of the non-included word included in the information of the first logical index set stored in the memory is referred to, and the By determining whether or not the logical index is included in the logical index set of the conversion target character string, it is determined whether or not the non-inclusive word is included in the conversion target character string. If the determination is affirmative, the process proceeds to step 89, and the customer code corresponding to the logical index set including the non-inclusive word among the logical index sets extracted by the search processing of step 68 to step 74 is converted. The customer code corresponding to the character string is output and the process proceeds to step 92.

  For example, in the example of FIG. 2, the character string to be converted is “NAKAMORI ELECTRIC CO, .LTD” (logical index set is “105,106,107”) or “NAKAMORI ELECTRIC CO, .LTD SHINZYUKU” (logical index set is “105,106,107,111”). In the search processing of step 68 to step 74, as a logical index set that matches the determination condition of step 70, a logical index set corresponding to a plurality of customer names having an inclusion relationship, that is, a character string representing the name of customer B A logical index set “105,107” corresponding to “NAKAMORI CO, .LTD” and a logical index set “105,106,107” corresponding to the character string “NAKAMORI ELECTRIC CO, .LTD” representing the name of customer C are extracted from the name dictionary, respectively. However, since the conversion target character string includes non-inclusive words in the above inclusion relationship, the conversion target character string includes It can be determined that represents the name of Murrell customer C. In the customer code conversion process according to the present embodiment, in the above case, the determination in step 88 is affirmed and the process proceeds to step 89, so that an uninclusive word is included in the name as the customer code corresponding to the character string to be converted. The customer code assigned to the included customer (in the above example, the customer code “3450000” assigned to the customer C) is output.

  In the next step 92, it is determined whether or not the customer name corresponding to the output customer code has an inclusion relationship. In this case, the determination is affirmed and the process proceeds to step 94 to convert the logical index of the character string to be converted. It is determined whether or not the set completely matches the logical index set of the customer name corresponding to the output customer code (the number of mismatch words is 0). In the above example, if the conversion target character string is “NAKAMORI ELECTRIC CO, .LTD”, the logical index set of the conversion target character string completely matches the logical index set of the customer name corresponding to the output customer code. The determination at step 94 is affirmed and the process is terminated.

  In addition, when the conversion target character string is “NAKAMORI ELECTRIC CO, .LTD SHINZYUKU”, the conversion target character string is the character string “NAKAMORI ELECTRIC CO, .LTD” that represents the customer name corresponding to the output customer code. An extra word “SHINZYUKU” is added, and the logical index set of the character string to be converted does not completely match the logical index set of the customer name corresponding to the output customer code. Then, the process proceeds to step 96. Here, the extra word added to the conversion target character string is a word that is originally unnecessary for the determination of the customer code corresponding to the conversion target character string, but the character representing the same customer name as the conversion target character string. When a column is input in the future, the same word is likely to be added to the character string, while the customer name represented by the character string to be converted has an inclusion relationship. There is a possibility that the above word can be used to determine the customer name represented by the target character string. For this reason, in step 94, the logic of the unmatched word (word “SHINZYUKU” in the above example) that is included in the character string to be converted and not included in the character string representing the customer name corresponding to the output customer code. After the index is registered in the unnecessary word dictionary in association with the output customer code, the process is terminated (see also FIG. 2C). Steps 92 to 96 described above correspond to the unnecessary word registration unit according to the present invention, and each step other than the above in the customer code determination process corresponds to the conversion unit according to the present invention.

  In addition, the customer name corresponding to the first logical index set has an inclusion relationship, and the character string to be converted does not include an extra-inclusion word in the inclusion relationship (for example, “NAKAMORI CO, .LTD”)) or When the character string is a character string (for example, “NAKAMORI AND CO, .LTD” or “NAKAMORI CO, .LTD SHINZYUKU”) in which a word other than the non-inclusion word is added to the character string, , As a logical index set that matches the determination condition of step 70, a logical index set corresponding to a customer name that does not include a non-included word among a plurality of customer names having an inclusion relationship, that is, a character string “NAKAMORI Only the logical index set “105,107” corresponding to “CO, .LTD” is extracted, but although the conversion target character string is likely to be a character string representing the name of customer B, customer B ’s There is a possibility that the specific word “ELECTRIC” in the name “NAKAMORI ELECTRIC CO, .LTD” of the customer C inclusive relationship with the name is a missing character string for some reason (a character string representing the name of the customer C). .

  In the above case, the determination in step 88 is affirmed and the process proceeds to step 98, and whether or not the logical index set of the character string to be converted completely matches the first logical index set (the number of mismatched words is 0). To determine. When the determination is affirmative (for example, when the conversion target character string is “NAKAMORI CO, .LTD”), the process proceeds to step 108 without performing any processing, but when the determination is negative (for example, the conversion target character string is In the case of “NAKAMORI AND CO, .LTD” or “NAKAMORI CO, .LTD SHINZYUKU”, the process proceeds to step 100, and the conversion is performed by comparing the logical index set of the conversion target character string with the first logical index set. A logical index of a word (non-matching word) that exists in the target character string but does not exist in the character string corresponding to the first logical index set is extracted. For example, when the conversion target character string is “NAKAMORI AND CO, .LTD” and the first logical index set is a logical index set corresponding to the name of the customer B, the mismatch word is “AND”, so “AND”. The logical index “108” is extracted.

  In the next step 102, an unnecessary word dictionary is searched using the customer code corresponding to the first logical index set as a key. The search for the unnecessary word dictionary may be performed after the entire unnecessary word dictionary is read from the HDD 22 and expanded in the memory, or the single customer information is read from the HDD 22 and stored in the memory repeatedly. Is also possible. In the next step 104, it is determined whether or not the corresponding information is extracted by the search in step 102. If the determination is affirmative, the process proceeds to step 106, and it is determined whether or not the information extracted by the search in step 102 includes the logical index of the mismatched word extracted in the previous step 100.

  If the determination in step 106 is affirmative, the mismatch word from which the logical index has been extracted in the previous step 100 is registered in the unnecessary word dictionary as an unnecessary word for the customer name corresponding to the first logical index set. Therefore, when the customer name corresponding to the first logical index set is represented, the character string to which the above mismatch word is added exists in the character string determined in the past (for example, as described above) In the example, if the name of the customer B is represented, the character string to which the above “AND” is added exists in the character string determined in the past), and the conversion target character string is the first character string. It can be determined that it represents the customer name corresponding to the logical index set. For this reason, when the determination in step 106 is affirmed, the process proceeds to step 107, the customer code corresponding to the first logical index set is output as the customer code corresponding to the character string to be converted, and the process is terminated.

  On the other hand, if the determination in step 104 or step 106 is affirmative, the logical character in the previous step 100 is included in the character string determined in the past as representing the customer name corresponding to the first logical index set. It is determined that there is no character string to which the mismatch word from which the index has been extracted is added, and the conversion target character string represents the customer name corresponding to the first logical index set based on the mismatch word. It is difficult. Therefore, if the determination in step 104 or step 106 is affirmed, the process proceeds to step 108, the name dictionary is searched using the inclusion code added to the first logical index set as a key, and the first logical index Information of the second logical index set representing the customer name having an inclusion relationship with the customer name corresponding to the set is extracted from the name dictionary.

  In the next step 110, by comparing the logical index set of the conversion target character string with the second logical index set, the character string corresponding to the second logical index set that exists in the conversion target character string is obtained. Extracts the logical index of non-matching mismatched words. For example, when the conversion target character string is “NAKAMORI CO, .LTD SHINZYUKU” and the second logical index set is a logical index set corresponding to the name of the customer C, the logical index “118” of the mismatch word “SHINZYUKU” Extracted. In the next step 112, an unnecessary word dictionary is searched using the customer code corresponding to the second logical index set as a key. In step 114, it is determined whether or not the corresponding information is extracted by the search in step 112. If the determination is affirmative, the process proceeds to step 116, and it is determined whether or not the information extracted by the search in step 112 includes the logical index of the mismatched word extracted in the previous step 110.

  If the determination in step 116 is affirmative, the mismatch word from which the logical index was extracted in the previous step 110 is registered in the unnecessary word dictionary as an unnecessary word for the customer name corresponding to the second logical index set. Therefore, when the customer name corresponding to the second logical index set is represented, there is a character string to which the above mismatch word is added in the character string determined in the past. It can be determined that the conversion target character string is highly likely to represent the customer name corresponding to the second logical index set. For example, the conversion target character string is “NAKAMORI CO, .LTD SHINZYUKU”, and the word “SHINZYUKU” is extracted as a mismatch word of the first logical index set, but corresponds to the first logical index set. While it was not registered in the unnecessary word dictionary as an unnecessary word for customer B, it is also extracted as a mismatched word in the second logical index set and is unnecessary as an unnecessary word for customer C corresponding to the second logical index set If it is registered in the word dictionary, the character string with the above “SHINZYUKU” added to the character string determined in the past as representing the name of the customer C exists. The character string to be converted can be determined to be highly likely to be a character string representing the name of the customer C although the word “ELECTRIC” is missing. For this reason, when the determination in step 116 is affirmed, the process proceeds to step 118, where the customer code corresponding to the second logical index set is output as the customer code corresponding to the character string to be converted, and the process is terminated.

  On the other hand, if the determination in step 114 or step 116 is affirmative, the logical character in the previous step 110 is included in the character string determined in the past as representing the customer name corresponding to the second logical index set. Since there is no character string to which the mismatched word from which the index is extracted is added, either the customer name corresponding to the first logical index set or the customer name corresponding to the second logical index set is the character string to be converted. It is difficult to determine whether or not Therefore, if the determination in step 114 or step 116 is affirmed, the process proceeds to step 120, where the conversion target character string is displayed on the display 16, and the character string corresponding to the first and second logical index sets, the customer Information such as a code is displayed on the display 16 and a predetermined message is displayed on the display 16 to request the operator to determine the customer name represented by the character string to be converted.

  In the next step 122, it is determined whether or not a determination result by the operator has been input, and step 122 is repeated until the determination is affirmed. When the determination of the customer name is requested, the operator determines the customer name represented by the character string to be converted by performing an operation such as making an inquiry to the second financial institution that sent the message. Then, information indicating the determination result is input via the keyboard 20. As a result, the determination in step 122 is affirmed and the process proceeds to step 124. After the customer code corresponding to the input determination result is output as the customer code corresponding to the character string to be converted, the process proceeds to step 92. Steps 120 to 124 correspond to the conversion means described in claim 2.

  Therefore, if the character string to be converted is a character string in which an extra word is added to the customer name determined by the operator, the determination in steps 92 and 94 is affirmed and the process proceeds to step 96, where the conversion target character string is converted. Since an unnecessary word in the character string is registered in the unnecessary word dictionary as an unnecessary word for the determined customer, the same word (unnecessary word) is used as a character string representing the same customer from the next time onward. When a character string to which is added appears, the determination of step 106 or step 116 is affirmed based on this unnecessary word, so that the customer name represented by the conversion target character string can be obtained without bothering the operator again. It can be determined automatically.

  Next, when the operator operates the keyboard 20 or the mouse 18 to instruct deletion of unnecessary words registered in the unnecessary word dictionary, the unnecessary word deletion program is executed by the CPU 12A, whereby the computer 12 is executed. The unnecessary word deletion process performed by the above will be described with reference to FIG. This unnecessary word deletion process corresponds to the unnecessary word registering means described in claim 5.

  In step 130, a customer code input screen provided with an input field for inputting a customer code is displayed on the display 16. In step 132, it is determined whether or not a customer code has been input, and step 132 is repeated until the customer code is input by the operator. When the operator operates the keyboard 20 or the like to input a customer code in the input field in the customer code input screen, the determination at step 132 is affirmed and the routine proceeds to step 134, where the name dictionary and the input customer code are used as keys. Search the unnecessary word dictionary, the logical index set registered in the name dictionary in association with the input customer code, and the unnecessary word registered in the unnecessary word dictionary in association with the input customer code Get each logical index.

  In step 136, the basic word dictionary is searched using the individual logical indexes constituting the acquired logical index set and the acquired logical index of unnecessary words as keys, thereby acquiring text data of words corresponding to each logical index. To do. Then, the words are arranged as a character string based on the acquired text data and displayed on the display 16. When displaying this character string, unnecessary words in the character string are displayed so as to be distinguishable from other words. This can be realized, for example, by making at least one of the display color, display brightness, and font of the unnecessary word different from other words. In the next step 138, it is determined whether or not deletion of a specific unnecessary word is instructed. When determination is denied, it transfers to step 140, and it is determined whether completion | finish of the unnecessary word deletion process was instruct | indicated. If this determination is also negative, the process returns to step 138, and steps 138 and 140 are repeated until either determination is positive.

  When the operator operates the mouse 18 or the like to designate an unnecessary word to be deleted, the determination at step 138 is affirmed and the routine proceeds to step 142, where it is associated with the customer code previously input by the operator and registered in the name dictionary. The logical index of the unnecessary word to be deleted that is instructed to be added is added to the set of logical indexes. In the next step 144, the inclusion code registered in the name dictionary in association with the input customer code is extracted, and the name dictionary is searched using the extracted inclusion code as a key. By extracting from the name dictionary a logical index set corresponding to another customer name having an inclusion relationship with the customer name corresponding to the logical index set, and comparing the extracted logical index set with the previously changed logical index set, It is determined whether or not the inclusion relationship has been canceled. If the determination is negative, the process proceeds to step 148 without performing any processing. If the determination is affirmative, the process proceeds to step 146, and the inclusion code corresponding to the resolved inclusion relation is deleted from the name dictionary.

  In step 148, the logical index of the designated unnecessary word to be deleted is deleted from the unnecessary word dictionary. When deleting unnecessary words from the unnecessary word dictionary, when the number of logical indexes of unnecessary words associated with the same customer code becomes 0, the customer code itself is also deleted from the unnecessary word dictionary. . When the process of step 144 is completed, the process returns to step 138 and returns to a state in which steps 138 and 140 are repeated. When the operator instructs the end of the unnecessary word deletion process, the determination in step 140 is affirmed and the unnecessary word deletion process ends.

  Thus, for example, when a specific unnecessary word is added to a conversion target character string representing a specific customer name at a very high frequency, the specific unnecessary word is used as a logical index set for the specific customer name. The inclusion relationship may be eliminated by adding. In such a case, if it is instructed to delete a specific unnecessary word from an unnecessary word for a specific customer, the specific unnecessary word is added to the logical index set corresponding to the specific customer by the above unnecessary word deletion processing. In addition, since the inclusion relationship is eliminated by excluding specific unnecessary words from the unnecessary words for a specific customer, it is necessary for the operator to manually update the name dictionary and unnecessary word dictionary to eliminate the inclusion relationship. The burden on the operator can be reduced.

  In the above description, an example in which only the logical index of unnecessary words is registered in the unnecessary word dictionary in association with the customer code is described as an example, but the present invention is not limited to this. For example, when registering unnecessary words, The position of the unnecessary word in the character string including the unnecessary word is also registered as information, and the conversion is performed in consideration of whether the position of the unnecessary word in the conversion target character string matches the position registered in the unnecessary word dictionary. The customer name represented by the target character string may be determined, and the appearance frequency or number of appearances of each unnecessary word is registered in the unnecessary word dictionary, and the appearance frequency or number of appearances is updated as appropriate, and the appearance frequency or appearance number is updated. Only unnecessary words whose number of times is greater than or equal to a predetermined value may be used to determine the customer name represented by the character string to be converted.

  In addition, in the above, when a word extracted from the conversion target character string is not registered in the basic word dictionary, a logical index is assigned to the word and newly registered in the basic word dictionary, thereby performing conversion processing. Although an example of converting all the words constituting a character string into a logical index has been described, the present invention is not limited to this. For words that are not registered in the basic word dictionary among the words constituting the character string to be converted In this case, the subsequent processing may be performed as it is without converting to the logical index. In this case, there is a possibility that a word registered as a logical index and a word registered as text data may be mixed in the unnecessary word dictionary and the auxiliary dictionary, but the present invention includes such an aspect within the scope of rights.

  In the above, the conversion target character string does not completely match the character string of the customer name represented by the conversion target character string (the number of mismatched words ≧ 1) and is included in the customer name represented by the conversion target character string. Although an example in which a mismatched word is registered as an unnecessary word only when there is a relationship has been described, the present invention is not limited to this, and even if there is no inclusion relationship in the customer name represented by the conversion target character string, the conversion target character If the column does not completely match the character string of the customer name, the mismatch word may be registered as an unnecessary word in the unnecessary word dictionary.

  Furthermore, in the above description, a case has been described where unnecessary word deletion processing is executed in response to an instruction from an operator to delete unnecessary words. However, the present invention is not limited to this and is registered in the name dictionary by the operator. Every time a new word logical index is instructed to the logical index set corresponding to the name of a specific customer, the logical index of the word instructed to be added is registered in the unnecessary word dictionary as an unnecessary word of the specific customer. It is possible to search for whether or not it has been performed, and to perform a process of deleting from the unnecessary word dictionary when the corresponding word exists.

  In the above description, the character string representing the customer name is described as an example of the character string according to the present invention. However, the present invention is not limited to this, and represents an arbitrary object formed by combining a plurality of words. Applicable to strings.

It is a block diagram which shows schematic structure of the computer system which concerns on this embodiment. (A) is an example of a basic word dictionary, (B) is an example of a name dictionary, and (C) is an image diagram showing an example of an unnecessary word dictionary. It is a flowchart which shows the content of the customer code conversion process. It is a flowchart which shows the content of the customer code determination process. It is a flowchart which shows the content of an unnecessary word deletion process.

Explanation of symbols

10 Computer System 12 Computer 16 Display 18 Mouse 20 Keyboard 22 HDD
28 network 30 computer

Claims (7)

Each time a character string composed of a plurality of words combined to represent a predetermined object is input, the input character string is presumed to be represented by the input character string. An information conversion device for converting into identification information given to a target,
For each object to which identification information is assigned, a name dictionary registered by associating a combination of identification information given to each object and a word constituting a character string representing each object is stored. First storage means;
By comparing each combination of words constituting the inputted character string with each combination of words registered in the name dictionary, the combination of the words constituting the inputted character string and the complete word unit A search means for searching for a combination of words that match or partially match;
Conversion that determines a target estimated to represent the input character string based on a search result by the search means, and converts the input character string into identification information given to the determined target Means,
The combination of words extracted by the search by the search means includes a combination of words excluding specific words from a plurality of words constituting the input character string, and the conversion means When the input character string is determined to represent a specific target corresponding to a combination of words excluding the specific word, the specific word is given to the specific target. Unnecessary word registration means for registering as an unnecessary word of the specific target in the unnecessary word dictionary stored in the second storage means,
With
The conversion means includes a combination of words excluding a specific word from a plurality of words constituting the inputted character string in the combination of words extracted by the search by the search means. Specific identification information registered in the name dictionary in association with a combination of words excluding the specific word is registered in the unnecessary word dictionary in association with the specific word. If the specific identification information is associated with the specific word and registered in the unnecessary word dictionary, the input character string is given the specific identification information. An information conversion device characterized in that it represents a target.   The conversion means includes a combination of words obtained by excluding specific words from a plurality of words constituting the input character string in a combination of words extracted by the search by the search means. And the specific identification information registered in the name dictionary in association with a combination of words excluding the specific word is registered in the unnecessary word dictionary in association with the specific word. If not, the input character string is displayed on the display device, so that the operator can determine the target represented by the input character string, and based on the determination result input by the operator via the input device. The information conversion apparatus according to claim 1, wherein an object represented by the input character string is determined. Among the individual objects to which the identification information is given, a combination of a specific word added to a combination of words constituting the character string representing the first object is a character string representing the second object. There is an object that has an inclusion relationship that matches a combination of multiple words
The unnecessary word registration means includes
The combination of words extracted by the search by the search means includes a combination of words excluding specific words from a plurality of words constituting the input character string, and the conversion means When the input character string is determined to represent a specific target corresponding to a combination of words excluding the specific word, the other character having the inclusion relation with the specific target is determined. Only when the target exists, the specific word is registered in the unnecessary word dictionary as the unnecessary word of the specific target,
The conversion means constitutes the input character string when a combination of words that completely matches the word combination constituting the input character string is extracted by the search by the search means; When a combination of words excluding a specific word from a plurality of words is extracted, there is no other target having the inclusion relationship in the specific target corresponding to the extracted word combination. , Determining that the input character string represents the specific object, and from among a plurality of words constituting the input character string in a combination of words extracted by the search by the search means If a combination of words excluding a specific word is included, and there is another target having the inclusion relation in the specific target corresponding to the combination of the word excluding the specific word , Serial information converter according to claim 1, characterized in that to search for unnecessary word dictionary. The name dictionary stored in the first storage means indicates whether or not there is another target having the inclusion relationship in units of information corresponding to each target to which the identification information is given. Inclusion identification information is also registered,
The unnecessary word registration unit and the conversion unit determine whether another target having the inclusion relationship exists in the specific target based on the inclusion identification information registered in the name dictionary. The information conversion apparatus according to claim 3.   The unnecessary word registering unit deletes the specified unnecessary word from the unnecessary word dictionary when an operator instructs to delete a specific unnecessary word registered in the unnecessary word dictionary via the input device. And searching the name dictionary using the identification information associated with the instructed unnecessary word on the unnecessary word dictionary as a key so that the name is associated with the same identification information as the unnecessary word. The information conversion apparatus according to claim 1, wherein a combination of words registered in a dictionary is extracted, and a word obtained by adding the unnecessary word to the extracted combination of words is re-registered in the name dictionary. Third storage means for storing a basic word dictionary registered in advance by associating a character string corresponding to each word constituting the input character string and a logical index assigned to each word;
By searching the basic word dictionary using character strings corresponding to individual words constituting the inputted character string as keys, the inputted character string is divided into individual words constituting the character string. A word conversion means for converting into a logical index as
Further comprising
In the name dictionary, the logical index combination is registered as a combination of the words, and in the unnecessary word dictionary, a logical index is registered as the unnecessary word,
The search means, the conversion means, and the unnecessary word registration means, as the input character string, a combination of logical indexes obtained by converting the input character string in units of words by the word conversion means The information conversion apparatus according to claim 1, wherein each process is performed using. Each time a character string composed of a plurality of words combined to represent a predetermined object is input, it is estimated that the input character string represents the input character string. An information conversion program for functioning as an information conversion device for converting into identification information given to the predetermined target,
For each object to which identification information is assigned, the computer registers each of the identification information assigned to each object and a combination of words constituting a character string representing each object, and registered First storage means for storing a dictionary and second storage means for storing an unnecessary word dictionary,
The computer,
By comparing each combination of words constituting the inputted character string with each combination of words registered in the name dictionary, the combination of the words constituting the inputted character string and the complete word unit Search means for searching for word combinations that match or partially match;
Conversion that determines a target estimated to represent the input character string based on a search result by the search means, and converts the input character string into identification information given to the determined target means,
And the combination of words extracted by the search by the search means includes a combination of words excluding specific words from a plurality of words constituting the input character string, and When it is determined by the conversion means that the input character string represents a specific object corresponding to a combination of words excluding the specific word, the specific word is set as the specific object. Corresponding to the given identification information, and functioning as unnecessary word registration means for registering as an unnecessary word of the specific target in the unnecessary word dictionary stored in the second storage means,
The conversion means includes a combination of words excluding a specific word from a plurality of words constituting the inputted character string in the combination of words extracted by the search by the search means. Specific identification information registered in the name dictionary in association with a combination of words excluding the specific word is registered in the unnecessary word dictionary in association with the specific word. If the specific identification information is associated with the specific word and registered in the unnecessary word dictionary, the input character string is given the specific identification information. An information conversion program characterized in that it represents a target.

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