JP2020173611A - Search processing program, search processing method, and search processing device - Google Patents

Abstract

To execute search to which an attribute is reflected for such a subject to be searched having a keyword being set for each attribute, even when input of a keyword is received in a state without having the attribute being designated.SOLUTION: A search processing device refers to an attribute candidate table 800, for identifying attribute keywords (words 711 to 714) from words 711 to 715 included in an input sentence 710. Next, the search processing device identifies registered words corresponding to the identified attribute keywords. Then, the search processing device extracts a document group 1110 including the identified registered words, as to attributes corresponding to the identified attribute keywords. Next, the search processing device identifies the word 715 other than the attribute keywords included in the input sentence 710 as a search keyword. Then, the search processing device identifies a search subject document 1120 from the document group 1110, based on the identified search keyword.SELECTED DRAWING: Figure 11

Description

The present invention relates to a search processing program, a search processing method, and a search processing apparatus.

In recent years, it has become popular to utilize unstructured data such as texts and images accumulated in a company for knowledge. Under such circumstances, there is a demand for a mechanism that enables efficient and easy search of documents (for example, product manuals, papers, etc.) accumulated in a company.

As a prior art, based on the field keyword entered by the user, the field / folder correspondence information database is referred to to select a folder containing the field keyword as an attribute, and the search index is referred to to search the selected folder. There is something to do.

Japanese Unexamined Patent Publication No. 2006-72705

However, in the prior art, it is difficult to perform a search in consideration of the attributes of the document to be searched. For example, it is conceivable to narrow down the search results by letting the user specify attributes for the set of search results searched by full-text search, but it is necessary to specify the attributes separately from the input of the search keyword. It takes time and effort.

On one aspect, it is an object of the present invention to execute a search reflecting an attribute for a search target in which a keyword is set for each attribute even if an input of a keyword is accepted without specifying an attribute.

In one embodiment, among the plurality of words received for the search for the search target, one or a plurality of words associated with each attribute of the search target previously stored in the storage unit are matched or similar. When it is determined whether or not the first word exists and it is determined that the first word exists, the first word is in the attribute associated with the word that matches or is similar to the first word. A search target group including a word is extracted, and the search is performed based on a comparison result between a second word other than the first word included in the plurality of words and a word included in the data of each of the search target groups. A search processing program that identifies the search target from the target group is provided.

According to one aspect of the present invention, even if the input of the keyword is accepted without specifying the attribute, the search target in which the keyword is set for each attribute can be searched by reflecting the attribute.

FIG. 1 is an explanatory diagram showing an embodiment of a search processing method according to an embodiment. FIG. 2 is an explanatory diagram showing a system configuration example of the search processing system 200. FIG. 3 is a block diagram showing a hardware configuration example of the search processing device 101. FIG. 4 is an explanatory diagram showing an example of the stored contents of the document management DB 220. FIG. 5 is an explanatory diagram showing an example of the stored contents of the product attribute table 230. FIG. 6 is a block diagram showing a functional configuration example of the search processing device 101. FIG. 7 is an explanatory diagram showing a comparative example of words. FIG. 8 is an explanatory diagram showing an example of the stored contents of the attribute candidate table 800. FIG. 9 is an explanatory diagram (No. 1) showing an example of narrowing down the attributes corresponding to the attribute keywords. FIG. 10 is an explanatory diagram (No. 2) showing an example of narrowing down the attributes corresponding to the attribute keywords. FIG. 11 is an explanatory diagram showing a document search example. FIG. 12 is an explanatory diagram showing a screen example of the search screen. FIG. 13 is a flowchart (No. 1) showing an example of the search processing procedure of the search processing device 101. FIG. 14 is a flowchart (No. 2) showing an example of the search processing procedure of the search processing device 101. FIG. 15 is a flowchart (No. 1) showing an example of a specific processing procedure of the matching process. FIG. 16 is a flowchart (No. 2) showing an example of a specific processing procedure of the matching process. FIG. 17 is a flowchart (No. 1) showing an example of a specific processing procedure of the search process. FIG. 18 is a flowchart (No. 2) showing an example of a specific processing procedure of the search process. FIG. 19 is an explanatory diagram showing an example of search conditions.

Hereinafter, embodiments of a search processing program, a search processing method, and a search processing apparatus according to the present invention will be described in detail with reference to the drawings.

(Embodiment)
FIG. 1 is an explanatory diagram showing an embodiment of a search processing method according to an embodiment. In FIG. 1, the search processing device 101 is a computer that executes a search reflecting the attributes based on the keywords input in a state where the attributes are not specified. Attributes are information that characterizes the search target.

The search target is, for example, a document (document data) such as a product manual or a paper. Attribute information indicating the attribute is given to the search target. For example, when the search target is a product manual, the attributes are the product name, edition (version number), OS (Operating System), version information, and the like.

As an existing search method, attribute information is added to a document to be searched, and at the time of search, the input keyword outputs a document included in the text or attribute information as a search result. However, if the search is performed using the entered keyword without distinguishing between the text and the attribute information, the noise (information not intended by the user) included in the search result will increase.

Further, as a method of reducing noise included in the search result, for example, there is a method of narrowing down the search result by having the user specify an attribute for a set of search results searched for the text. However, there is a problem that it takes time and effort because an operation of specifying an attribute is required separately from inputting a search keyword. In addition, if the user does not know the details of the attribute, the attribute for narrowing down the search result cannot be specified.

Therefore, in the present embodiment, even if the input of the keyword is accepted without specifying the attribute, the search processing method that enables the search reflecting the attribute for the search target in which the keyword is set for each attribute will be described. .. Hereinafter, a processing example of the search processing device 101 will be described.

(1) The search processing device 101 includes one or a plurality of words associated with each attribute of the search target previously stored in the storage unit 110 among the plurality of words received for the search for the search target. Determine if there is a first word that matches or is similar.

Here, the plurality of words are two or more words that are input as keywords at the time of search. The one or more words associated with each attribute to be searched are one or more words included in the words and phrases registered in advance as keywords corresponding to the attribute. For example, as a keyword of the attribute "product name", a product name that actually exists is set.

Specifically, for example, the search processing device 101 compares each word of the received plurality of words with each word associated with each attribute of the search target. Then, the search processing device 101 has a first word that matches or is similar to any word associated with each attribute of the search target among the plurality of received words based on the comparison result. Judge whether or not.

In the example of FIG. 1, it is assumed that the word 111 (xxx) and the word 112 (aaa) are accepted for the search for the search target. Further, the storage unit 110 is associated with the word "xxx" associated with the search target attribute 1, the word "yyy" associated with the search target attribute 2, and the search target attribute 3. It is assumed that the word "zzz" is stored.

In this case, the search processing device 101 compares each of the words 111 and 112 with each word associated with each of the attributes 1 to 3 of the search target. Here, the received word 111 (xxx) matches the word "xxx" associated with the attribute 1 to be searched. Therefore, it is determined that the first word "xxx" exists.

(2) When the search processing device 101 determines that the first word exists, it extracts a search target group including the first word in the attribute associated with the word that matches or is similar to the first word. To do. Here, the plurality of search targets that are the extraction sources are, for example, documents accumulated in the company.

Further, in the attribute associated with the word that matches or is similar to the first word, the search target including the first word is a word that matches or is similar to the first word among the attributes that characterize the search target. The search target includes the first word in the attribute value of the associated attribute.

That is, the search processing device 101 extracts a search target group in which the first word is included in the attribute value of the attribute associated with the word that matches or is similar to the first word from the plurality of search targets. To do. As a result, the search target group including the first word can be narrowed down to the attribute value of the attribute associated with the word that matches or is similar to the first word.

In the example of FIG. 1, the search processing device 101 extracts a search target group in which the first word “xxx” is included in the attribute value of the attribute 1 from the extraction source 120. In addition, attribute information indicating the attribute values of attributes 1 to 3 is given to each search target included in the extraction source 120. Here, it is assumed that the search target group 121 is extracted.

(3) The search processing device 101 searches based on the comparison result between the second word other than the first word included in the received plurality of words and the word included in the data of each of the extracted search target groups. Identify the search target from the target group. Here, the data of each search target group is, for example, the text information of the document.

Specifically, for example, the search processing device 101 identifies a second word other than the first word among the plurality of received words. Next, the search processing device 101 compares the specified second word with the word included in the data of each of the extracted search target groups. Then, the search processing device 101 identifies a search target whose data includes a word that matches the second word from the extracted search target group.

In the example of FIG. 1, the search processing device 101 identifies a second word “aaa” other than the first word “xxx” among the received words 111 and 112. Next, the search processing device 101 compares the second word “aaa” with the word included in the data of each of the extracted search target group 121. Then, the search processing device 101 identifies a search target whose data includes a word that matches the second word "aaa" from the search target group 121. Here, the search target set 122 is specified.

As described above, according to the search processing device 101, even if the input of the keyword is accepted without specifying the attribute, the search target in which the keyword is set for each attribute can be searched by reflecting the attribute. ..

In the example of FIG. 1, the words 111 and 112 received for the search for the search target are narrowed down (first word) and full-text search words (words for full-text search) without the user having to consciously input the words. It can be classified into the second word). As a result, it is possible to estimate the attribute information that the user wants to specify, narrow down the search target group 121, and then perform a full-text search, reduce noise included in the search results, and make it easier for the user to find the information that the user wants. it can.

(System configuration example of search processing system 200)
Next, a system configuration example of the search processing system 200 according to the embodiment will be described. The search processing system 200 is a computer system including the search processing device 101 shown in FIG. 1, and is applied to, for example, a system for utilizing knowledge of documents stored in a company.

FIG. 2 is an explanatory diagram showing a system configuration example of the search processing system 200. In FIG. 2, the search processing system 200 includes a search processing device 101 and a client device 201. In the search processing system 200, the search processing device 101 and the client device 201 are connected via a wired or wireless network 210. The network 210 is, for example, a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, or the like.

Here, the search processing device 101 has a document management DB (Database) 220 and a product attribute table 230. For example, the search processing device 101 is a server. The search processing device 101 may be realized by a plurality of servers. The stored contents of 220 and 230 of various DBs and the like will be described later with reference to FIGS. 4 and 5. The storage unit 110 shown in FIG. 1 corresponds to, for example, the product attribute table 230.

However, the various DBs 220 and 230 may be provided by another computer that can be accessed by the search processing device 101. In this case, the search processing device 101 can access another computer and refer to the stored contents of 220 and 230 such as various DBs.

The client device 201 is a computer used by the user of the search processing system 200. The user is, for example, an employee of a company in which the search processing system 200 is introduced. The client device 201 is, for example, a PC (Personal Computer), a tablet PC, a smartphone, or the like.

In the example of FIG. 2, only one client device 201 is displayed, but the search processing system 200 may include a plurality of client devices 201.

(Example of hardware configuration of search processing device 101)
FIG. 3 is a block diagram showing a hardware configuration example of the search processing device 101. In FIG. 3, the search processing device 101 includes a CPU (Central Processing Unit) 301, a memory 302, a disk drive 303, a disk 304, a communication I / F (Interface) 305, and a portable recording medium I / F 306. Have. Further, each component is connected by a bus 300.

Here, the CPU 301 controls the entire search processing device 101. The CPU 301 may have a plurality of cores. The memory 302 includes, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), a flash ROM, and the like. Specifically, for example, the flash ROM stores the OS (Operating System) program, the ROM stores the application program, and the RAM is used as the work area of the CPU 301. The program stored in the memory 302 is loaded into the CPU 301 to cause the CPU 301 to execute the coded process.

The disk drive 303 controls data read / write to the disk 304 according to the control of the CPU 301. The disk 304 stores the data written under the control of the disk drive 303. Examples of the disk 304 include a magnetic disk and an optical disk.

The communication I / F 305 is connected to the network 210 through a communication line, and is connected to an external computer (for example, the client device 201 shown in FIG. 2) via the network 210. The communication I / F 305 controls the interface between the network 210 and the inside of the device, and controls the input / output of data from an external computer. For the communication I / F 305, for example, a modem, a LAN adapter, or the like can be adopted.

The portable recording medium I / F 306 controls data read / write to the portable recording medium 307 according to the control of the CPU 301. The portable recording medium 307 stores the data written under the control of the portable recording medium I / F 306. Examples of the portable recording medium 307 include a CD (Compact Disc) -ROM, a DVD (Digital Versaille Disk), and a USB (Universal Serial Bus) memory.

In addition to the above-mentioned components, the search processing device 101 may include, for example, an SSD (Solid State Drive), an input device, a display, and the like. Further, the search processing device 101 does not have to have, for example, a disk drive 303, a disk 304, a portable recording medium I / F 306, and a portable recording medium 307 among the above-described components.

Further, the client device 201 shown in FIG. 2 can also be realized by the same hardware configuration as the search processing device 101. However, the client device 201 has an input device and a display in addition to the above-described components. The input device has keys for inputting characters, numbers, various instructions, etc., and inputs data. The input device may be a keyboard, a mouse, or the like, or may be a touch panel type input pad, a numeric keypad, or the like. A display is a display device that displays data such as a cursor, an icon, a toolbox, a document, an image, and functional information. As the display, for example, a liquid crystal display, an organic EL (Electroluminescence) display, or the like can be adopted.

(Memory contents of 220 and 230 such as various DBs)
Next, the stored contents of various DBs and the like 220 and 230 included in the search processing device 101 will be described with reference to FIGS. 4 and 5. The various DBs 220 and 230 are realized, for example, by storage devices such as the memory 302 and the disk 304 of the search processing device 101 shown in FIG.

FIG. 4 is an explanatory diagram showing an example of the stored contents of the document management DB 220. In FIG. 4, the document management DB 220 has fields for document ID, product name, edition, family product name, OS, and text information. By setting information in each field, document management information (for example, document management information 400-1, 400-2) is stored as a record.

Here, the document ID is an identifier that uniquely identifies the document to be searched. The document is, for example, HTML (HyperText Markup Language) format data of one file per page. Here, a case where the document to be searched is a "product manual" will be described as an example.

The product name, edition, family product name, and OS are examples of attributes that characterize the document to be searched. The product name is the name of the product. The edition is the edition of the product. Family product names are the names of related products. The OS is the OS on which the product operates.

The text information indicates the text of the document to be searched. However, the text information may be information indicating the storage location of the document (for example, URL: Uniform Resource Locator). In this case, the client device 201 can refer to the text by reading the text from the storage location indicated by the text information.

For example, the document management information 400-1 includes the product name "Interstage Charge Manager" of the document D1, the edition "Enterprise Edition", the family product name "xxx", the OS "Windows (registered trademark)", and the text information "...". Is shown.

In addition, the document management information 400-2 includes the product name "Interstage Charge Manager" of the document D2, the edition "Enterprise Edition", the family product name "xxx", the OS "Linux (registered trademark)", and the text information "...". Is shown.

FIG. 5 is an explanatory diagram showing an example of the stored contents of the product attribute table 230. In FIG. 5, the product attribute table 230 has fields for attribute names and registered words, and by setting information in each field, product attribute information (for example, product attribute information 500-1 to 500-3) is recorded. Remember as.

Here, the attribute name indicates the name of the attribute that characterizes the document to be searched. A registered word is a phrase containing one or more words associated with an attribute of an attribute name. For example, as a registered word of the attribute name "product name", a product name that actually exists is set. In addition, the edition of the product that actually exists is set as the registered word of the attribute name "edition". As the registered word of the attribute name "family product name", the related product name that actually exists is set. As the registered word of the attribute name "OS", the OS name that actually exists is set.

For example, the product attribute information 500-1 indicates the registered word “Interstage Charge Manager” of the attribute name “product name”.

(Example of Functional Configuration of Search Processing Device 101)
FIG. 6 is a block diagram showing a functional configuration example of the search processing device 101. In FIG. 6, the search processing device 101 includes a reception unit 601, a determination unit 602, an extraction unit 603, a specific unit 604, an output unit 605, and a storage unit 610. Specifically, for example, the reception units 601 to the output units 605 may cause the CPU 301 to execute a program stored in a storage device such as the memory 302, the disk 304, or the portable recording medium 307 shown in FIG. , Communication I / F 305 realizes the function. The processing result of each functional unit is stored in a storage device such as a memory 302 or a disk 304, for example. The storage unit 610 is realized by a storage device such as a memory 302 or a disk 304, for example. Specifically, for example, the storage unit 610 stores the document management DB 220 shown in FIG. 4 and the product attribute table 230 shown in FIG.

The reception unit 601 accepts a plurality of words for searching for the search target. Here, the plurality of words are two or more words that are input as keywords at the time of search. The input of the plurality of words is performed, for example, by the user's operation input using the input device (not shown) in the client device 201 shown in FIG.

Specifically, for example, the reception unit 601 receives an input sentence included in the received search request by receiving the search request from the client device 201. The input sentence includes a plurality of words input as keywords. The search request is made, for example, on the search screen 1200 shown in FIG. 12, which will be described later. However, the reception unit 601 may accept a plurality of words by the user's operation input using the input device (not shown) of the own device.

Among the plurality of received words, the determination unit 602 includes a first word that matches or is similar to one or a plurality of words associated with each attribute of the search target stored in advance in the storage unit 610. Determine whether or not to do so. Here, the one or more words associated with each attribute to be searched are one or a plurality of words included in a word (registered word) registered in advance as a keyword corresponding to the attribute.

In the following description, a word may be referred to as a "word".

Specifically, for example, the determination unit 602 divides the received input sentence into words. At this time, the determination unit 602 also holds, for example, the word order of the words divided from the input sentence. As a result, a plurality of words for searching for the search target can be obtained. The process of dividing into words can be performed by using techniques such as dictionary information and morphological analysis.

Further, the determination unit 602 divides the registered word associated with the attribute to be searched into words by referring to the product attribute table 230 shown in FIG. At this time, the determination unit 602 also holds, for example, the word order of the words divided from the registered words. As a result, one or more words associated with the attribute to be searched can be obtained.

Next, the determination unit 602 compares the word divided from the input sentence with the word divided from the registered word for each divided word. Some registered words associated with attributes are composed of a plurality of words. Therefore, the determination unit 602 may, for example, compare the word string included in the input sentence with the word string included in the registered word. A word sequence is a sequence of a plurality of words arranged in word order.

Here, when the character strings of the compared words (or word strings) completely match, the determination unit 602 determines that the words (or word strings) match. On the other hand, when the character strings of the compared words (or word strings) do not completely match, the determination unit 602 determines that the words (or word strings) do not match.

However, since the input text is free input, spelling mistakes may occur during input. In order to allow a certain amount of spelling mistakes, the determination unit 602 may determine that the words (or word strings) are similar if the difference is about several characters. The number of characters allowed may be determined according to the number of characters in the word (or word string).

For example, for words of 4 or more characters, the allowable number of characters is "2", and for words of less than 4 characters, the allowable number of characters is "0". In this case, the determination unit 602 determines that the words are similar for words having 4 or more characters, even if the character strings of the compared words do not exactly match, if the number of mismatched characters is 2 or less. Further, the determination unit 602 determines that the words having less than 4 characters are not similar even if the number of mismatched characters is "1".

Further, when the character strings of the compared words (or word strings) do not completely match, the determination unit 602 may calculate the editing distance between the words (or the word strings). The edit distance (Levenshtein distance) is an index value indicating how different the two character strings are. Then, if the calculated editing distance is equal to or less than a predetermined threshold value, the determination unit 602 may use the word (or word) even if the character strings of the compared words (or word strings) do not completely match. It may be determined that the columns) are similar.

Further, depending on the attribute name (for example, the product name), it may be represented by an abbreviation in the input sentence. Therefore, the determination unit 602 converts the abbreviation into a formal name by using, for example, dictionary information indicating the correspondence between the abbreviation and the formal name, and then uses the converted word (formal name) and the registered word. You may want to compare it with the divided words.

Then, the determination unit 602 matches or resembles at least one word (or word string) divided from the registered word among the plurality of words (or word strings) divided from the input sentence (or word). Column) is specified as the first word. A comparative example of words will be described later with reference to FIG. 7.

When it is determined that the first word exists, the extraction unit 603 includes the first word in the attribute associated with the word that matches or is similar to the first word from among a plurality of search targets. Extract the search target group. Here, the plurality of search targets are, for example, documents accumulated in the company.

In the attribute associated with the word matching or similar to the first word, the search target including the first word is the attribute value of the attribute associated with the word matching or similar to the first word. , Is a search target including the first word. That is, the first word is used as a keyword (attribute keyword) when narrowing down the search target by the attribute.

However, the first word may contain misspellings. In addition, the first word may be represented by an abbreviation. Therefore, the extraction unit 603 extracts a search target group including the word (word that matches or is similar to the first word) in the attribute associated with the word that matches or is similar to the first word. It may be.

Further, when it is determined that the first word exists, the extraction unit 603 sets the attribute in the attribute associated with the word that matches or is similar to the first word from among a plurality of search targets. A search target group including one or a plurality of associated words may be extracted.

More specifically, for example, the extraction unit 603 refers to the document management DB 220 shown in FIG. 4 and associates it with the attribute in the attribute associated with the word that matches or is similar to the first word. Extract the document group including the registered words.

Here, the attribute associated with the word that matches or is similar to the first word is defined as the attribute "OS", and the registered word associated with the attribute "OS" is defined as "Windows". In this case, the determination unit 602 refers to the document management DB 220 and extracts a document group (for example, document D1) including the registered word "Windows" in the attribute value of the attribute "product name".

As a result, the attribute (attribute value) that the user wants to specify can be estimated from the input sentence, and the documents to be searched can be narrowed down.

There may be a plurality of first words among the plurality of received words. In this case, the extraction unit 603 is, for example, a search target including a registered word associated with the attribute in an attribute associated with a word that matches or is similar to at least one of the plurality of first words. A group may be extracted. Further, the extraction unit 603 extracts a search target group including a registered word associated with each attribute in each attribute associated with a word that matches or is similar to each word of the plurality of first words. You may decide.

The specific unit 604 sets the search target group based on the comparison result between the second word other than the first word included in the received plurality of words and the word included in the data of each of the extracted search target groups. Identify the search target from the inside.

Specifically, for example, the identification unit 604 specifies a word other than the first word in the input sentence as the second word. In addition, the specific unit 604 refers to the document management DB 220 and acquires the text information of each of the extracted document groups. Next, the specific unit 604 compares the specified second word with the word included in the text information of each document group.

Then, the identification unit 604 identifies a document in which the word matching the second word is included in the text information from the extracted document group. Further, the specifying unit 604 may specify a document in which a word similar to the second word is included in the text information from the document group.

That is, the identification unit 604 specifies a document from the extracted document group using a word other than the first word (second word) in the input sentence as a search keyword.

In addition, there may be a plurality of second words. In this case, the specific unit 604 may specify a document whose body information includes a word that matches or is similar to at least one of a plurality of second words from the document group (OR search). ). Further, the identification unit 604 may specify a document in which all the words that match or are similar to each word of the plurality of second words are included in the text information from the document group (AND search).

The output unit 605 outputs the specified search target for the plurality of received words. Specifically, for example, the output unit 605 outputs information (for example, a title, a summary, etc.) indicating the specified document as a search result for the search request from the client device 201. As a result, in the client device 201, the search result for the search request is displayed on the display (not shown).

Further, the output unit 605 outputs the words and phrases associated with the attributes associated with the first word and the words that match or are similar to the first word, together with the specified search target, for the received plurality of words. You may do it. Here, the phrase associated with the attribute is a phrase composed of one or a plurality of words associated with the attribute, and is, for example, a registered word associated with the attribute (see FIG. 5).

More specifically, for example, the output unit 605 is a search that displays the registered word associated with the attribute associated with the word that matches or is similar to the first word, together with the information indicating the specified document. The screen may be displayed on the client device 201. As a result, it is possible to present information that can identify the attributes used to narrow down the search results when displaying the search results for the search request. A screen example of the search screen will be described later with reference to FIG.

In the above description, when it is determined that the first word exists, the extraction unit 603 has an attribute associated with a word that matches or is similar to the first word from among a plurality of search targets. In, it was decided to extract the search target group including the first word, but the present invention is not limited to this.

For example, when it is determined that the first word exists, the extraction unit 603 is included in the second word other than the first word included in the received plurality of words and in the data of each of the plurality of search targets. A search target group may be extracted from a plurality of search targets based on the comparison result with the word. That is, the extraction unit 603 extracts a search target group from a plurality of search targets using a second word other than the first word among the plurality of words as a search keyword. Then, the specific unit 604 identifies the search target including the first word in the attribute associated with the word that matches or is similar to the first word from the extracted search target group. May be good.

(Example of word comparison)
Next, a comparison example of a word divided from the input sentence and a word divided from the registered words associated with each attribute to be searched will be described.

FIG. 7 is an explanatory diagram showing a comparative example of words. In FIG. 7, the input sentence 710 is an example of the input sentence included in the search request from the client device 201. The determination unit 602 divides the input sentence 710 into words. In the example of FIG. 7, the input sentence 710 is divided into the word 711 (Charset), the word 712 (Enterprise), the word 713 (Edition), the word 714 (Windows), and the word 715 (installation).

Further, the determination unit 602 refers to the product attribute table 230 and divides each registered word associated with the attribute to be searched into a word for each attribute. Here, the attributes are "product name", "edition", "family product name", and "OS". Further, the registered words associated with the attribute "product name" are "Interstage Charge Manager" and "Enterpress".

In this case, the determination unit 602 divides the registered word "Interstage Charge Manager" into words. Here, it is divided into the word 721 (Interstage), the word 722 (Charset), and the word 723 (Manager). The registered word "Enterprise" is not divided because it is one word, and becomes the word 731 (Enterprise).

Further, the registered word associated with the attribute "edition" is defined as "Enterprise Edition". In this case, the determination unit 602 divides the registered word "Enterprise Edition" into words. Here, it is divided into the word 741 (Enterprise) and the word 742 (Edition).

In addition, the registered word associated with the attribute "family product name" is defined as "development package for Windows". In this case, the determination unit 602 divides the registered word "development package for Windows" into words. Here, it is divided into word 751 (development), word 752 (package), word 753 (for) and word 754 (Windows). Further, the registered word associated with the attribute "OS" is defined as "Windows". The registered word "Windows" is not divided because it is one word, and becomes the word 761 (Windows).

Next, the determination unit 602 compares the words 711 to 715 divided from the input sentence with the words 721 to 723, 731, 741, 742, 751 to 754, 761 divided from the registered words for each divided word. .. For example, for word 711, the comparison result with word 722 is "match", and the comparison result with other words is "mismatch and dissimilarity".

Further, regarding the word 712, the comparison result with the words 731 and 741 is "match", and the comparison result with the other words is "disagreement and dissimilarity". Further, regarding the word 713, the comparison result with the word 742 is "match", and the comparison result with the other words is "disagreement and dissimilarity". Further, regarding the word 714, the comparison result with the words 754 and 761 is "match", and the comparison result with the other words is "mismatch and dissimilarity". Further, for the word 715, the comparison result with all the words is "mismatch and dissimilar".

As a result of comparison, among the words 711 to 715 divided from the input sentence, the word (first word) determined to match or be similar to at least one of the words divided from the registered words is, for example, as shown in FIG. It is stored in the attribute candidate table 800. The attribute candidate table 800 is realized by a storage device such as a memory 302 or a disk 304, for example.

FIG. 8 is an explanatory diagram showing an example of the stored contents of the attribute candidate table 800. In FIG. 8, the attribute candidate table 800 has fields of attribute name, attribute keyword, and registered word, and by setting information in each field, attribute candidate information 800-1 to 800-5 is stored as a record. ..

Here, the attribute name indicates the name of the attribute that characterizes the document to be searched. The attribute keyword indicates a word (first word) that matches or is similar to at least one word divided from the registered word associated with the attribute of the attribute name among the words divided from the input sentence. Attribute keywords correspond to keywords used when narrowing down the search target by attribute. The registered word indicates a registered word associated with the attribute of the attribute name.

For example, the attribute candidate information 800-1 indicates the attribute keyword “Charset” of the attribute “product name” and the registered word “Interstage Charge Manager”. According to the attribute candidate table 800, among the words included in the input sentence (for example, the input sentence 710), the words that match or are similar to the words included in the registered words associated with the attribute to be searched (first word). ) Can be specified.

(Narrowing down the attributes corresponding to the attribute keywords)
Here, there may be a plurality of attributes associated with a word that matches or is similar to the first word. That is, there may be a plurality of attributes corresponding to the attribute keywords. In this case, the attribute corresponding to the attribute keyword (first word) may be selected from the plurality of attributes.

For example, when the extraction unit 603 has a plurality of attributes associated with a word that matches or is similar to the first word, for each attribute of the plurality of attributes, among the plurality of words received, each attribute The number of words that match or are similar to one or more associated words may be calculated. At this time, the extraction unit 603 may calculate the number of words that continuously match or are similar to one or more words associated with each attribute among the plurality of received words for each attribute. Good. Then, the extraction unit 603 may specify the attribute having the largest number of calculated words from the plurality of attributes. In this case, the extraction unit 603 extracts the search target group including the first word (or the registered word associated with the attribute) in the specified attribute.

More specifically, for example, the extraction unit 603 refers to the attribute candidate table 800 shown in FIG. 8 and has a plurality of attributes associated with words that match or are similar to the attribute keyword (first word). Determine if it exists. In the example of FIG. 8, the attribute keyword "Enterprise" corresponds to the attribute "product name" and the attribute "edition".

In this case, for example, for each attribute of the attribute "product name" and the attribute "edition", the extraction unit 603 is continuous with the word included in the registered word associated with each attribute among the words included in the input sentence. Calculate the number of matching or similar words. Here, an example of calculating the number of words (word length) will be described with reference to FIG.

FIG. 9 is an explanatory diagram (No. 1) showing an example of narrowing down the attributes corresponding to the attribute keywords. For example, the extraction unit 603 refers to the attribute candidate information 800-2, and among the words 711 to 715 included in the input sentence 710 (see FIG. 7), the registered word "Enterprise" associated with the attribute "product name". The number of words (word length) that continuously match or are similar to the word 731 included in "" is calculated. Here, the word length "1" is calculated.

Further, the extraction unit 603 is included in the registered word "Enterprise Edition" associated with the attribute "edition" among the words 711 to 715 included in the input sentence 710 with reference to the attribute candidate information 800-3, for example. The number of words (word length) that continuously match or are similar to the words 741 and 742 that are used is calculated. Here, the word length "2" is calculated.

Then, the extraction unit 603 specifies the attribute "edition" having the maximum calculated word length from the attribute "product name" and the attribute "edition". In this case, the extraction unit 603 deletes the attribute candidate information 800-2 from the attribute candidate table 800. As a result, the attributes corresponding to the attribute keyword "Enterprise" can be narrowed down to one.

In addition, the attribute keyword "Windows" corresponds to the attribute "family product name" and the attribute "OS". However, for the attribute keyword "Windows", the word length of each attribute of the attribute "family product name" and the attribute "OS" is "1", and the attribute cannot be narrowed down to one from the word length.

Therefore, when there are a plurality of attributes associated with a word that matches or is similar to the first word, the extraction unit 603 may use one or a plurality of attributes associated with each attribute for each attribute of the plurality of attributes. Among the words, the character string ratio occupied by words that match or are similar to the words included in the plurality of accepted words may be calculated. Then, the extraction unit 603 may specify the attribute having the maximum calculated character string ratio from the plurality of attributes. In this case, the extraction unit 603 extracts the search target group including the first word (or the registered word associated with the attribute) in the specified attribute.

More specifically, for example, the extraction unit 603 matches each attribute of the attribute "family product name" and the attribute "OS" with the word included in the input sentence among the registered words associated with each attribute. Calculate the character string ratio occupied by similar words. Here, an example of calculating the character string ratio will be described with reference to FIG.

FIG. 10 is an explanatory diagram (No. 2) showing an example of narrowing down the attributes corresponding to the attribute keywords. The extraction unit 603 is included in the input sentence 710 (see FIG. 7) of the registered word “development package for Windows” associated with the attribute “family product name” with reference to the attribute candidate information 800-4, for example. Calculate the character string ratio occupied by words that match or are similar to the words 711 to 715.

Here, since the word 754 (Windows) in the registered word "development package for Windows" matches the word 714 included in the input sentence 710, the character string ratio "7/19" is calculated. The denominator "19" is the number of characters in the registered word "development package for Windows". The "7" in the numerator is the number of characters in "Windows".

Further, the extraction unit 603 refers to, for example, the attribute candidate information 800-5, and matches or matches the words 711 to 715 included in the input sentence 710 among the registered words "Windows" associated with the attribute "OS". Calculate the string ratio occupied by similar words. Here, since the registered word "Windows" matches the word 714 included in the input sentence 710, the character string ratio "7/7" is calculated.

Then, the extraction unit 603 specifies the attribute "OS" having the maximum calculated character string ratio from the attribute "family product name" and the attribute "OS". In this case, the extraction unit 603 deletes the attribute candidate information 800-4 from the attribute candidate table 800. As a result, the attributes corresponding to the attribute keyword "Windows" can be narrowed down to one.

When there are a plurality of attributes associated with a word that matches or is similar to the first word, the extraction unit 603 has the highest priority among the plurality of attributes according to a predetermined priority for each attribute. You may want to identify attributes with high.

Further, a word that is not used as an attribute keyword may be registered in advance as a stop word. For example, a word included in many registered words may be registered in advance as a stop word. In this case, even if the input sentence contains a word that matches or is similar to the word included in the registered word associated with the attribute, if the word is a stop word, the determination unit 602 first It may not be adopted as a ward. As a result, it is possible to prevent many registered words from being hit and increasing the number of noises included in the search results.

(Document search example)
Next, a search example of the document to be searched will be described with reference to FIG.

FIG. 11 is an explanatory diagram showing a document search example. In FIG. 11, the extraction unit 603 specifies, for example, the attribute keyword among the words 711 to 715 included in the input sentence 710 with reference to the attribute candidate table 800 shown in FIG. Here, the words 711 to 714 are specified as attribute keywords.

Next, the extraction unit 603 refers to the attribute candidate table 800 and identifies the registered word corresponding to the specified attribute keyword. Here, as the registered word corresponding to the attribute keyword (word 711), the registered word "Interstage Charge Manager" of the attribute "product name" is specified. Further, as a registered word corresponding to the attribute keyword (words 712, 713), the registered word "Enterprise Edition" of the attribute "edition" is specified. As a registered word corresponding to the attribute keyword (word 714), the registered word "Windows" of the attribute "OS" is specified.

Then, the extraction unit 603 extracts a document group satisfying at least one of the following (i), (ii), and (iii) with reference to the document management DB 220. Further, the extraction unit 603 may refer to the document management DB 220 and extract a document group that satisfies all of the following conditions (i), (ii), and (iii).

(I) The attribute value of the attribute "product name" includes the registered word "Interstage Charge Manager".

(Ii) The registered word "Enterprise Edition" is included in the attribute value of the attribute "edition".

(Iii) The registered word "Windows" is included in the attribute value of the attribute "OS".

In the example of FIG. 11, it is assumed that the document group 1110 satisfying all the above conditions (i), (ii) and (iii) is extracted.

Next, the specifying unit 604 specifies a word (second word) other than the attribute keyword among the words 711 to 715 included in the input sentence 710 as a search keyword. Here, the word 715 is specified as a search keyword. Then, the specific unit 604 identifies the document to be searched from the document group 1110 based on the comparison result between the specified search keyword and the word included in the text information of each of the extracted document group 1110.

In the example of FIG. 11, a document set 1120 including the search keyword “install” in the text information is specified from the document group 1110. The document set 1120 is the result of performing a full-text search after narrowing down the document group 1110 having the attributes desired by the user, and can be said to be a search result with less noise.

(Screen example of search screen)
Next, a screen example of the search screen displayed on the client device 201 will be described with reference to FIG.

FIG. 12 is an explanatory diagram showing a screen example of the search screen. In FIG. 12, the search screen 1200 is an example of an operation screen for displaying the search result 1210 for the search request including the input sentence input in the box 1201. The search result 1210 includes search target information 121 to 1213.

The search target information 121 to 1213 indicates, for example, the title or summary of the document to be searched. On the search screen 1200, the text information of the document can be browsed by selecting any of the search target information 1211 to 1213 by the user's operation input using the input device (not shown).

Further, the attribute information 1220 is displayed on the search screen 1200. The attribute information 1220 indicates a registered word associated with an attribute associated with a word that matches or is similar to the attribute keyword (first word) included in the input sentence. According to the attribute information 1220, the user can specify what kind of attribute the search result is narrowed down.

(Search processing procedure of the search processing device 101)
Next, the search processing procedure of the search processing device 101 will be described with reference to FIGS. 13 and 14.

13 and 14 are flowcharts showing an example of the search processing procedure of the search processing device 101. In the flowchart of FIG. 13, first, the search processing device 101 determines whether or not a search request has been received from the client device 201 (step S1301). Here, the search processing device 101 waits for receiving the search request (step S1301: No).

Then, when the search processing device 101 receives the search request (step S1301: Yes), the search processing device 101 divides the input sentence included in the received search request into words (step S1302). Next, the search processing device 101 selects an unselected attribute among the attributes whose attribute names are registered in the product attribute table 230 (step S1303).

Next, the search processing device 101 refers to the product attribute table 230 and selects an unselected registered word among the registered words of the selected attribute (step S1304). Then, the search processing device 101 divides the selected registered word into words (step S1305). Next, the search processing device 101 executes a matching process of comparing the word divided from the input sentence with the word divided from the registered word (step S1306).

The specific processing procedure of the matching process will be described later with reference to FIGS. 15 and 16.

Then, the search processing device 101 refers to the attribute keyword detection flag corresponding to the selected attribute, and determines whether or not there is an attribute keyword (step S1307). The attribute keyword is a word (first word) that matches or is similar to one or more words divided from the registered word among the words divided from the input sentence.

The attribute keyword detection flag is a flag indicating whether or not the attribute keyword of the registered word is detected in the input sentence. The attribute keyword detection flag is "true" when the input sentence contains a word constituting the registered word, and is "false" when the word constituting the registered word is not included.

Here, if there is no attribute keyword (step S1307: No), the search processing device 101 shifts to step S1309. On the other hand, when there is an attribute keyword (step S1307: Yes), the attribute keyword and a registered word including a word that matches or is similar to the attribute keyword are registered in the attribute candidate table 800 in association with the attribute name of the selected attribute. (Step S1308). The attribute keyword is a word registered in the word list of the attribute keyword corresponding to the selected attribute.

Next, the search processing device 101 refers to the product attribute table 230 and determines whether or not there is an unselected registered word among the registered words of the selected attribute (step S1309). Here, if there is an unselected registered word (step S1309: Yes), the search processing device 101 returns to step S1304.

On the other hand, when there is no unselected registered word (step S1309: No), the search processing device 101 determines whether or not there is an unselected attribute among the attributes whose attribute name is registered in the product attribute table 230. (Step S1310). Here, if there is an unselected attribute (step S1310: Yes), the search processing device 101 returns to step S1303.

On the other hand, when there is no unselected attribute (step S1310: No), the search processing device 101 shifts to step S1401 shown in FIG.

In the flowchart of FIG. 14, first, the search processing device 101 refers to the attribute candidate table 800 and determines whether or not a plurality of attributes corresponding to the attribute keywords exist (step S1401). Here, when the plurality of attributes do not exist (step S1401: No), the search processing device 101 shifts to step S1403.

On the other hand, when a plurality of attributes corresponding to the attribute keywords exist (step S1401: Yes), the search processing device 101 identifies the attribute corresponding to the attribute keyword from the plurality of attributes (step S1402). For the identification of the attribute, for example, the word length described in FIG. 9 and the character string ratio described in FIG. 10 are used.

Next, the search processing device 101 identifies a word other than the attribute keyword from the input sentence as a search keyword (step S1403). Then, the search processing device 101 creates a search condition based on the registered word associated with the attribute corresponding to the attribute keyword and the specified search keyword (step S1404). The registered word associated with the attribute corresponding to the attribute keyword is a registered word that is a narrowing condition, and is specified from the attribute candidate table 800. A specific example of the search condition will be described later with reference to FIG.

Next, the search processing device 101 executes a search process for searching the document to be searched based on the created search condition (step S1405). Then, the search processing device 101 outputs a search result (step S1406), and ends a series of processes according to this flowchart. The search result is information indicating a record stored in the search result storage list described later.

As a result, even if the input of the input sentence (search keyword) is accepted without specifying the attribute, the search reflecting the attribute can be executed.

Next, a specific processing procedure of the matching process of step S1306 shown in FIG. 13 will be described with reference to FIGS. 15 and 16.

15 and 16 are flowcharts showing an example of a specific processing procedure of the matching process. In the flowchart of FIG. 15, first, the search processing device 101 sets the attribute keyword detection flag corresponding to the attribute selected in step S1303 shown in FIG. 13 to “false” (step S1501).

Next, the search processing device 101 initializes the word list of the attribute keywords corresponding to the selected attributes (step S1502). Then, the search processing device 101 initializes "i" with "i = 0" (step S1503) and initializes "j" with "j = 0" (step S1504).

Next, the search processing device 101 compares the i-th word of the registered word selected in step S1304 shown in FIG. 13 with the j-th word of the input sentence (step S1505). However, the first word is the 0th word. Then, the search processing device 101 determines whether or not the i-th word of the registered word and the j-th word of the input sentence match (step S1506). Note that a word match means that the words match or are similar.

Here, if the words do not match (step S1506: No), the search processing device 101 shifts to step S1605 shown in FIG. On the other hand, when the words match (step S1506: Yes), the search processing device 101 determines whether or not the attribute keyword detection flag corresponding to the selected attribute is "false" (step S1507).

Here, when the attribute keyword detection flag is "true" (step S1507: No), the search processing device 101 shifts to step S1509. On the other hand, when the attribute keyword detection flag is "false" (step S1507: Yes), the search processing device 101 sets the attribute keyword detection flag to "true" (step S1508).

Then, the search processing device 101 stores the j-th word of the input sentence at the end of the word list of the attribute keywords corresponding to the selected attribute (step S1509), and proceeds to step S1601 shown in FIG.

In the flowchart of FIG. 16, first, the search processing device 101 sets “i” to “i = i + 1” (step S1601) and “j” to “j = j + 1” (step S1602). Then, the search processing device 101 determines whether or not "j" is equal to or greater than the number of words constituting the input sentence (step S1603).

Here, when "j" is equal to or greater than the number of words constituting the input sentence (step S1603: Yes), the search processing device 101 returns to step S1504 shown in FIG. On the other hand, when "j" is less than the number of words constituting the input sentence (step S1603: No), the search processing device 101 determines whether or not "i" is equal to or more than the number of words constituting the registered word (step S1603: No). Step S1604).

Here, when "i" is less than the number of words constituting the registered word (step S1604: No), the search processing device 101 returns to step S1505 shown in FIG. On the other hand, when "i" is equal to or greater than the number of words constituting the registered word (step S1604: Yes), the search processing device 101 returns to the step in which the matching process is called.

Further, when the search processing device 101 shifts from step S1506 shown in FIG. 15, “i” is set to “i = i + 1” (step S1605). Then, the search processing device 101 initializes "j" with "j = 0" (step S1606), and proceeds to step S1604.

As a result, the word divided from the input sentence and the word divided from the registered word can be compared, and the matching word can be registered in the word list of the attribute keyword corresponding to the attribute.

Next, a specific processing procedure of the search process of step S1405 shown in FIG. 14 will be described with reference to FIGS. 17 and 18.

17 and 18 are flowcharts showing an example of a specific processing procedure of the search process. In the flowchart of FIG. 17, first, the search processing device 101 initializes the refined match record storage list (step S1701). Next, the search processing device 101 selects an unselected record that has not been selected from the document management DB 220 (step S1702).

Next, the search processing device 101 selects an unselected attribute that is not selected from the attributes that characterize the document to be searched (step S1703). Next, the search processing device 101 refers to the search condition (or the attribute candidate table 800) created in step S1404 shown in FIG. 14, and is not selected among the registered words corresponding to the selected attribute. The selected registered word is selected as the registered word of the narrowing condition (step S1704).

In the following description, the record selected in step S1702 may be referred to as "target record", and the attribute selected in step S1703 may be referred to as "target attribute".

Then, the search processing device 101 determines whether or not the registered word of the selected narrowing-down condition and the attribute value of the target attribute of the target record match (step S1705). Here, when the registered word of the narrowing-down condition and the attribute value of the target record do not match (step S1705: No), the search processing device 101 proceeds to step S1707.

On the other hand, when the registered word of the narrowing down condition and the attribute value of the target record match (step S1705: Yes), the search processing device 101 stores the target record in the narrowing down matching record storage list (step S1706). Then, the search processing device 101 determines whether or not there is an unselected registered word among the registered words corresponding to the target attribute (step S1707).

Here, if there is an unselected registered word (step S1707: Yes), the search processing device 101 returns to step S1704. On the other hand, when there is no unselected registered word (step S1707: No), the search processing device 101 determines whether or not there is an unselected unselected attribute among the attributes that characterize the document to be searched (step). S1708).

Here, if there is an unselected attribute (step S1708: Yes), the search processing device 101 returns to step S1703. On the other hand, when there is no unselected attribute (step S1708: No), the search processing device 101 determines whether or not there is an unselected record that has not been selected from the document management DB 220 (step S1709).

Here, if there is an unselected record (step S1709: Yes), the search processing device 101 returns to step S1702. On the other hand, when there is no unselected record (step S1709: No), the search processing device 101 shifts to step S1801 shown in FIG.

In the flowchart of FIG. 18, first, the search processing device 101 initializes the search result storage list (step S1801). Next, the search processing device 101 selects an unselected record that has not been selected from the refined match record storage list (step S1802).

Then, the search processing device 101 refers to the search condition and determines whether or not the search keyword is included in the body information of the selected record (step S1803). Here, when the search keyword is not included (step S1803: No), the search processing device 101 shifts to step S1805.

On the other hand, when the search keyword is included (step S1803: Yes), the search processing device 101 stores the selected record in the search result storage list (step S1804). Then, the search processing device 101 determines whether or not there is an unselected record that has not been selected from the narrowed-down match record storage list (step S1805).

Here, if there is an unselected record (step S1805: Yes), the search processing device 101 returns to step S1802. On the other hand, when there is no unselected record (step S1805: No), the search processing device 101 returns to the step in which the search processing is called.

This makes it possible to narrow down the search to a set of documents having the attributes that the user wants, using a search method similar to the existing full-text search.

In the example of FIG. 17, the OR of the registered word corresponding to each attribute is taken to narrow down the documents to be searched, but the present invention is not limited to this. For example, the search processing device 101 may narrow down the documents to be searched by ANDing the registered words corresponding to each attribute.

Here, a specific example of the search condition when narrowing down the documents to be searched by taking the AND of the registered words corresponding to each attribute will be described.

FIG. 19 is an explanatory diagram showing an example of search conditions. In FIG. 19, the search condition 1900 includes a narrowing condition 1910 and a full text search condition 1920. The narrowing-down condition 1910 is a condition in which OR is taken between the registered words in one attribute and AND is taken between the registered words of each attribute. The full-text search condition 1920 is a condition for performing a full-text search using a search keyword.

When the search process of step S1405 shown in FIG. 14 is executed based on the search condition 1900, the search processing device 101 holds, for example, a refined match record storage list for each attribute as a separate list, and narrows down all attributes. The record stored in the match record storage list is used as the final refined match record.

As described above, according to the search processing device 101 according to the embodiment, for each attribute of the search target stored in advance in the storage unit 610 among the plurality of words received for the search for the search target. It can be determined whether or not there is a first word that matches or is similar to one or more associated words. Further, according to the search processing device 101, when it is determined that the first word exists, the search target group including the first word in the attribute associated with the word that matches or is similar to the first word is selected. Can be extracted. Then, according to the search processing device 101, based on the comparison result between the second word other than the first word included in the received plurality of words and the word included in the data of each of the extracted search target groups, the search processing device 101 is used. The search target can be specified from the search target group.

As a result, even if the input of the keyword is accepted without specifying the attribute, the search target in which the keyword is set for each attribute can be searched by reflecting the attribute. More specifically, for example, a keyword for narrowing down a plurality of words (words) included in an input sentence (attribute keyword) and a keyword for full-text search (search keyword) without the user having to consciously input the word (word). ) And can be classified. For this reason, it is possible to perform a full-text search after narrowing down the search target group having the attributes that the user wants, reducing noise (information not intended by the user) contained in the search results and making it easier for the user to find the information that the user wants. can do.

Further, according to the search processing device 101, in the attribute associated with a word that matches or is similar to the first word, a search target group including one or a plurality of words associated with the attribute is extracted. Can be done.

As a result, it is possible to extract a search target group that includes a registered word (keyword) associated with an attribute in advance in the attribute value, and it is possible to narrow down by attribute more effectively and reduce noise. For example, if a specific product name that actually exists is set as a registered word of the attribute "product name", the attribute "product name" can be narrowed down to a document group that is a specific product name.

Further, according to the search processing device 101, when there are a plurality of attributes associated with a word that matches or is similar to the first word, among the plurality of words received for each attribute of the plurality of attributes. The number of words (word length) that match or are similar to one or more words associated with each attribute can be calculated. Then, according to the search processing device 101, the attribute having the largest number of calculated words can be specified from the plurality of attributes, and the search target group including the first word can be extracted from the specified attributes. ..

As a result, from among the plurality of attribute candidates, the attribute in which the word included in the registered word is contained more in the input sentence can be selected as the attribute corresponding to the attribute keyword (first word). Therefore, when narrowing down the search target group, it is possible to make it easier to narrow down by attribute and reduce noise.

Further, according to the search processing device 101, when there are a plurality of attributes associated with a word that matches or is similar to the first word, each attribute of the plurality of attributes is associated with each attribute1. Or, among a plurality of words, the character string ratio occupied by words that match or are similar to the words included in the received multiple words is calculated, and the attribute having the maximum calculated character string ratio is specified from the plurality of attributes. be able to.

As a result, from among a plurality of attribute candidates, the attribute having a high ratio (filling rate) of the word string included in the input sentence among the registered words is set as the attribute corresponding to the attribute keyword (first word). Can be selected. Therefore, when narrowing down the search target group, it is possible to make it easier to narrow down by attribute and reduce noise.

Further, according to the search processing device 101, it is possible to output a specified search target for a plurality of received words. Further, according to the search processing device 101, it is possible to output a registered word (phrase) associated with an attribute associated with a word that matches or is similar to the first word together with the specified search target.

As a result, it is possible to provide search results with less noise. In addition, when displaying the search results, it is possible to present information that can identify the attributes used to narrow down the search results.

Further, according to the search processing device 101, when it is determined that the first word exists, the second word other than the first word included in the received plurality of words and the data of each of the plurality of search targets A search target group can be extracted from a plurality of search targets based on the comparison result with the included words. Then, according to the search processing device 101, it is possible to specify the search target including the first word in the attribute associated with the word that matches or is similar to the first word from the extracted search target group. it can.

As a result, multiple words included in the input sentence are classified into attribute keywords and search keywords, a full-text search is performed using the search keywords, and then a search with the attributes desired by the user is performed using the attribute keywords. The target group can be narrowed down.

From these facts, according to the search processing apparatus 101 according to the embodiment, in the document search, the attribute information can be automatically extracted from the input sentence (search sentence) input by the user, and the search condition can be optimized. .. As a result, it is possible to perform a search narrowed down to a set of documents having the attributes desired by the user by a search method such as an existing full-text search, and it is possible to improve convenience.

The search processing method described in the present embodiment can be realized by executing a program prepared in advance on a computer such as a personal computer or a workstation. This search processing program is recorded on a computer-readable recording medium such as a hard disk, flexible disk, CD-ROM, DVD, or USB memory, and is executed by being read from the recording medium by the computer. Further, the search processing program may be distributed via a network such as the Internet.

Further, the search processing device 101 described in the present embodiment can also be realized by a standard cell, an IC for a specific purpose such as a structured ASIC (Application Specific Integrated Circuit), or a PLD (Programmable Logic Device) such as an FPGA.

The following additional notes are further disclosed with respect to the above-described embodiment.

(Appendix 1) Among the plurality of words received for the search for the search target, the first word that matches or is similar to one or more words associated with each attribute of the search target stored in the storage unit in advance. Determine if the word exists and
When it is determined that the first word exists, a search target group including the first word in the attribute associated with the word matching or similar to the first word is extracted.
The search target is specified from the search target group based on the comparison result between the second word other than the first word included in the plurality of words and the word included in the data of each of the search target groups. To do
A search processing program characterized by having a computer execute processing.

(Appendix 2) The extraction process is
The description in Appendix 1, wherein a search target group including one or a plurality of words associated with the attribute is extracted from the attributes associated with the word matching or similar to the first word. Search processing program.

(Appendix 3) The extraction process is
When there are a plurality of attributes associated with a word that matches or is similar to the first word, each attribute of the plurality of attributes is associated with each of the received plurality of words. Calculate the number of words that match or are similar to one or more words
From the plurality of attributes, the attribute having the largest number of calculated words is specified.
The search processing program according to Appendix 1 or 2, wherein a search target group including the first word is extracted from the specified attribute.

(Appendix 4) The extraction process is
When there are a plurality of attributes associated with words that match or are similar to the first word, each attribute of the plurality of attributes is accepted from among one or more words associated with each attribute. Calculate the character string ratio occupied by words that match or are similar to the words included in the plurality of words.
From the plurality of attributes, the attribute having the maximum calculated character string ratio is specified.
The search processing program according to any one of Supplementary note 1 to 3, wherein a search target group including the first word is extracted from the specified attribute.

(Supplementary Note 5) The search processing program according to any one of Supplementary note 1 to 4, wherein the computer is made to execute a process of outputting the specified search target for the plurality of received words. ..

(Appendix 6) The one or more words associated with each attribute are one or more words divided from the words and phrases associated with each attribute.
The output process is
The search processing program according to Appendix 5, characterized in that, together with the specified search target, words and phrases associated with attributes associated with words that match or are similar to the first word are output.

(Appendix 7) When it is determined that the first word exists, the second word other than the first word included in the plurality of words and the word included in the data of each of the plurality of search targets Based on the comparison result, a search target group is extracted from the plurality of search targets, and the search target group is extracted.
From the extracted search target group, a search target including the first word is specified in an attribute associated with a word that matches or is similar to the first word.
The search processing program according to Appendix 1, wherein the processing is executed by the computer.

(Appendix 8) Among the plurality of words received for the search for the search target, the first word that matches or is similar to one or a plurality of words associated with each attribute of the search target stored in the storage unit in advance. Determine if the word exists and
When it is determined that the first word exists, a search target group including the first word in the attribute associated with the word matching or similar to the first word is extracted.
The search target is specified from the search target group based on the comparison result between the second word other than the first word included in the plurality of words and the word included in the data of each of the search target groups. To do
A search processing method characterized in that the processing is performed by a computer.

(Appendix 9) Among the plurality of words received for the search for the search target, the first word that matches or is similar to one or a plurality of words associated with each attribute of the search target stored in the storage unit in advance. Judgment unit that determines whether or not the word of
Extraction that extracts the search target group including the first word in the attribute associated with the word that matches or is similar to the first word when the determination unit determines that the first word exists. Department and
Based on the comparison result between the second word other than the first word included in the plurality of words and the word included in the data of each of the search target groups extracted by the extraction unit, the search target group A specific part that identifies the search target from among
A search processing device characterized by having.

101 Search processing device 110, 610 Storage unit 200 Search processing system 201 Client device 210 Network 220 Document management DB
230 Product attribute table 300 Bus 301 CPU
302 Memory 303 Disk drive 304 Disk 305 Communication I / F
306 Portable recording medium I / F
307 Portable recording medium 601 Reception unit 602 Judgment unit 603 Extraction unit 604 Specific unit 605 Output unit 710 Input text 800 Attribute candidate table 1200 Search screen 1900 Search conditions

Claims (7)

Among the plurality of words received for the search for the search target, there is a first word that matches or is similar to one or more words associated with each attribute of the search target stored in the storage unit in advance. Judge whether to do or not,
When it is determined that the first word exists, a search target group including the first word in the attribute associated with the word matching or similar to the first word is extracted.
The search target is specified from the search target group based on the comparison result between the second word other than the first word included in the plurality of words and the word included in the data of each of the search target groups. To do
A search processing program characterized by having a computer execute processing. The extraction process is
The first aspect of the present invention is to extract a search target group including one or a plurality of words associated with the attribute in an attribute associated with a word that matches or is similar to the first word. The search processing program described. The extraction process is
When there are a plurality of attributes associated with a word that matches or is similar to the first word, each attribute of the plurality of attributes is associated with each of the received plurality of words. Calculate the number of words that match or are similar to one or more words
From the plurality of attributes, the attribute having the largest number of calculated words is specified.
The search processing program according to claim 1 or 2, wherein a search target group including the first word is extracted from the specified attribute. The extraction process is
When there are a plurality of attributes associated with words that match or are similar to the first word, each attribute of the plurality of attributes is accepted from among one or more words associated with each attribute. Calculate the character string ratio occupied by words that match or are similar to the words included in the plurality of words.
From the plurality of attributes, the attribute having the maximum calculated character string ratio is specified.
The search processing program according to any one of claims 1 to 3, wherein a search target group including the first word is extracted from the specified attribute. The search processing program according to any one of claims 1 to 4, wherein the computer executes a process of outputting the specified search target for the plurality of received words. Among the plurality of words received for the search for the search target, there is a first word that matches or is similar to one or more words associated with each attribute of the search target stored in the storage unit in advance. Judge whether to do or not,
When it is determined that the first word exists, a search target group including the first word in the attribute associated with the word matching or similar to the first word is extracted.
The search target is specified from the search target group based on the comparison result between the second word other than the first word included in the plurality of words and the word included in the data of each of the search target groups. To do
A search processing method characterized in that the processing is performed by a computer. Among the plurality of words received for the search for the search target, there is a first word that matches or is similar to one or more words associated with each attribute of the search target stored in the storage unit in advance. A judgment unit that determines whether or not to do
Extraction that extracts the search target group including the first word in the attribute associated with the word that matches or is similar to the first word when the determination unit determines that the first word exists. Department and
Based on the comparison result between the second word other than the first word included in the plurality of words and the word included in the data of each of the search target groups extracted by the extraction unit, the search target group A specific part that identifies the search target from among
A search processing device characterized by having.

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