Information processing device, information processing method, and information processing program

Abstract

To identify an appropriate space delimiter position of a search query.SOLUTION: An information processing device comprises: a generation unit which generates a character string indicated by a search query entered by a user by deleting a space delimiter included in the search query; a classification unit which classifies the search query on the basis of the character string generated by the generation unit; and an identification unit which identifies a space delimiter position in the character string generated from each search query on the basis of the number of times each of the search queries classified into the same group was entered.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] Conventionally, there are known techniques for providing assistance regarding a search query, which is a character string entered by a user when performing an Internet search, etc. One example of such a technique is a technique that, when an entered search query corresponds to a character string that could be entered as a typographical error, converts the entered search query into a character string associated with the character string that could be entered as a typographical error, and searches for information using the converted character string as the search query. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6529456 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-mentioned techniques may not be able to identify appropriate space delimiter positions in a search query.

[0005] For example, the above-mentioned technology merely converts typographical errors into corresponding correct strings, and cannot be said to be able to identify the appropriate space delimiter positions in a search query.

[0006] The present application has been made in view of the above, and aims to identify appropriate space delimiter positions in a search query. [Means for solving the problem]

[0007] The information processing device according to the present application is characterized by having a generation unit that generates a string indicated by a search query entered by a user by deleting space separators included in the search query, a classification unit that classifies the search queries based on the strings generated by the generation unit, and an identification unit that identifies the position of space separators in the strings generated from each search query based on the number of times each search query classified into the same group has been entered. [Effects of the Invention]

[0008] According to one aspect of the embodiment, it is possible to provide an effect of identifying appropriate space delimiter positions in a search query. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. [Figure 2] FIG. 2 is a diagram showing an example of the configuration of the information processing device 10 according to the embodiment. [Figure 3] FIG. 3 is a diagram showing an example of the search query information database 31 according to the embodiment. [Figure 4] FIG. 4 is a diagram showing an example of the group information database 32 according to the embodiment. [Figure 5] FIG. 5 is a flowchart illustrating an example of a procedure for information processing according to the embodiment. [Figure 6] FIG. 6 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 10. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an information processing device, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited to these embodiments. In the following embodiments, the same components are denoted by the same reference numerals, and duplicated descriptions will be omitted.

[0011] 1. Embodiment Information processing implemented by an information processing device or the like according to this embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of information processing according to the embodiment. Note that in Fig. 1, it is assumed that the information processing according to the embodiment is implemented by an information processing device 10, which is an example of the information processing device according to the present application.

[0012] As shown in Fig. 1, an information processing system 1 according to the embodiment includes an information processing device 10 and a user terminal 100. The information processing device 10 and the user terminal 100 are connected to each other via a network N (see Fig. 2, for example) so as to be able to communicate with each other via a wired or wireless connection. The network N is, for example, a wide area network (WAN) such as the Internet. Note that the information processing system 1 shown in Fig. 1 may include a plurality of information processing devices 10 and a plurality of user terminals 100.

[0013] 1 is an information processing device that performs information processing, and is realized by, for example, a server device or a cloud system. For example, the information processing device 10 provides a search service and manages information indicating a history of search queries entered by users in the search service in a storage unit of the information processing device 10. Then, the information processing device 10 identifies appropriate space delimiter positions in the search query based on the search query history.

[0014] The services provided by the information processing device 10 may be, for example, a search service, a shopping service, a payment service, a route search service, a map provision service, a travel service, a restaurant introduction service, a weather forecast service, a schedule management service, a news provision service, an auction service, a video content distribution service, a financial transaction (stock trading, etc.) service, etc.

[0015] Here, conventionally, when a user inputs a search query into a search service, etc., there are cases where spaces are not entered into the search query due to input errors by the user, or where the search query is entered by voice input, and therefore spaces are not entered. In such cases, a method can be considered in which spaces are automatically entered into the search query entered by the user using morphological analysis technology. However, when such a method is used, for example, if the search query includes a recently created proper noun (e.g., the name of content such as a manga, movie, or song), the proper noun may be excessively separated.

[0016] Therefore, the information processing device etc. of this embodiment executes the following information processing for the purpose of identifying appropriate space delimiter positions in a search query.

[0017] The user terminal 100 shown in Fig. 1 is an information processing device used by a user. The user terminal 100 is realized, for example, by a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), etc. In the example shown in Fig. 1, the user terminal 100 is a smartphone used by a user.

[0018] An example of information processing performed by information processing device 10 will be described below with reference to FIG. 1. In the following description, user terminal 100 will be described as user terminals 100-1 to 100-N (N is any natural number) depending on the user using user terminal 100. For example, user terminal 100-1 is the user terminal 100 used by a user (user U1) identified by user ID "UID#1." In the following description, user terminals 100-1 to 100-N will be referred to as user terminal 100 when there is no particular distinction between them. In the following description, user terminal 100 may be considered to be the same as the user. That is, in the following description, user U1 can also be read as user terminal 100-1.

[0019] First, the information processing device 10 generates a character string indicated by a search query entered by a user in a search service (step S1). For example, the information processing device 10 generates the character string by deleting space delimiters included in the search query.

[0020] To give a specific example, the information processing device 10 generates a character string "AABBCC" from the search query "AA BB CC" by deleting the space separator between "AA" and "BB" and the space separator between "BB" and "CC" in the search query "AA BB CC." Also, the information processing device 10 generates a character string "AABBCC" from the search query "AA BBCC" by deleting the space separator between "AA" and "BBCC" in the search query "AA BBCC." Note that since there is no space separator in the search query "AABBCC," the information processing device 10 generates a character string "AABBCC" that directly represents the search query "AABBCC."

[0021] Next, the information processing device 10 classifies the search queries based on the character strings generated from the search queries (step S2). For example, the information processing device 10 classifies search queries that have matching character strings after removing spaces into the same group. To give a specific example, the information processing device 10 classifies the search queries "AABBCC," "AA BB CC," and "AA BBCC" into group #1 because the character string generated from each of the search queries is "AABBCC." Furthermore, the information processing device 10 classifies the search queries "DDEEFF," "DDEE FF," and "DD EE FF" into group #2 because the character string generated from each of the search queries is "DDEEFF."

[0022] Next, the information processing device 10 identifies the positions of space separators in the character string based on the search query that has been most frequently entered by users in the search service among the search queries classified into the same group (step S3). For example, since the search query "AA BB CC" has been most frequently entered in group #1, the information processing device 10 identifies that the appropriate positions of space separators in the character string "AABBCC" are between "AA" and "BB" and between "BB" and "CC".

[0023] Furthermore, for example, since the search query "DDEE FF" is input the most frequently in group #2, the information processing device 10 determines that the appropriate space delimiter position for the character string "DDEEFF" is between "DDEE" and "FF."

[0024] Next, the information processing device 10 performs training of a model that, when a character string is input, adds a space separator or deletes a space separator based on the position of the space separator in the character string identified in step S3, and outputs a character string from which the space separator is added or deleted (step S4). For example, when a search query entered by a user in a search service is input, the information processing device 10 performs training of a model that, when a search query is input by a user, adds a space separator to the search query or deletes a space separator present in the search query, and outputs a character string from which the space separator present in the search query is deleted.

[0025] In the information processing device 10, the generation and learning of the model may be performed using various conventional techniques related to machine learning, as appropriate. For example, the generation of the model may be performed using a technique related to supervised learning machine learning, such as SVM (Support Vector Machine). The generation of the model may also be performed using a technique related to unsupervised learning machine learning. The generation of the model may also be performed using a deep learning technique. The generation of the model may also be performed using various deep learning techniques, such as DNN (Deep Neural Network), RNN (Recurrent Neural Network), and CNN (Convolutional Neural Network), as appropriate. The above descriptions regarding the generation and learning of the model are merely examples, and the generation of the model may also be performed using a learning method selected as appropriate depending on the obtainable information, etc.

[0026] Next, the information processing device 10 receives a search query entered by a user in the search service from the user terminal 100 (step S5). Next, the information processing device 10 edits the search query entered by the user using the positions of the space separators identified in step S3 and the model trained in step S4, and provides search results based on the edited search query to the user terminal 100 (step S6). For example, if user U1 enters the search query "AA BBCC" (in other words, if the user enters a search query that would be classified as group #1 if the space separators were deleted), the information processing device 10 edits the search query to "AA BB CC" and provides search results based on the edited search query. Also, if user U2 enters the search query "DD EE FF" (in other words, if the user enters a search query that would be classified as group #2 if the space separators were deleted), the information processing device 10 edits the search query to "DDEE FF" and provides search results based on the edited search query.

[0027] Furthermore, if user U3 enters a search query (e.g., "GG HHII") indicating the string "GGHHII" without identifying the appropriate space separator, the information processing device 10 inputs the search query into the model and provides search results based on the output string "GGHH II."

[0028] Next, the information processing device 10 acquires behavioral information relating to the user's behavior after the search results have been provided from the user terminal 100 (step S7). For example, the information processing device 10 acquires behavioral information of the user U3 to whom the search results based on the character string "GGHH II" output from the model have been provided from the user terminal 100-3. As a specific example, the information processing device 10 acquires behavioral information indicating whether or not the user U3 selected the content provided as the search result based on "GGHH II".

[0029] Next, the information processing device 10 retrains the model based on the behavioral information of the user (step S8). For example, if the behavioral information of user U3 indicates that user U3 selected content provided as a search result based on "GGHH II", the information processing device 10 trains the model using the edited string "GGHH II" of the string "GGHHII" as a positive example. On the other hand, if the behavioral information of user U3 indicates that user U3 did not select content provided as a search result based on "GGHH II", the information processing device 10 trains the model using the edited string "GGHHII" of the string "GGHH II" as a negative example.

[0030] As described above, the information processing device 10 according to the embodiment identifies the position of a space separator in the character string indicated by each search query based on the search query most frequently entered by users among the search queries classified into the same group. In other words, the information processing device 10 according to the embodiment can identify the appropriate position of a space separator in the search query.

[0031] [2. Other processing examples] The above-described process is merely an example, and the information processing device 10 may perform various processes using various information. In this regard, examples are listed below.

[0032] [2-1. Identifying space separators] In the example of FIG. 1, the information processing device 10 may calculate the proportion of times each search query is input within a group, and identify appropriate space delimiter positions in a character string based on the position of the space delimiter of the search query with the highest proportion.

[0033] Furthermore, the information processing device 10 may identify the positions of space delimiters in the character string based on the search query that has been input by the largest number of unique users among the search queries classified into the same group.

[0034] Furthermore, the information processing device 10 may identify the positions of space delimiters in the character string based on the search query that has been input by the largest number of unique browsers among the search queries classified into the same group.

[0035] Furthermore, the information processing device 10 may identify the positions of space separators in a character string based on the number of times that content indicating search results for each search query classified into the same group has been selected. For example, the information processing device 10 identifies the positions of space separators in a character string based on the search query that, among the search queries classified into the same group, has the most number of times that content provided to users as search results has been selected (e.g., CTR (Click Through Rate)).

[0036] Furthermore, the information processing device 10 may identify the positions of space separators in a character string based on the number of conversions of advertising content corresponding to each search query classified into the same group. For example, the information processing device 10 identifies the positions of space separators in a character string based on the search query with the highest number of times (CVR (Conversion Rate) or the like) that advertising content provided to users as search results was selected among the search queries classified into the same group.

[0037] The information processing device 10 may combine a plurality of the above processes to identify appropriate space delimiter positions in a character string. For example, the information processing device 10 may identify appropriate space delimiter positions in a character string based on the number of times each search query classified into the same group was input, the ratio at which each search query was input within the group, the number of unique users who input each search query, the number of unique browsers that input each search query, the number of times content showing search results for each search query was selected, the number of conversions of advertising content corresponding to each search query, etc.

[0038] [2-2. When there are multiple search queries entered that exceed the specified threshold] In the example of FIG. 1, if there are multiple search queries classified into the same group that have been entered more than a predetermined threshold number of times (in other words, there are multiple search queries that have been entered by users at similar frequencies), the information processing device 10 may identify the positions of space separators in the character string based on the search query with the most space separators. For example, if the threshold for the number of entries is set to "100," group #2 includes the search queries "DDEE FF" and "DD EE FF." In such a case, the information processing device 10 identifies the positions of space separators in the character string "DDEEFF" based on the search query "DD EE FF" that has the most space separator positions.

[0039] Note that, when there are multiple search queries classified into the same group that have been entered a predetermined number of times or more, the information processing device 10 may identify the positions of space separators in the character string based on the search query with the fewest number of space separators. For example, the information processing device 10 identifies the positions of space separators in the character string "DDEEFF" based on the search query "DDEE FF" with the fewest positions of space separators out of the search queries "DDEE FF" and "DD EE FF".

[0040] When there are multiple search queries classified into the same group whose input count is equal to or exceeds a predetermined threshold, the information processing device 10 may identify the positions of space separators in the character string based on search queries extracted based on the number of times each substring separated by a space is input. For example, the information processing device 10 tallies the input counts of the partial search queries "DD," "EE," and "DDEE" included in the search queries "DDEE FF" and "DD EE FF" (in other words, partial search queries corresponding to parts of the search queries "DDEE FF" and "DD EE FF" that have different space separator positions). Then, when the input count of the partial search query "DDEE" is greater than the input count of the partial search queries "DD" and "EE," the information processing device 10 identifies the positions of space separators in the character string "DDEEFF" based on the search query "DDEE FF." On the other hand, if the number of times either the partial search query "DD" or "EE" is entered is greater than the number of times the partial search query "DDEE" is entered, the information processing device 10 determines the position of the space separator in the string "DDEEFF" based on the search query "DD EE FF".

[0041] [2-3. When a single search query can be classified into multiple groups] In the example of FIG. 1, if a search query can be classified into multiple groups, the information processing device 10 may classify the search query based on the number of times the search query is input and the number of times each search query classified into the multiple groups is input. For example, if a search query can be classified into multiple groups when part of the search query is converted into synonyms or similar words using a thesaurus, the information processing device 10 classifies the search query into one of the possible groups in which the difference between the number of times the search query is input (e.g., the average number of times the search query is input) and the number of times the search query is input is less than a predetermined threshold. Furthermore, if a search query can be classified into multiple groups, the information processing device 10 classifies the search query into one of the possible groups in which the difference between the number of times the search query is input and the number of times the search query is input is equal to or greater than a predetermined threshold.

[0042] [2-4. About the model] In the example of Figure 1, the information processing device 10 may separately generate and train a model (hereinafter, sometimes referred to as "model #1") that outputs a string separated by spaces when a string is input, and a model (hereinafter, sometimes referred to as "model #2") that outputs a string with the space separators removed when a string is input.

[0043] Note that the information processing device 10 may perform training using different training data for models #1 and #2. For example, the information processing device 10 trains model #1 using the positions of space delimiters in character strings identified based on the number of times each search query is entered into the same group (in other words, the positions of space delimiters in character strings identified using the number of times the search query is entered as an index) and information indicating the character strings. Then, the information processing device 10 trains model #2 using the positions of space delimiters in character strings identified using an index (e.g., CTR or CVR) different from the information used to train model #1 and information indicating the character strings.

[0044] Furthermore, the information processing device 10 trains model #2 using the positions of space separators in character strings identified by a method different from that used for model #1 and information indicating the character strings. To give a specific example, the information processing device 10 trains model #2 using the positions of space separators in character strings identified based on the search query for which content provided to users as search results was selected the most frequently among search queries classified into the same group and information indicating the character strings. Furthermore, the information processing device 10 trains model #2 using the positions of space separators in character strings identified based on the number of conversions of advertising content corresponding to each search query classified into the same group and information indicating the character strings.

[0045] [2-5. Generating a string by deleting specified characters] In the example of Fig. 1, the information processing device 10 may generate a character string by deleting predetermined characters included in the search query in addition to space separators. For example, the information processing device 10 generates a character string indicated by the search query by deleting space separators and macrons from partial search queries separated by spaces. As a specific example, the information processing device 10 generates the character string "cherry juice in season" by deleting space separators and macrons at the end of the word "cherry" from the search queries "cherry juice in season" and "cherry juice in season."

[0046] Note that the information processing device 10 may delete a macron from the search query if it is possible to classify the search query into a predetermined group when a macron included in the search query is deleted in addition to the space separator included in the search query. For example, if it is possible to classify the search query into the group of the character string "cherry juice in season" by deleting a macron or the like at the end of the word "cherry" included in the search query "cherry juice in season", the information processing device 10 deletes the macron from the end of the word "cherry".

[0047] Furthermore, the information processing device 10 may delete all the space separators included in the search query as well as the long notes included in the search query to generate a character string. For example, the information processing device 10 may delete the space separators and the long notes from the search query "cherry juice shun" to generate the character string "cherry juice shun." Furthermore, the information processing device 10 may leave the space separators and generate the character string "cherry juice shun."

[0048] 3. Configuration of Information Processing Device Next, the configuration of the information processing device 10 will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the information processing device 10 according to an embodiment. As shown in Fig. 2, the information processing device 10 has a communication unit 20, a storage unit 30, and a control unit 40.

[0049] (Regarding the communication unit 20) The communication unit 20 is realized by, for example, a network interface card (NIC), etc. The communication unit 20 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the user terminal 100, etc.

[0050] (Regarding the storage unit 30) The storage unit 30 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 2 , the storage unit 30 has a search query information database 31, a group information database 32, and a model database 33.

[0051] (About Search Query Information Database 31) The search query information database 31 stores various types of information related to search queries entered by users. An example of information stored in the search query information database 31 will now be described with reference to FIG. 3. FIG. 3 is a diagram showing an example of the search query information database 31 according to an embodiment. In the example of FIG. 3, the search query information database 31 has items such as a "search query ID," a "group ID," a "search query," a "character string," a "number of inputs," "search result information," and "conversion information."

[0052] "Search query ID" indicates identification information for identifying a search query. "Group ID" indicates identification information for identifying a group. "Search query" indicates information (text information, etc.) that indicates a search query. "String" indicates a string generated from a search query. "Number of inputs" indicates the number of times a search query was input. "Search result information" indicates information about the search results when a search query was input, and stores information indicating, for example, the number of times content input as a search result was selected. "Conversion information" indicates information about the conversion of advertising content corresponding to the search query.

[0053] That is, Figure 3 shows an example in which a search query identified by a search query ID "QID#1" is classified into a group identified by a group ID "GID#1", the search query is "search query #1", the string is "string #1", the number of inputs is "number of inputs #1", the search result information is "search result information #1", and the conversion information is "conversion information #1".

[0054] The information stored in the search query information database 31 is not limited to the above, and various types of information may be stored. For example, the search query information database 31 may store information indicating the number of unique users who input search queries, the number of unique browsers that input search queries, etc.

[0055] (About Group Information Database 32) The group information database 32 stores various types of information related to groups into which search queries are classified. An example of the information stored in the group information database 32 will now be described with reference to FIG. 4. FIG. 4 is a diagram showing an example of the group information database 32 according to the embodiment. In the example of FIG. 4, the group information database 32 has items such as "group ID," "search query information," "character string," and "space delimiter information."

[0056] "Group ID" indicates identification information for identifying a group. "Search query information" indicates information about the search queries included in the group (such as the search query ID). "String" indicates the string generated from the search queries classified into the group. "Space separator information" indicates the position of the space separator in the string.

[0057] That is, FIG. 4 shows an example in which the search query information of a group classified by the group ID "GID#1" is "search query information #1", the character string is "character string #1", and the space delimiter information is "space delimiter information #1".

[0058] (About Model Database 33) The model database 33 stores a model that, when a character string is input, outputs a character string with a space delimiter added or deleted.

[0059] (Regarding the control unit 40) The control unit 40 is a controller, and is realized by, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs stored in a storage device inside the information processing device 10 using RAM as a work area. The control unit 40 is also a controller, and is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). As shown in FIG. 3 , the control unit 40 according to the embodiment has a generation unit 41, a classification unit 42, an identification unit 43, and a learning unit 44, and realizes or executes the functions and actions of information processing described below.

[0060] (Regarding the generation unit 41) The generation unit 41 generates a character string indicated by a search query entered by a user by deleting space separators included in the search query. For example, in the example of Fig. 1, the generation unit 41 generates a character string "AABBCC" from the search query "AA BB CC" by deleting the space separator between "AA" and "BB" and the space separator between "BB" and "CC" in the search query "AA BB CC", and stores the character string "AABBCC" in the search query information database 31.

[0061] Furthermore, the generation unit 41 may generate a character string indicated by the search query by further deleting predetermined characters included in the search query. For example, in the example of Fig. 1, the generation unit 41 generates a character string indicated by the search query by deleting space separators and macrons at the ends of partial search queries separated by spaces.

[0062] (Regarding classification unit 42) The classification unit 42 classifies the search queries based on the character strings generated by the generation unit 41. For example, in the example of FIG. 1 , the character string generated from each of the search queries "AABBCC," "AA BB CC," and "AA BBCC" is "AABBCC," so the classification unit 42 classifies these search queries into group #1. To give a specific example, the classification unit 42 stores the search queries "AABBCC," "AA BB CC," and "AA BBCC" in association with group #1 in the group information database 32.

[0063] Furthermore, when a search query can be classified into multiple groups, the classification unit 42 may classify the search query based on the number of times the search query is input and the number of times each search query classified into the multiple groups is input. For example, in the example of FIG. 1, when a thesaurus is used to convert part of the search query into synonyms or similar words, if the search query can be classified into multiple groups, the classification unit 42 classifies the search query into one of the possible groups in which the difference between the number of times the search query is input and the number of times the search query is input is less than a predetermined threshold. Furthermore, when a search query can be classified into multiple groups, the classification unit 42 classifies the search query into one of the possible groups in which the difference between the number of times the search query is input and the number of times the search query is input is equal to or greater than a predetermined threshold.

[0064] (Regarding the identifying unit 43) The identification unit 43 identifies the positions of space separators in the character string generated from each search query classified into the same group based on the number of times each search query has been input. For example, in the example of Fig. 1, since the search query "AA BB CC" has been input the most frequently in group #1, the identification unit 43 identifies that appropriate positions of space separators in the character string "AABBCC" are between "AA" and "BB" and between "BB" and "CC".

[0065] Furthermore, the identification unit 43 may identify the position of a space separator in a character string generated from each search query based on the proportion of search queries classified into the same group that were input, that is, the proportion within the same group. For example, in the example of Fig. 1, the identification unit 43 calculates the proportion of search queries that were input within the group, and identifies the appropriate position of a space separator in a character string based on the position of a space separator in the search query with the highest proportion.

[0066] Furthermore, the identification unit 43 may identify the positions of space separators in the character string generated from each search query classified into the same group, based on the number of browsers that have input each search query. For example, in the example of Fig. 1, the identification unit 43 identifies the positions of space separators in the character string, based on the search query that has been input by the largest number of unique browsers, among the search queries classified into the same group.

[0067] Furthermore, the identification unit 43 may further identify the positions of space separators in the character strings generated from each search query based on the number of times that content indicating the search results for each search query classified into the same group has been selected. For example, in the example of Fig. 1, the identification unit 43 identifies the positions of space separators in the character string based on the search query for which content provided to users as search results has been selected the most frequently among the search queries classified into the same group.

[0068] Furthermore, the identification unit 43 may further identify the positions of space separators in the character strings generated from each search query based on the number of conversions of advertising content corresponding to each search query classified into the same group. For example, in the example of Fig. 1, the identification unit 43 identifies the positions of space separators in the character string based on the search query for which advertising content provided to users as search results has been selected the most frequently among the search queries classified into the same group.

[0069] Furthermore, the identification unit 43 may identify the positions of space separators in the character string generated from each search query based on the positions of space separators in the search query that has been entered most frequently among the search queries classified into the same group. For example, in the example of Fig. 1, since the search query "AA BB CC" has been entered most frequently in group #1, the identification unit 43 identifies that appropriate positions of space separators in the character string "AABBCC" are between "AA" and "BB" and between "BB" and "CC".

[0070] Furthermore, when there are multiple search queries that have been entered a predetermined number of times or more among the search queries classified into the same group, the identification unit 43 may identify the positions of space separators in the character string generated from each search query based on the search query with the largest number of space separators among the search queries that have been entered a predetermined number of times or more. For example, in the example of FIG. 1, when the threshold for the number of entries is set to "100," the search queries "DDEE FF" and "DD EE FF" fall into group #2. In such a case, the identification unit 43 identifies the positions of space separators in the character string "DDEEFF" based on the search query "DD EE FF" that has the largest number of space separator positions.

[0071] Furthermore, when there are multiple search queries classified into the same group that have been input a predetermined number of times or more, the identification unit 43 may identify the positions of space separators in the character string generated from each search query based on the search query with the fewest number of space separators among the search queries that have been input a predetermined number of times or more. For example, in the example of FIG. 1, when the input count threshold is set to "100," the search queries "DDEE FF" and "DD EE FF" correspond to group #2. In such a case, the identification unit 43 identifies the positions of space separators in the character string "DDEEFF" based on the search query "DDEE FF" that has the fewest space separators among the search queries "DDEE FF" and "DD EE FF."

[0072] Furthermore, when there are multiple search queries classified into the same group that have been input a predetermined number of times or more, the identification unit 43 may identify the positions of space separators in the character string generated from each search query based on search queries extracted based on the number of times each substring separated by a space was input from the search queries that have been input a predetermined number of times or more. For example, in the example of FIG. 1 , when the input count threshold is set to "100," group #2 corresponds to the search queries "DDEE FF" and "DD EE FF." In such a case, the identification unit 43 tallies the input counts of the partial search queries "DD," "EE," and "DDEE" included in the search queries "DDEE FF" and "DD EE FF," respectively. Then, when the input count of the partial search query "DDEE" is greater than the input count of each of the partial search queries "DD" and "EE," the information processing device 10 identifies the positions of space separators in the character string "DDEEFF" based on the search query "DDEE FF." On the other hand, if the number of times either the partial search query "DD" or "EE" is entered is greater than the number of times the partial search query "DDEE" is entered, the information processing device 10 determines the position of the space separator in the string "DDEEFF" based on the search query "DD EE FF".

[0073] (About Learning Section 44) The learning unit 44 learns a model that outputs a character string separated by spaces when a character string is input, based on the positions of space separators in the character string identified by the identification unit 43. For example, in the example of Fig. 1, the learning unit 44 learns a model that outputs a character string separated by spaces when a character string is input.

[0074] The learning unit 44 may further train the model based on information about search results using the character string output by the model. For example, in the example of FIG. 1, when the behavioral information of user U3 indicates that user U3 selected content provided as a search result based on "GGHH II," the learning unit 44 trains the model using a character string "GGHH II" obtained by editing the character string "GGHHII" as a positive example. When the behavioral information of user U3 indicates that user U3 did not select content provided as a search result based on "GGHH II," the learning unit 44 trains the model using a character string "GGHH II" obtained by editing the character string "GGHHII" as a negative example.

[0075] Furthermore, the learning unit 44 may train a model that outputs a character string from which space separators have been deleted when a character string is input, based on the positions of space separators in the character string identified by the identification unit 43. For example, in the example of Fig. 1, the learning unit 44 trains a model that outputs a character string from which space separators have been deleted when a character string is input.

[0076] [4. Information processing flow] The procedure of information processing of the information processing device 10 according to the embodiment will be described with reference to Fig. 5. Fig. 5 is a flowchart showing an example of the procedure of information processing according to the embodiment.

[0077] As shown in FIG. 5, the information processing device 10 generates a character string indicated by a search query input by a user by deleting space separators included in the search query (step S101). Next, the information processing device 10 classifies the search queries based on the generated character strings (step S102). Next, the information processing device 10 identifies the positions of space separators in the character strings generated from each search query based on the number of times each search query classified into the same group has been input (step S103). Next, the information processing device 10 determines whether or not a search query has been received from the user (step S104). If a search query has not been received (step S104; No), the information processing device 10 waits until a search query is received.

[0078] On the other hand, if a search query has been received (step S104; Yes), search results are provided based on the identified space delimiter positions and the received search query (step S105), and the process ends.

[0079] [5. Modifications] The above-described embodiment is merely an example, and various modifications and applications are possible.

[0080] [5-1. Regarding the period when the search query was entered] In the above-described embodiment, the information processing device 10 may perform the above-described process using search queries input by a user in a predetermined period (e.g., the last month, the last six months, etc.). If the amount of search queries input by a user in a predetermined period does not reach a predetermined amount, the information processing device 10 may extend the period (e.g., from the last month to the last three months, or from the last six months to the last year, etc.) so that the amount of search queries input by the user reaches the predetermined amount.

[0081] [5-2. About generating strings] The method by which the information processing device 10 generates a character string from a search query is not limited to the above-described method, and any method may be used. For example, if a group of the character string "BBCCAA" exists, the information processing device 10 may delete the space separator from the search query "AA BB CC" and change the order of the partial search queries to generate the character string "BBCCAA" from the search query.

[0082] [5-3. Processing mode] Of the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, and conversely, all or part of the processes described as being performed manually can be performed automatically using known methods. In addition, the information, including the processing procedures, specific names, various data, and parameters shown in the above text and drawings, can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0083] Furthermore, the components of each device shown in the figure are conceptual functional components and do not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

[0084] Furthermore, the above-described embodiments can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0085] The information processing device 10 may combine the above-described process with various other processes to build a model for performing spelling correction. For example, the information processing device 10 acquires spelling correction data such as "shop YY port town" as an uncorrected string and "shop YY port town" as a corrected string. This process is performed, for example, by comparing the log of the input search query with a pre-created database and extracting pairs of strings that are similar to or greater than a predetermined threshold in terms of the number of different characters, pronunciation, number of adjacent keyboard keys used during input, etc., as the uncorrected string and the corrected string. The information processing device 10 adds spaces to such spelling correction data using the above-described model. For example, the information processing device 10 may convert the corrected string "shop YY port town" in the spelling correction data into data such as "shop YY port town" and train a correction model that corrects "shop YY port town" to a string such as "shop YY port town." That is, the information processing device 10 may use the generated model to input a space delimiter into the corrected character string used for learning the correction model, and generate a correction model that corrects the pre-correction character string to the corrected character string.

[0086] [6. Effects] As described above, the information processing device 10 according to the embodiment includes a generation unit 41, a classification unit 42, an identification unit 43, and a learning unit 44. The generation unit 41 generates a character string indicated by a search query entered by a user by deleting space separators included in the search query. The generation unit 41 also generates a character string indicated by the search query by deleting predetermined characters included in the search query. The classification unit 42 classifies the search query based on the character string generated by the generation unit 41. If a search query can be classified into multiple groups, the classification unit 42 classifies the search query based on the number of times the search query was entered and the number of times each search query classified into the multiple groups was entered. The identification unit 43 identifies the position of space separators in the character string generated from each search query based on the number of times each search query classified into the same group was entered. The identification unit 43 also identifies the position of space separators in the character string generated from each search query based on the position of space separators in the search query that has been entered the most frequently among the search queries classified into the same group. The learning unit 44 trains a model that outputs a character string separated by spaces when a character string is input, based on the positions of space separators in the character string identified by the identification unit 43. The learning unit 44 also trains a model that outputs a character string from which the space separators have been deleted when a character string is input, based on the positions of space separators in the character string identified by the identification unit 43. The learning unit 44 also trains the model based on information regarding search results using the character string output by the model.

[0087] As a result, the information processing device 10 according to the embodiment can identify the position of space separators in the character string indicated by each search query based on the search query most frequently entered by users among the search queries classified into the same group, and can therefore identify the appropriate position of space separators in the search query.

[0088] In the information processing device 10 according to the embodiment, for example, the identification unit 43 identifies the position of space separators in the character string generated from each search query based on the proportion of search queries entered within the same group. The identification unit 43 also identifies the position of space separators in the character string generated from each search query based on the number of browsers that entered each search query entered within the same group. The identification unit 43 also identifies the position of space separators in the character string generated from each search query based on the number of times content indicating search results for each search query entered within the same group was selected. The identification unit 43 also identifies the position of space separators in the character string generated from each search query based on the number of conversions of advertising content corresponding to each search query entered within the same group. When there are multiple search queries entered within the same group that have been entered a predetermined number of times or more, the identification unit 43 identifies the position of space separators in the character string generated from each search query based on the search query with the greatest number of space separators among the search queries entered a predetermined number of times or more. Furthermore, when there are multiple search queries that have been input a predetermined number of times or more, among the search queries classified into the same group, the identification unit 43 identifies the positions of space separators in the character string generated from each of the search queries based on the search query that has the fewest number of space separators among the search queries that have been input a predetermined number of times or more. Furthermore, when there are multiple search queries that have been input a predetermined number of times or more, among the search queries classified into the same group, the identification unit 43 identifies the positions of space separators in the character string generated from each of the search queries based on the search queries that have been input a predetermined number of times or more and are extracted based on the number of times each substring separated by a space was input.

[0089] As a result, the information processing device 10 according to the embodiment can identify the positions of space separators in a search query using various indices, thereby improving the accuracy of identifying the positions of space separators.

[0090] [7. Hardware Configuration] The information processing device 10 according to each of the above-described embodiments is realized, for example, by a computer 1000 configured as shown in Fig. 6. The information processing device 10 will be described below as an example. Fig. 6 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 10. The computer 1000 has a CPU 1100, a ROM 1200, a RAM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0091] The CPU 1100 operates and controls each unit based on programs stored in the ROM 1200 or the HDD 1400. The ROM 1200 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, programs that depend on the hardware of the computer 1000, and the like.

[0092] The HDD 1400 stores programs executed by the CPU 1100, data used by such programs, etc. The communication interface 1500 receives data from other devices via a communication network 500 (corresponding to the network N in the embodiment) and sends the data to the CPU 1100, and also transmits data generated by the CPU 1100 to other devices via the communication network 500.

[0093] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 1600. The CPU 1100 acquires data from the input devices via the input / output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input / output interface 1600.

[0094] Media interface 1700 reads a program or data stored in recording medium 1800 and provides it to CPU 1100 via RAM 1300. CPU 1100 loads the program or data from recording medium 1800 onto RAM 1300 via media interface 1700 and executes the loaded program. Recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0095] For example, when the computer 1000 functions as the information processing device 10, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1300 to realize the functions of the control unit 40. The HDD 1400 also stores various data in the storage device of the information processing device 10. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a predetermined communication network.

[0096] [8. Other] Although some of the embodiments of the present application have been described in detail above with reference to the drawings, these are merely examples, and the present invention can be implemented in other forms that include the embodiments described in the Disclosure of the Invention section and that have undergone various modifications and improvements based on the knowledge of those skilled in the art.

[0097] Furthermore, the information processing device 10 described above can flexibly change its configuration, for example, by calling an external platform or the like using an API (Application Programming Interface) or network computing, depending on the function.

[0098] Furthermore, the term "unit" in the claims can be read as "means" or "circuit," etc. For example, a generating unit can be read as generating means or generating circuit. [Explanation of symbols]

[0099] 10. Information processing equipment 20 Communications Department 30 Storage section 31 Search Query Information Database 32 Group Information Database 33 Model Database 40 Control Unit 41 Generation part 42 Classification Department 43 Specific part 44 Learning Department 100 user terminals

Claims

1. a generation unit that generates a character string indicated by a search query input by a user by deleting space separators included in the search query; a classification unit that classifies the search queries based on the character strings generated by the generation unit; an identification unit that identifies the position of a space delimiter in the character string generated from each search query classified into the same group based on the number of times each search query has been input; and The identification unit Furthermore, the position of the space delimiter in the character string generated from each search query is identified based on the number of times that content representing search results for each search query classified into the same group has been selected.

1. An information processing device comprising:

2. The identification unit Identifying the position of space delimiters in the character string generated from each search query based on the ratio of inputs of each search query classified into the same group, the ratio within the same group.

2. The information processing apparatus according to claim 1, wherein:

3. The identification unit Identifying the positions of space delimiters in the character string generated from each search query based on the number of browsers that have entered each search query classified into the same group.

2. The information processing apparatus according to claim 1, wherein:

4. The identification unit Furthermore, based on the number of conversions of advertising content corresponding to each search query classified into the same group, the position of the space delimiter in the character string generated from each search query is identified.

2. The information processing apparatus according to claim 1, wherein:

5. The identification unit Identifying the positions of space separators in the character strings generated from each search query based on the positions of space separators in the search query that has been entered most frequently among the search queries classified into the same group.

2. The information processing apparatus according to claim 1, wherein:

6. The identification unit If there are multiple search queries that have been entered a predetermined number of times or more among the search queries classified into the same group, the positions of space separators in the character strings generated from each of the search queries are identified based on the search query that has the largest number of space separators among the search queries that have been entered a predetermined number of times or more.

2. The information processing apparatus according to claim 1, wherein:

7. The identification unit If there are multiple search queries that have been entered a predetermined number of times or more among the search queries classified into the same group, the positions of space separators in the character strings generated from each of the search queries are identified based on the search query that has the fewest number of space separators among the search queries that have been entered a predetermined number of times or more.

2. The information processing apparatus according to claim 1, wherein:

8. The identification unit If there are multiple search queries that have been entered a predetermined number of times or more among the search queries classified into the same group, the position of the space separator in the character string generated from each search query is identified based on the search queries extracted based on the number of times each substring separated by a space has been entered from the search queries that have been entered a predetermined number of times or more.

2. The information processing apparatus according to claim 1, wherein:

9. a first learning unit that learns a model that outputs a character string separated by spaces when a character string is input, based on the positions of space separators in the character string identified by the identification unit; 2. The information processing apparatus according to claim 1, further comprising:

10. The first learning unit Furthermore, the model is trained based on information about search results using character strings output by the model.

10. The information processing apparatus according to claim 9,

11. a second learning unit that learns a model that outputs a character string from which space separators have been deleted when a character string is input based on the positions of space separators in the character string identified by the identification unit; 2. The information processing apparatus according to claim 1, further comprising:

12. The second learning unit Furthermore, the model is trained based on information about search results using character strings output by the model.

12. The information processing apparatus according to claim 11,

13. The generation unit Furthermore, a character string indicated by the search query is generated by deleting predetermined characters contained in the search query.

2. The information processing apparatus according to claim 1, wherein:

14. 1. A computer-implemented information processing method, comprising: a generating step of generating a character string indicated by the search query by deleting space separators included in the search query entered by the user; a classification step of classifying the search queries based on the character strings generated by the generation step; an identifying step of identifying the positions of space delimiters in the character strings generated from each of the search queries classified into the same group based on the number of times each of the search queries has been input; Including, The identifying step includes: Furthermore, the position of the space delimiter in the character string generated from each search query is identified based on the number of times that content representing search results for each search query classified into the same group has been selected. An information processing method comprising:

15. a generation step of generating a character string indicated by a search query input by a user by deleting space separators included in the search query; a classification step of classifying the search queries based on the character strings generated by the generation step; an identifying step of identifying the position of a space delimiter in the character string generated from each search query classified into the same group based on the number of times each search query has been input; on the computer, The identification procedure includes: Furthermore, the position of the space delimiter in the character string generated from each search query is identified based on the number of times that content representing search results for each search query classified into the same group has been selected. An information processing program characterized by:

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