Patent Publication Number: US-2015081477-A1

Title: Search query analysis device, search query analysis method, and computer-readable recording medium

Description:
TECHNICAL FIELD 
     The present invention relates to a search query analysis device and a search query analysis method that enable search queries to be analyzed in order to uncover new applications of a given product, and a computer-readable recording medium storing a computer program for realizing the device and method. 
     BACKGROUND ART 
     An increasing number of users are utilizing EC (electronic commerce) sites or electronic shopping malls to purchase products following the popularization of the Internet in recent years. With such use of EC sites and the like to purchase products, or so-called online shopping, it is easy to find products using a search system, and thus the purchase of products through online shopping is expected to further increase from now on. 
     In order to make it easier for a user to be able to search for a product that he or she is looking for with online shopping, a system disclosed in Patent Document  1 , for example, recommends another search query related to the search query input by the user. Using this other recommended search query, even a user with a poor search technique can easily search for products that he or she wants. 
     With such online shopping through EC sites and the like, the user goes through the following steps, for example, to purchase a product. First, the user inputs the brand name or the like of the product that he or she wishes to purchase as a search query. The search system presents the user with products related to this input search query, and if the user likes one of products that are presented, he or she purchases that product. 
     Incidentally, in order to look for products suitable for a given application, the user sometimes inputs the application as a search query, rather than a brand name or the like. In this case, a typical search system extracts products whose description includes the application input by the user, and these extracted products are presented to the user. If one of the extracted products is suitable for the application that the user is looking for, the user purchases that product. 
     CITATION LIST 
     Patent Document 
     Patent Document 1: JP 2008-544377A 
     DISCLOSURE OF THE INVENTION 
     Problem to be Solved by the Invention 
     However, only applications envisaged by the manufacturer, retailer or the like of each product are included in the description of the product. Thus, even if a product could be used for the application that the user is looking for, a typical search system is not able to present that product to the user if the applications included in the description of that product differs from the application that the user is looking for. Since potential customers may, as a result, be overlooked with a typical search system, uncovering new applications of products is also important in order to gain potential customers. 
     In view of this, an exemplary object of the present invention is to provide a search query analysis device, a search query analysis method, and a computer-readable recording medium that enable search queries to be analyzed in order to uncover new applications of a given product. 
     Means for Solving the Problem 
     In order to attain the above object, a search query analysis device according to one aspect of the present invention includes a search query sorting unit that sorts a plurality of search queries input by a user into a plurality of search query groups in chronological order, and specifies a purchase search query group that includes a search query input immediately before a product purchase of the user and first search query groups input before the purchase search query group, among the plurality of search query groups, a keyword extraction unit that extracts a keyword group from a description of a purchased product purchased by the user, and a search query group extraction unit that computes a similarity between the first search query groups and the keyword group extracted by the keyword extraction unit, and extracts a first search query group whose similarity is less than a threshold. 
     Also, in order to attain the above object, a search query analysis method according to one aspect of the present invention includes the steps of (a) sorting a plurality of search queries input by a user into a plurality of search query groups in chronological order, and specifying a purchase search query group that includes a search query input immediately before a product purchase of the user and first search query groups input before the purchase search query group, among the plurality of search query groups, (b) extracting a keyword group from a description of a purchased product purchased by the user, and (c) computing a similarity between the first search query groups and the keyword group extracted in the step (b), and extracting a first search query group whose similarity is less than a threshold. 
     Furthermore, in order to attain the above object, a computer-readable recording medium according to one aspect of the present invention is a computer-readable recording medium storing a computer program for analyzing, by computer, a search query input by a user, the computer program including commands for causing the computer to execute the steps of (a) sorting a plurality of search queries input by a user into a plurality of search query groups in chronological order, and specifying a purchase search query group that includes a search query input immediately before a product purchase of the user and first search query groups input before the purchase search query group, among the plurality of search query groups, (b) extracting a keyword group from a description of a purchased product purchased by the user, and (c) computing a similarity between the first search query groups and the keyword group extracted in the step (b), and extracting a first search query group whose similarity is less than a threshold. 
     Effects of the Invention 
     As mentioned above, according to the present invention, search queries can be analyzed in order to uncover new applications of a product. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a block diagram showing a configuration of a search query analysis device according to an embodiment of the present invention. 
         FIG. 2  is a flowchart showing operations of the search query analysis device according to an embodiment of the present invention. 
         FIG. 3  is a diagram showing an example of search query information that is stored by an information storage unit according to an embodiment of the present invention. 
         FIG. 4  is a diagram showing an example of purchase information that is stored by the information storage unit according to an embodiment of the present invention. 
         FIG. 5  is a diagram showing an example of search query group information sorted by a search query sorting unit according to an embodiment of the present invention. 
         FIG. 6  is a diagram showing an example of various information that is acquired by a search query group extraction unit according to an embodiment of the present invention. 
         FIG. 7  is a diagram showing an example of various information that is acquired by a search query group distinguishing unit according to an embodiment of the present invention. 
         FIG. 8  is a diagram showing an example of various information that is acquired by the search query group distinguishing unit according to an embodiment of the present invention. 
         FIG. 9  is a block diagram showing the configuration of a computer that realizes the search query analysis device according to an embodiment of the present invention. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Embodiments 
     Hereinafter, a search query analysis device, a search query analysis method and a computer program according to embodiments of the present invention will be described, with reference to the drawings. 
     Search Query Analysis Device 
     Initially, the configuration of a search query analysis device according to the present embodiment will be described using  FIG. 1 .  FIG. 1  is a block diagram showing the configuration of the search query analysis device according to an embodiment of the present invention. 
     As shown in  FIG. 1 , in the present embodiment, a search query analysis device  1  is connected to a shopping site system  2  such as an EC (electronic commerce) site system or an electronic shopping mall system. The search query analysis device  1  analyzes search queries input from terminal devices  3  connected to the shopping site system  2  via a network  4  such as the Internet. The search query analysis device  1  according to the present embodiment is provided with a search query sorting unit  13 , a keyword extraction unit  12 , and a search query group extraction unit  14 . 
     The search query sorting unit  13  sorts a plurality of search queries input by a user into a plurality of search query groups in chronological order. The search query sorting unit  13  then specifies a purchase search query group that includes the search query input immediately before the user&#39;s product purchase and first search query groups input before the purchase search query group, among the plurality of sorted search query groups. 
     The keyword extraction unit  12  extracts a keyword group from the description of the purchased product purchased by the user. 
     The search query group extraction unit  14  computes the similarity between the first search query groups and the keyword group, and extracts a first search query group whose similarity is less than a threshold. 
     According to the above search query analysis device  1 , a first search query group whose similarity to a keyword group is low can be extracted. Since this extracted first search query group has low similarity to the keyword group contained in the description of the purchased product, it can be regarded as a candidate for a new application that is not contained in the description of the purchased product. In this way, the search query analysis device  1  according to the present embodiment is able to analyze search queries in order to uncover new applications of the purchased product. 
     Here, the configuration of the search query analysis device  1  will be described more specifically. As shown in  FIG. 1 , in the present embodiment, the search query analysis device  1  is further provided with an information storage unit  11  and a search query group distinguishing unit  15 , in addition to the search query sorting unit  13 , the keyword extraction unit  12  and the search query group extraction unit  14 . 
     The shopping site system  2  is provided with a search engine  21  and a purchase procedure processing unit  22 . 
     The search engine  21  searches for a product based on a search query received from the terminal device  3  connected via the network  4 . Also, the search engine  21  stores search query information in the information storage unit  11  for every search event. Note that the search query information includes user information specifying the user who performed the search, search date-time information and a search query. 
     The purchase procedure processing unit  22  executes purchase procedure processing when the user purchases a product from among the retrieved products. 
     When the purchase procedure processing unit  22  executes purchase procedure processing, the keyword extraction unit  12  detects the purchase event, and acquires the user information of the user who made the purchase and the purchase date-time information. Also, the keyword extraction unit  12  extracts a keyword group consisting of a plurality of keywords from the description of the product on the Web page on which the purchased product appears. 
     The keyword extraction unit  12  stores purchase information in the information storage unit  11 . Note that this purchase information includes user information specifying the user who purchased the product, purchase date-time information and a keyword group. 
     The information storage unit  11  stores the search query information from the search engine  21  and the purchase information from the keyword extraction unit  12 . 
     The search query sorting unit  13 , in the present embodiment, acquires the search query information and the purchase information that are stored in the information storage unit  11 . The search query sorting unit  13  then, for each user, computes the similarity between the search queries in chronological order, and sorts the search queries into a plurality of search query groups based on this similarity. 
     Also, the search query sorting unit  13  specifies a purchase search query group input immediately before the user&#39;s product purchase and first search query groups input before this purchase search query group, from among the plurality of search query groups. 
     The search query group extraction unit  14 , in the present embodiment, acquires the first search query groups from the search query sorting unit  13 , and acquires the purchase information from the information storage unit  11 . The search query group extraction unit  14  then computes the similarity between the first search query groups and the keyword group, and extracts a first search query group whose similarity is less than a threshold. 
     The search query group distinguishing unit  15  acquires the first search query group extracted by the search query group extraction unit  14  from the search query group extraction unit  14 , and distinguishes this acquired first search query group as being a target search query group or a non-target search query group. Note that “target search query group” refers to a search query group directed to searching for the purchased product among the first search query groups, and “non-target search query group” refers to a search query group not directed to searching for the purchased product among the first search query groups. 
     Also, the search group distinguishing unit  15 , in the case where the first search query group is the target search query group, notifies the first search query group to the retailer of the purchased product, the administrator of the shopping site system  2  or the like as a new application of the purchased product. 
     Operations of Search Query Analysis Device 
     Next, the operations of the search query analysis device according to an embodiment of the present invention will be described using  FIG. 2 , while taking  FIG. 1  into consideration as appropriate. Note that, in the present embodiment, since the search query analysis method is implemented by operating the search query analysis device  1 , the following description of the operations of the search query analysis device is given in place of description of the search query analysis method according to the present embodiment. 
       FIG. 2  is a flowchart showing operation procedures of the search query analysis device according to an embodiment of the present invention. 
     First, the terminal device  3 , upon receiving input of a search query that apparently refers to an application in order to look for a product suitable for a certain application, transmits the search query to the search engine  21  via the network  4 . The search engine  21  executes product search processing based on this search query. The search engine  21  then transmits the search query to the information storage unit  11  as search query information together with user information and search date-time information, every time there is such a search event. 
     As shown in  FIG. 2 , the information storage unit  11  stores the search query information received from the search engine  21  (step S 1 ). Note that the search query information that is stored in the information storage unit  11  includes, for example, user information  101 , search date-time information  102 , and a search query  103 , as shown in  FIG. 3 .  FIG. 3  is a diagram showing an example of search query information that is stored in the information storage unit  11  according to an embodiment of the present invention. 
     When the user purchases a product from among the products presented as search results in the shopping site system  2 , the purchase procedure processing unit  22  of the shopping site system  2  executes purchase procedure processing. The keyword extraction unit  12  of the search query analysis device  1  then detects that purchase event (step S 2 ). 
     Also, whenever a purchase event is detected, the keyword extraction unit  12  acquires user information and purchase date-time information relating to the purchase event, and extracts a keyword group from the description of the purchased product (step S 3 ). For example, the keyword extraction unit  12  is able to extract keywords by acquiring the description of the purchased product that appears on the Web page, and perform morphological analysis on this description. 
     The keyword extraction unit  12  then stores purchase information including the user information, the purchase date-time information and the keyword group in the information storage unit  11  (step S 4 ). Note that the purchase information that is stored in the information storage unit  11  includes user information  201 , purchase date-time information  202  and keyword group  203 , as shown in  FIG. 4 .  FIG. 4  is a diagram showing an example of purchase information that is stored in the information storage unit  11  according to an embodiment of the present invention. 
     The processing of the above steps S 1  to S 4  is repeatedly executed for a preset period, and search query information and purchase information are thereby stored in the information storage unit  11 . 
     Once storing of search query information and purchase information has been performed for a predetermined period, next the search query sorting unit  13  sorts the search queries stored in the information storage unit  11  into a plurality of search query groups (step S 5 ). 
     Specifically, first, the search query sorting unit  13  acquires the search query information and the purchase information that are stored in the information storage unit  11 . The search query sorting unit  13  then sorts the search queries into a plurality of search query groups in chronological order for each user, based on the user information and search date-time information associated with the search queries. Specifically, the search query sorting unit  13  computes the similarity between the search queries in chronological order, and separates the search queries at the point at which this similarity falls to less than or equal to a threshold. That is, the search query sorting unit  13  collects similar search queries among the search queries arranged in chronological order as one search query group. 
     For example, in the case where search query information such as shown in  FIG. 3  is acquired, the search query sorting unit  13  computes the similarity between the search query that is at the top, and the search query that is second from the top. The search query sorting unit  13  then judges that this similarity exceeds the threshold, and collects the search query that is at the top and the search query that is second from the top as one search query group. 
     Similarly, the search query sorting unit  13  computes the similarity between the search query that is second from the top and the search query that is third from the top. The search query sorting unit  13  then judges that this similarity is less than or equal to the threshold, and sorts the search query that is second from the top and the search query that is third from the top into different search query groups. 
     Next, the search query sorting unit  13  computes the similarity between the search query that is third from the top and the search query that is fourth from the top. The search query sorting unit  13  judges that this similarity exceeds the threshold, and collects the search query that is third from the top and the search query that is fourth from the top as one search query group. As described above, the search query sorting unit  13  sorts the search queries in search query information such as shown in  FIG. 3  into two search query groups. 
     Search query groups  30  thus sorted by the search query sorting unit  13  are, as shown in  FIG. 5 , associated with user information  301 , a search start date-time  302 , and a search end date-time  303 . Note that  FIG. 5  is a diagram showing exemplary search query group information sorted by the search query sorting unit  13  according to an embodiment of the present invention. 
     Note that as the method of computing the similarity between search queries, the similarity can be computed based on the number of Web pages that are included in both search results, as a result of searches performed using search queries that are adjacent in chronological order, for example. 
     Also, the search query sorting unit  13  specifies a purchase search query group that includes the search query input immediately before the user purchased the product and first search query groups input before the purchase search query group, among the sorted search query groups. 
     For example, the search query sorting unit  13  acquires the purchase information shown in  FIG. 4 , and, based on the purchase date-time information  202  in this purchase information, specifies the search query group that is second from the top in  FIG. 5  as the purchase search query group, and specifies the search query group that is at the top in  FIG. 5  as a first search query group. 
     Next, the search query group extraction unit  14  extracts a first search query group to serve as a candidate for a new application of the purchased product (hereinafter “new application candidate query group”), from the first search query groups specified by the search query sorting unit  13  (step S 6 ). 
     Specifically, the search query group extraction unit  14  acquires various information such as shown in  FIG. 6 . That is, the search query group extraction unit  14  acquires first search query group information from the search query sorting unit  13 , and acquires purchase information from the information storage unit  11 .  FIG. 6  shows an example of various information that is acquired by the search query group extraction unit according to an embodiment of the present invention, the information that is at the top being first search query group information, and the information that is second from the top being purchase information. 
     Next, the search query group extraction unit  14  computes the similarity between the first search query groups and the keyword group extracted at step S 3 . The search query group extraction unit  14  then extracts a first search query group whose similarity to the keyword group is less than or equal to a threshold as a candidate for a new application of the purchased product, that is, as a new application candidate query group. 
     Note that in the case where there are a plurality of first search query groups, the search query group extraction unit  14  computes the similarity to the keyword group sequentially from the first search query group whose search date-time is closest to the purchase date-time. 
     The search query group extraction unit  14  is able to compute the similarity between a first search query group and the keyword group as follows, for example. 
     First, the search query group extraction unit  14  generates a keyword vector using a TF-IDF value, from the keywords constituting the first search query group. Similarly, the search query group extraction unit  14  generates a keyword vector using a TF-IDF value, from each keyword constituting the keyword group extracted at step S 3 . The search query group extraction unit  14  is then able to compute the similarity between the first search query group and the keyword group, by computing the inner product of the generated keyword vectors. 
     Next, the search query group distinguishing unit  15  acquires the first search query group (new application candidate query group) to serve as a candidate for a new application from the search query group extraction unit  14 , and determines whether this new application candidate query group is a target search query group directed to searching for the purchased product (step S 7 ). 
     This search query group distinguishing unit  15  is able to distinguish the new application candidate query group as being a target search query group directed to searching for the purchased product or a non-target search query group not directed to searching for the purchased product, with the following method, for example. 
     For example, the search query group distinguishing unit  15  acquires various information such as shown in  FIG. 7 . That is, the search query group distinguishing unit  15  acquires information on the new application candidate query group extracted by the search query group extraction unit  14 . Also, the search query group distinguishing unit  15  acquires information on a second search query group from the search query sorting unit  13 .  FIG. 7  is a diagram showing an example of the various information that is acquired by the search query group distinguishing unit according to an embodiment of the present invention, the information that is at the top being information on the new application candidate query group, and the information that is second from the top being information on the second search query group. Also, “second search query group” refers to a search query group input after the purchase search query group, among the search query groups sorted by the search query sorting unit  13 . 
     The search query group distinguishing unit  15  then determines whether the new application candidate query group acquired as a candidate for a new application is similar to the second search query group. This similarity determination can be performed by, for example, generating a keyword vector for each of the search query groups, and deriving the similarity from the inner product of the keyword vectors, as described above. 
     In the case where the above similarity exceeds the threshold, the search query group distinguishing unit  15  determines that the first search query group and the second search query group are similar, and specifies that this new application candidate query group that is similar to the second search query group is a non-target search query group (No at step S 7 ). That is, search queries input by the same user after the product purchase are highly likely to not be search queries input for the purpose of searching for the purchased product. It can thus be assumed that a new application candidate query group that is similar to a second search query group input after the product purchase is a non-target search query group. 
     The search query group distinguishing unit  15  is alternatively able to distinguish the new application candidate query group as being a target search query group or a non-target search query group with the following method. 
     First, the search query group distinguishing unit  15  acquires various information such as shown in  FIG. 8 . That is, the search query group distinguishing unit  15  acquires the new application candidate query group extracted by the search query group extraction unit  14 . Also, the search query group distinguishing unit  15  acquires a purchase search query group used when another user purchased another product from the search query sorting unit  13 .  FIG. 8  is a diagram showing an example of information that is acquired by the search query group distinguishing unit according to an embodiment of the present invention, with the information that is at the top being information on the new application candidate query group, the information that is second from the top being information on a purchase search query group and the information that is third from the top being purchase information. 
     The search query group distinguishing unit  15  then computes the similarity between the purchase search query group of the other user and the new application candidate query group serving as a candidate for a new application. Note that the same method of computing the similarity as the method described above can be used in this case. The search query group distinguishing unit  15  judges that the new application candidate query group is a non-target search query group, in the case where this computed similarity exceeds a threshold (No at step S 7 ). 
     When the search query group distinguishing unit  15  judges that the new application candidate query group is not a target search query group by methods such as described above (No at step S 7 ), the search query analysis device  1  ends the application uncovering processing with respect to the target purchased product of the target user. 
     On the other hand, the search query group distinguishing unit  15 , upon having judged that the new application candidate query group is a target search query group (Yes at step S 7 ), notifies the retailer of the purchased product, the administrator of the shopping site system  2  or the like that this new application candidate query group is a new application of the purchased product (step S 8 ). 
     In the case where other purchase information is also stored in the information storage unit  11 , the search query analysis device  1  executes the processing of steps S 5  to S 8  for every purchased product to uncover new applications. Also, in the case where the search query group information and purchase information for a plurality of users are stored in the information storage unit  11 , the search query analysis device  1  executes the processing of steps S 5  to S 8  for every purchased product of each user to uncover new applications. 
     Computer Program 
     A computer program according to an embodiment of the present invention can be a computer program that causes a computer to perform steps S 1  to S 8 . The search query analysis device and the search query analysis method according to the present embodiment can be realized by installing this computer program in a computer and executing the installed computer program. In this case, a CPU (Central Processing Unit) of the computer functions and performs processing as the search query sorting unit  13 , the search query group extraction unit  14 , the keyword extraction unit  12  and the search query group distinguishing unit  15 . 
     The first search query group (target search query group) that is ultimately extracted according to the present embodiment as described above is a search query group directed to searching for the purchased product, despite not being similar to the keyword group extracted from the description of the purchased product. This first search query group (target search query group) can thus be regarded as a new application of the product purchased by the user. Therefore, the present embodiment enables a new application of the purchased product to be uncovered. 
     Here, a computer that realizes the search query analysis device  1  by executing the computer program according to the embodiment will be described using  FIG. 9 .  FIG. 9  is a block diagram showing an example of a computer that realizes the search query analysis device  1  according to an embodiment of the present invention. 
     As shown in  FIG. 9 , the computer  110  is provided with a CPU  111 , a main memory  112 , a storage device  113 , an input interface  114 , a display controller  115 , a data reader/writer  116 , and a communication interface  117 . These constituent elements are connected to each other via a bus  121  in a manner that enables data communication. 
     The CPU  111  implements various operations by expanding the computer program (codes) according to the present embodiment stored in the storage device  113  in the main memory  112 , and executing these codes in a predetermined order. The main memory  112  is, typically, a volatile storage device such as DRAM (Dynamic Random Access Memory). Also, the computer program according to the present embodiment is provided in a state of being stored on a computer-readable recording medium  120 . Note that the computer program according to the present embodiment may also be circulated on the Internet connected via the communication interface  117 . 
     Also, apart from a hard disk, specific examples of the storage device  113  include a semiconductor memory device such as a flash memory. The input interface  114  mediates data communication between the CPU  111  and an input device  118  such as a keyboard and a mouse. The display controller  115  is connected to a display device  119  and controls display on the display device  119 . The data reader/writer  116  mediates data communication between the CPU  111  and the recording medium  120 , and executes reading out of the computer program from the recording medium  120 , and writing of the results of processing by the computer  110  to the recording medium  120 . The communication interface  117  mediates data communication between the CPU  111  and other computers. 
     Also, specific examples of the recording medium  120  include general-purpose semiconductor memory devices such as CF (Compact Flash (registered trademark)) and SD (Secure Digital), magnetic storage media such as a flexible disk (Flexible Disk) and optical storage media such as CD-ROM (Compact Disk Read Only Memory). 
     Although embodiments of the present invention have been described above, the invention is not limited to these embodiments, and various modifications can be made without deviating from the gist of the invention. 
     For example, in the search query analysis device  1 , the search query group distinguishing unit  15  may further have a function of extracting the user information of a user who has input at least a predetermined number of first search query groups that were distinguished as being the target search query group, and specifying this user as a lead user. Note that “lead user” in this specification refers to a user who devises a way of using an existing product to serve his or her purpose if a product that can directly serve his or her purpose is not available. 
     Also, the abovementioned embodiments can be partially or wholly represented by supplementary notes 1 to 21 described below, but are not limited to the following description. 
     Supplementary Note 1 
     A search query analysis device includes a search query sorting unit that sorts a plurality of search queries input by a user into a plurality of search query groups in chronological order, and specifies a purchase search query group that includes a search query input immediately before a product purchase of the user and first search query groups input before the purchase search query group, among the plurality of search query groups, a keyword extraction unit that extracts a keyword group from a description of a purchased product purchased by the user, and a search query group extraction unit that computes a similarity between the first search query groups and the keyword group extracted by the keyword extraction unit, and extracts a first search query group whose similarity is less than a threshold. 
     Supplementary Note 2 
     With the search query analysis device according to supplementary note 1, the search query sorting unit sorts the plurality of search queries into the plurality of search query groups based on a similarity between the search queries. 
     Supplementary Note 3 
     The search query analysis device according to supplementary note 1 further includes a search query group distinguishing unit for distinguishing the first search query group extracted by the search query group extraction unit as being a target search query group directed to searching for the purchased product or a non-target search query group not directed to searching for the purchased product. 
     Supplementary Note 4 
     With the search query analysis device according to supplementary note 3, the search query group distinguishing unit computes a similarity between the first search query group extracted by the search query group extraction unit and a second search query group input after the purchase search query group, and judges the first search query group to be the non-target search query group if the similarity is greater than a threshold. 
     Supplementary Note 5 
     With the search query analysis device according to supplementary note 3, the search query group distinguishing unit computes a similarity between the first search query group extracted by the search query group extraction unit and a purchase search query group used when another product different from the purchased product was purchased by another user different from the user, and judges that the first search query group is the non-target search query group if the similarity is greater than or equal to a threshold. 
     Supplementary Note 6 
     With the search query analysis device according to supplementary note 3, the search query group distinguishing unit extracts user information of a user who has input at least a predetermined number of first search query groups that were distinguished as being the target search query group. 
     Supplementary Note 7 
     With the search query analysis device according to supplementary note 1, the search query group extraction unit, in a case where there are a plurality of first search query groups, computes the similarity to the keyword group sequentially from the first search query group whose search date-time is closest to a purchase date-time. 
     Supplementary Note 8 
     A search query analysis method includes the steps of (a) sorting a plurality of search queries input by a user into a plurality of search query groups in chronological order, and specifying a purchase search query group that includes a search query input immediately before a product purchase of the user and first search query groups input before the purchase search query group, among the plurality of search query groups, (b) extracting a keyword group from a description of a purchased product purchased by the user, and (c) computing a similarity between the first search query groups and the keyword group extracted in the step (b), and extracting a first search query group whose similarity is less than a threshold. 
     Supplementary Note 9 
     With the search query analysis method according to supplementary note 8, in the step (a), the plurality of search queries are sorted into the plurality of search query groups based on a similarity between the search queries. 
     Supplementary Note 10 
     The search query analysis method according to supplementary note 8 further includes the step of (d) distinguishing the first search query group extracted in the step (c) as being a target search query group directed to searching for the purchased product or a non-target search query group not directed to searching for the purchased product. 
     Supplementary Note 11 
     With the search query analysis method according to supplementary note 10, in the step (d), a similarity between the first search query group extracted in the step (c) and a second search query group input after the purchase search query group is computed, and the first search query group is judged to be the non-target search query group if the similarity is greater than a threshold. 
     Supplementary Note 12 
     With the search query analysis method according to supplementary note 10, in the step (d), a similarity between the first search query group extracted in the step (c) and a purchase search query group used when another product different from the purchased product was purchased by another user different from the user is computed, and the first search query group is judged to be the non-target search query group if the similarity is greater than or equal to a threshold. 
     Supplementary Note 13 
     With the search query analysis method according to supplementary note 10, in the step (d), user information of a user who has input at least a predetermined number of first search query groups that were distinguished as being the target search query group is extracted. 
     Supplementary Note 14 
     With the search query analysis method according to supplementary note 8, in the step (c), in a case where there are a plurality of first search query groups, the similarity to the keyword group is computed sequentially from the first search query group whose search date-time is closest to a purchase date-time. 
     Supplementary Note 15 
     A computer-readable recording medium stores a computer program for analyzing, by computer, a search query input by a user, the computer program including commands for causing the computer to execute the steps of (a) sorting a plurality of search queries input by a user into a plurality of search query groups in chronological order, and specifying a purchase search query group that includes a search query input immediately before a product purchase of the user and first search query groups input before the purchase search query group, among the plurality of search query groups, (b) extracting a keyword group from a description of a purchased product purchased by the user, and (c) computing a similarity between the first search query groups and the keyword group extracted in the step (b), and extracting a first search query group whose similarity is less than a threshold. 
     Supplementary Note 16 
     With the computer-readable recording medium according to supplementary note 15, in the step (a), the plurality of search queries are sorted into the plurality of search query groups based on a similarity between the search queries. 
     Supplementary Note 17 
     With the computer-readable recording medium according to supplementary note 15, the computer program further includes a command for causing the computer to execute the step of (d) distinguishing the first search query group extracted in the step (c) as being a target search query group directed to searching for the purchased product or a non-target search query group not directed to searching for the purchased product. 
     Supplementary Note 18 
     With the computer-readable recording medium according to supplementary note 17, in the step (d), a similarity between the first search query group extracted in the step (c) and a second search query group input after the purchase search query group is computed, and the first search query group is judged to be the non-target search query group if the similarity is greater than a threshold. 
     Supplementary Note 19 
     With the computer-readable recording medium according to supplementary note 17, in the step (d), a similarity between the first search query group extracted in the step (c) and a purchase search query group used when another product different from the purchased product was purchased by another user different from the user is computed, and the first search query group is judged to be the non-target search query group if the similarity is greater than or equal to a threshold. 
     Supplementary Note 20 
     With the computer-readable recording medium according to supplementary note 17, in the step (d), user information of a user who has input at least a predetermined number of first search query groups that were distinguished as being the target search query group is extracted. 
     Supplementary Note 21 
     With the computer-readable recording medium according to supplementary note 15, in the step (c), in a case where there are a plurality of first search query groups, the similarity to the keyword group is computed sequentially from the first search query group whose search date-time is closest to a purchase date-time. 
     Although the present invention has been described above with reference to embodiments, the invention is not limited to these embodiments. A person skilled in the art will appreciate that the configuration and details of the invention can be variously modified within the scope of the invention. 
     This application claims priority from Japanese Patent Application No. 2012-096400 filed on Apr. 20, 2012, the entire disclosure of which is herein incorporated by reference. 
     INDUSTRIAL APPLICABILITY 
     According to the present invention as described above, search queries can be analyzed in order to uncover a new application of a product. The present invention is thus useful in shopping site systems and the like. 
     DESCRIPTION OF REFERENCE NUMERALS 
     
         
           1  Search query analysis device 
           12  Keyword extraction unit 
           13  Search query sorting unit 
           14  Search query group extraction unit 
           15  Search query group distinguishing unit 
           110  Computer 
           111  CPU 
           112  Main memory 
           113  Storage device 
           114  Input interface 
           115  Display controller 
           116  Data reader/writer 
           117  Communication interface 
           118  Input device 
           119  Display device 
           120  Recording medium 
           121  Bus