Information processing apparatus, information processing method, and information processing program

Abstract

To easily classify multiple pieces of data based on a history of search queries, into a plurality of quadrants.SOLUTION: An information processing apparatus includes an acquisition unit, a generation unit, and a provision unit. The acquisition unit acquires multiple pieces of data based on a history of search queries, including numerical values of multiple kinds of indices, and designation information related to a designation for classifying the multiple pieces of data. The generation unit generates a classification result for classifying the multiple pieces of data into a plurality of quadrants, based on the multiple pieces of data and the designation information acquired by the acquisition unit. The provision unit provides content indicating the classification result generated by the generation unit.SELECTED DRAWING: Figure 6

Description

Technical Field

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

Background Art

[0002] Conventionally, a technique for classifying a plurality of data based on the history of a search query, such as keywords input to a search engine, into a plurality of quadrants indicating the trend state of the search query, etc. is known.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the prior art, there are cases where it cannot be said that a plurality of data based on the history of a search query are appropriately classified into a plurality of quadrants. For example, in the prior art, thresholds for indicators such as the number of searches and the number of repeated searches, and the number of quadrants to be divided are set manually. If this setting is not appropriate, a plurality of data cannot be appropriately classified, and it takes time to optimize the threshold for which numerical value is assigned to which quadrant.

[0005] The present application has been made in view of the above, and an object thereof is to easily classify a plurality of data based on the history of a search query into a plurality of quadrants.

Means for Solving the Problems

[0006] The information processing apparatus according to the present application includes an acquisition unit that acquires numerical values of a plurality of types of indicators, a plurality of data based on a search query history, and designation information regarding a designation for classification of the plurality of data; a generation unit that generates a classification result for classifying the plurality of data into a plurality of quadrants based on the plurality of data and the designation information acquired by the acquisition unit; and a provision unit that provides content indicating the classification result generated by the generation unit.

Effect of the Invention

[0007] According to one aspect of the embodiment, a plurality of data based on a search query history can be easily classified into a plurality of quadrants.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Modes for Carrying Out the Invention

[0009] Hereinafter, embodiments for implementing the information processing apparatus, information processing method, and information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing apparatus, information processing method, and information processing program according to the present application are not limited by this embodiment. Also, in the following embodiments, the same parts are denoted by the same reference numerals, and duplicate descriptions are omitted.

[0010] (Embodiment) [1. Configuration of Information Processing System] The information processing system 1 shown in FIG. 1 will be described. FIG. 1 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. As shown in FIG. 1, the information processing system 1 includes a terminal device 10 and an information processing device 100. The terminal device 10 and the information processing device 100 are communicably connected by wire or wirelessly via a predetermined communication network (network N).

[0011] The information processing device 100 in FIG. 1 includes numerical values of a plurality of types of indicators, generates a classification result for classifying a plurality of data into a plurality of quadrants based on a plurality of data based on the history of search queries and designation information regarding the designation of the classification of the plurality of data. The information processing device 100 provides the terminal device 10 with content indicating the classification result via the network N.

[0012] For example, the information processing device 100 inputs a prompt, which is a natural language string including both a plurality of search queries and designation information for designating processing for the plurality of search queries, to a learned model such as a generative AI (Artificial Intelligence) like GPT.

[0013] Subsequently, the information processing device 100 automatically generates, as a classification result, a character string following the input character string, which indicates, for each search query output from the learned model, what threshold value should be used for classification and which search queries are classified in each quadrant.

[0014] Then, the information processing apparatus 100 provides, as content, a quadrant diagram in which each data is classified into a quadrant, which is an area divided vertically and horizontally by threshold values of each index, with the number of searches and the degree of increase in searches, which are indices associated with a plurality of search queries, on the horizontal and vertical axes, to the terminal device 10.

[0015] The terminal device 10 is an information processing apparatus used by a user who makes a designation or the like regarding the classification of a plurality of data based on the history of search queries. The terminal device 10 may be any device as long as it can realize the processing in the embodiment. The terminal device 10 is, for example, a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, or the like.

[0016] The terminal device 10 is, for example, a smart device such as a smartphone or a tablet, and is a portable terminal device that can communicate with an arbitrary server device via a wireless communication network such as 3G to 5G (Generation) or LTE (Long Term Evolution). Further, the terminal device 10 has, for example, a screen such as a liquid crystal display, and has a screen having a touch panel function, and accepts various operations on display data such as content, such as a tap operation, a slide operation, and a scroll operation, from the user using a finger, a stylus, or the like.

[0017] The information processing apparatus 100 is an information processing apparatus aimed at easily classifying a plurality of data based on the history of search queries, and may be any device as long as it can realize the processing in the embodiment. The information processing apparatus 100 is, for example, a server device, a cloud system, or the like that accepts a designation (for example, input, selection, etc.) from a user and provides content indicating a classification result for classifying a plurality of data into a plurality of quadrants.

[0018] In addition, in FIG. 1, the case where the terminal device 10 and the information processing apparatus 100 are separate devices is shown, but the terminal device 10 and the information processing apparatus 100 may be integrated.

[0019] 〔2. An Example of Information Processing〕 Hereinafter, an example of information processing will be described with reference to FIGS. 2 to 4. FIG. 2 is a diagram showing an example of information processing according to an embodiment. FIG. 3 is a diagram showing an example of a quadrant diagram according to an embodiment. FIG. 4 is a diagram showing an example of a plurality of data and designation information according to an embodiment. In FIG. 2, a case where the terminal device 10 is a smartphone that receives various operations from the user U1 and the information processing device 100 is a server device will be described.

[0020] For example, the terminal device 10 receives from the user U1 an input of a prompt that is a natural language string including a plurality of search queries that are a plurality of data and designation information for specifying processing for the plurality of search queries, and transmits the input to the information processing device 100. The information processing device 100 acquires the received above-described prompt as a plurality of data and designation information (step S101).

[0021] As an example, the terminal device 10 transmits a prompt P in FIG. 4 in which a plurality of search queries (a plurality of data) that are classification targets for each area (each quadrant) of the quadrant diagram C1 in FIG. 3 are input as "input data" in FIG. 4, and the information processing device 100 acquires the prompt P.

[0022] Here, the input data includes, as a plurality of types of indexes, a trend score that is the number of searches within the most recent one day of a search query corresponding to the horizontal axis of the quadrant diagram C1 in FIG. 3 and the degree of increase in the search of the search query corresponding to the vertical axis (for example, the number of repeated searches, etc.). The information processing device 100 may generate a plurality of data by associating these indexes with a plurality of search queries based on the history of the search queries of the user U1, or may acquire a plurality of search queries in which these indexes are associated in advance as a plurality of data.

[0023] Further, the information processing apparatus 100 may receive from the user U1 a specification regarding which information to use as an index among various types of information associated with the search query, and which numerical value calculated from which information using what calculation formula to use as an index. In such a case, the information processing apparatus 100 generates an index from various types of information associated with the search query, and generates a prompt P using these indexes as input data.

[0024] Further, the prompt P includes specified information P1 to specified information P6. The specified information P1 is specified information indicating that the search query is divided into four areas by dividing two indexes, namely, the search count and the trend score, into two for each. That is, the specified information P1 is information specifying the number of areas into which the input data is divided. Note that when the information processing apparatus 100 receives from the user U1 a specification regarding the number of areas, the specified information P1 for dividing into the received number of areas is generated each time.

[0025] The specified information P2 is specified information for generating a threshold value of the search count and a threshold value of the trend area for classifying a plurality of search queries into a plurality of areas.

[0026] The specified information P3 is specified information for classifying search queries into a plurality of areas so that the number of search queries classified into each area is one or more. The specified information P5 is specified information for classifying search queries into a plurality of areas so that the number of search queries classified into each area is five or more.

[0027] The specified information P4 is specified information for generating a title (name) of each area indicating the attribute of each area based on the content of the search queries classified into each area. The specified information P6 is specified information for generating a summary indicating, as an attribute, what search queries are classified into each area summarized within 20 characters.

[0028] Note that the pre-trained models such as GPT are considered to output titles and summaries that take into account the content of the search query based on the specified information P4 and the specified information P6. On the other hand, the information processing apparatus 100 may adopt the specified information P5 and P6 that are made explicit to consider the content of the search query, such as "outputting a title in consideration of the content of the search query" and "outputting a summary in consideration of the content of the search query".

[0029] Next, the information processing apparatus 100 generates a classification result for classifying a plurality of pieces of data into a plurality of quadrants based on the acquired plurality of pieces of data and the specified information (step S102). For example, the information processing apparatus 100 inputs a prompt P including the plurality of search queries and the specified information acquired in step S101 to a pre-trained model such as GPT that has been trained to output a character string following the input character string, and automatically generates a classification result.

[0030] As an example, when the information processing apparatus 100 inputs a prompt P as shown in FIG. 4 to GPT, it acquires thresholds such as a search count of 2511 and a trend score of 0.75 from GPT. In such a case, as shown in FIG. 3, the information processing apparatus 100 classifies each search query into four areas according to the two thresholds acquired from GPT.

[0031] In addition, the information processing apparatus 100 obtains natural language character strings such as "Potential Area", "Next Break Area", "Break Area", and "Boom Area" as titles for each area from GPT as titles. In such a case, as shown in FIG. 3, the information processing apparatus 100 generates, as a classification result, the natural language character string output as a title from the pre-trained model for each area.

[0032] The "Potential Area" in the lower left of FIG. 3 is an unpopular quadrant where search queries with both low trend scores and low search counts are classified. The "Next Break Area" in the upper left is a quadrant where search queries with high trend score values and low search counts are classified, such as by maniacs. The "Break Area" in the upper right is a quadrant indicating a trend where search queries with both high trend scores and high search counts are classified. The "Boom Area" in the lower right is a quadrant where search queries with low trend scores and high search counts are classified, and the degree of attention is at its upper limit.

[0033] Next, the information processing apparatus 100 provides the terminal apparatus 10 with content indicating the generated classification result (step S103). For example, based on the character string of the classification result, the information processing apparatus 100 generates a quadrant diagram C1 of FIG. 3 in which each search query is classified into each area described above with a search count of 2511 on the horizontal axis and a trend score of 0.75 on the vertical axis, and the title of each area is visualized. Then, the information processing apparatus 100 provides the terminal apparatus 10 with the quadrant diagram C1 as content. The terminal apparatus 10 receives and displays the content provided by the information processing apparatus 100.

[0034] Note that the content provided by the information processing apparatus 100 includes a summary of each area generated using GPT. For example, when the user U1 selects the potential area, the terminal apparatus 10 will display the summary text generated for the potential area.

[0035] Also, in FIG. 3, there are two types of indicators, but if there are multiple types, any values can be adopted. Also, the values of the indicators are not limited to the values in FIG. 3, and any values can be adopted. For example, the indicators can include at least one of the search count within the most recent day and the trend score, the number of users who searched the search query, the degree of relevance to the attributes of multiple quadrants, the search date and time of the search query, and the increase in the number of times the search query was searched within the most recent month.

[0036] In this case, the information processing apparatus 100 generates a classification result such that each search query is classified into each quadrant with each index as an axis. As an example, the information processing apparatus 100 generates a classification result such that each search query is classified into each quadrant with the number of searches within the most recent one day as the X-axis which is the horizontal axis and the search date and time of the search query as the Y-axis which is the vertical axis. As another example, the information processing apparatus 100 generates a classification result such that each search query is classified into each quadrant with the increase in the number of times the search query has been searched within the most recent one month as the Z-axis.

[0037] Also, in FIG. 3, the number of quadrants is four, but any value can be adopted as long as it is a plurality. Also, although the quadrant diagram C1 is a trend map showing the trend state of the search query, any one can be adopted as long as a plurality of data are classified into a plurality of quadrants.

[0038] [3. Configuration of the Terminal Device] Next, with reference to FIG. 5, the configuration of the terminal device 10 according to the embodiment will be described. FIG. 5 is a diagram showing a configuration example of the terminal device 10 according to the embodiment. As shown in FIG. 5, the terminal device 10 includes a communication unit 11, an input unit 12, an output unit 13, and a control unit 14.

[0039] (Communication Unit 11) The communication unit 11 is realized by, for example, a NIC (Network Interface Card) or the like. Then, the communication unit 11 is connected to a predetermined network N by wire or wirelessly, and information is transmitted and received to and from the information processing apparatus 100 or the like via the predetermined network N.

[0040] (Input Unit 12) The input unit 12 receives various operations from the user. For example, the input unit 12 receives various operations from the user via a display surface having a touch panel function, buttons provided on the terminal device 10, or a keyboard and a mouse connected to the terminal device 10. As an example, the input unit 12 receives at least one input operation of designation information, quadrant number information, and data number information from the user.

[0041] (Output Unit 13) The output unit 13 is a display screen of a tablet terminal or the like realized by, for example, a liquid crystal display, an organic EL (Electro-Luminescence) display, or the like, and is a display device for displaying various information. For example, the output unit 13 displays content based on the information received from the information processing device 100.

[0042] (Control unit 14) The control unit 14 is, for example, a controller. The control unit 14 is realized, for example, by various programs stored in a storage device inside the terminal device 10 being executed with the RAM (Random Access Memory) as a work area by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like.

[0043] For example, these various programs include the programs of applications installed in the terminal device 10. For example, the various programs include the programs of applications for displaying content based on the information received from the information processing device 100. Further, the control unit 14 is realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0044] As shown in FIG. 5, the control unit 14 has a receiving unit 141 and a transmitting unit 142, and realizes or executes the operations of information processing described below.

[0045] (Receiving unit 141) The receiving unit 141 receives content indicating a classification result for classifying a plurality of data into a plurality of quadrants. For example, the receiving unit 141 receives the quadrant diagram C1 of FIG. 3 from the information processing device 100.

[0046] (Transmitting unit 142) The transmission unit 142 transmits information based on the operations of the user. For example, the transmission unit 142 transmits the prompt P in FIG. 4 input by the user to the information processing apparatus 100 through the input unit 12. Further, for example, when at least one of the quadrant number information and the data number information is input to the input unit 12, the transmission unit 142 transmits the information input to the input unit 12 to the information processing apparatus 100.

[0047] [4. Configuration of Information Processing Apparatus] Next, the configuration of the information processing apparatus 100 according to the embodiment will be described with reference to FIG. 6. FIG. 6 is a diagram showing a configuration example of the information processing apparatus 100 according to the embodiment. As shown in FIG. 6, the information processing apparatus 100 includes a communication unit 110, a storage unit 120, and a control unit 130. Note that the information processing apparatus 100 may include an input unit (for example, a keyboard, a mouse, etc.) that receives various operations from the administrator of the information processing apparatus 100, and a display unit (for example, a liquid crystal display, etc.) that displays various information.

[0048] (Communication Unit 110) The communication unit 110 is realized by, for example, a NIC or the like. The communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the terminal device 10 and the like via the network N.

[0049] (Storage Unit 120) The storage unit 120 stores various information such as a plurality of data, designation information, classification results, and contents. The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk.

[0050] (Control Unit 130) The control unit 130 is a controller, and is realized, for example, by a CPU, an MPU, or the like, when various programs stored in the storage device inside the information processing apparatus 100 are executed using the RAM as a work area. Further, the control unit 130 is realized by an integrated circuit such as an ASIC or an FPGA.

[0051] As shown in FIG. 6, the control unit 130 includes a reception unit 131, an acquisition unit 132, a generation unit 133, and a provision unit 134, and realizes or executes the operations of information processing described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 6, and any other configuration may be used as long as it can perform the information processing described later.

[0052] (Reception Unit 131) The reception unit 131 receives various information from the user. For example, the reception unit 131 indirectly receives various information from the user via an input to another information processing device such as the terminal device 10. Also, the reception unit 131 receives, for example, from the user, quadrant number information regarding the number of multiple quadrants in the same manner as described above. Further, the reception unit 131 receives, for example, from the user, data number information regarding the number of data classified into each of the multiple quadrants in the same manner as described above.

[0053] (Acquisition Unit 132) The acquisition unit 132 acquires a plurality of data based on the history of search queries, including numerical values of a plurality of types of indicators, and designation information regarding the classification of the plurality of data. For example, the acquisition unit 132 acquires the prompt P in FIG. 4 from another information processing device such as the terminal device 10.

[0054] Also, the acquisition unit 132 further acquires, for example, as the designation information, variation information indicating the variation of the search mode of the search query corresponding to each of the plurality of data. As an example, the acquisition unit 132 acquires variation information indicating that the search count and the trend score have increased by a predetermined number or more, corresponding to the diagonally upward arrow at the right end such as "XXX Subsidy" in the "Next Break Area" of FIG. 3. As another example, the acquisition unit 132 acquires variation information indicating that the search count and the trend score have decreased by a predetermined number or more, corresponding to the diagonally downward arrow at the right end such as "XXXXXX Shibuya" in the "Potential Area".

[0055] Further, the acquisition unit 132 acquires designation information including designation information for classifying a plurality of data into a plurality of quadrants corresponding to the number indicated by the quadrant number information received by the reception unit 131, for example. As an example, the acquisition unit 132 acquires a prompt P including the designation information P1 in FIG. 4.

[0056] Further, the acquisition unit 132 acquires designation information including designation information for classifying a plurality of data into a plurality of quadrants such that the conditions indicated by the data number information received by the reception unit 131 are satisfied by the number of data classified into each of the plurality of quadrants, for example. As an example, the acquisition unit 132 acquires a prompt P including the designation information P3 in FIG. 4. As another example, the acquisition unit 132 acquires a prompt P including the designation information P5.

[0057] Further, the acquisition unit 132 acquires data including at least one of, for example, the number of searches of a search query, the number of users who searched the search query, the degree of relevance to the attributes of a plurality of quadrants, and a trend score that is the degree of increase in the search of the search query. As an example, the acquisition unit 132 acquires the number of searches of a search query within the most recent one day and a search query associated with a trend score.

[0058] (Generation unit 133) The generation unit 133 generates a classification result for classifying a plurality of data into a plurality of quadrants based on the plurality of data and the designation information acquired by the acquisition unit 132. For example, the generation unit 133 automatically generates a classification result for classifying each search query into each area divided into the number specified by the designation information according to the threshold value of each index specified by the designation information.

[0059] Further, the generation unit 133 inputs the plurality of data and the designation information acquired by the acquisition unit 132 into a learned model that has been learned to output a character string following the input character string, for example, and generates a classification result. As an example, the generation unit 133 inputs a prompt P, which is a character string in natural language including a plurality of search queries and designation information, into a learned model such as a generative AI like GPT, and generates a character string following the prompt P as a classification result.

[0060] Further, the generation unit 133 generates a classification result including threshold information by using specification information including specification information to the effect of generating threshold information regarding thresholds of respective types of indicators for classifying a plurality of data into a plurality of quadrants. As an example, the generation unit 133 inputs a prompt P including the specification information P2 in FIG. 4 to a learned model such as a generation AI, and generates, as a classification result, a character string in which the threshold of the search count is 2511 and the threshold of the trend score is 0.75.

[0061] Further, the generation unit 133 generates a classification result including attribute information by using specification information including specification information to the effect of generating attribute information indicating attributes of respective ones of a plurality of quadrants based on the content of data classified into respective ones of the plurality of quadrants. As an example, the generation unit 133 inputs a prompt P including the specification information P4 in FIG. 4 to a learned model such as a generation AI, and generates, as a classification result, a character string including the title of each area.

[0062] Further, the generation unit 133 generates attribute information by using specification information including specification information to the effect of generating attribute information indicating, as an attribute, what kind of data is classified in each of a plurality of quadrants. As an example, the generation unit 133 inputs a prompt P including the specification information P6 in FIG. 4 to a learned model such as a generation AI, and generates, as a classification result, a character string including a summary of each area.

[0063] Further, the generation unit 133 generates threshold information by using specification information including specification information to the effect of generating threshold information based on the similarity of each of a plurality of data. As an example, the generation unit 133 generates threshold information with a search count threshold of 2511 so as to include "Residential Loan Tax Deduction 2024", which is similar in terms of being related to housing and has a larger search count than other data, in the "Potential Area" in FIG. 3.

[0064] Further, the generation unit 133 generates threshold information using designation information including designation information to the effect that the threshold information is generated based on, for example, the density of data classified into each of a plurality of quadrants. As an example, the generation unit 133 generates threshold information with a threshold of 0.75 for the trend area so that the "Route Price Map Tokyo Reiwa 5" satisfying a predetermined density or more in the vertical axis direction of the "Potential Area" in FIG. 3 is included in the "Potential Area".

[0065] Further, the generation unit 133 generates threshold information using designation information including designation information to the effect that the threshold information is generated based on fluctuation information. As an example, the generation unit 133 generates threshold information with a threshold of 0.75 for the trend area so that the "XXXX Family Funeral" in FIG. 3 having a diagonally downward arrow indicating a decrease in the search count or the like at the right end is not included in the "Break Area".

[0066] (Providing unit 134) The providing unit 134 provides content indicating the classification result generated by the generation unit 133. For example, the providing unit 134 provides content indicating the classification result of classifying a plurality of data according to the threshold indicated by the threshold information and the attribute information. As an example, the providing unit 134 provides the quadrant diagram C1 in FIG. 3 in which each search query is classified into each of the above areas according to the search count 2511 on the horizontal axis and the trend score 0.75 on the vertical axis, and the title of each area is visualized, to the terminal device 10.

[0067] [5. Flow of information processing] Next, with reference to FIG. 7, the information processing procedure by the information processing system 1 according to the embodiment will be described. FIG. 7 is a flowchart showing the information processing procedure by the information processing system 1 according to the embodiment. It is a flowchart.

[0068] As shown in FIG. 7, the information processing apparatus 100 acquires numerical values of a plurality of types of indicators, a plurality of data based on the history of search queries, and designation information regarding the designation of the classification of the plurality of data (step S201).

[0069] The information processing apparatus 100 generates a classification result for classifying a plurality of data into a plurality of quadrants based on the acquired plurality of data and the specified information (step S202).

[0070] The information processing apparatus 100 provides content indicating the generated classification result (step S203).

[0071] [6. Effects] As described above, the information processing apparatus 100 includes an acquisition unit 132, a generation unit 133, and a provision unit 134. The acquisition unit 132 acquires a plurality of data including numerical values of a plurality of types of indicators, based on the history of the search query, and specified information regarding the classification of the plurality of data. The generation unit 133 generates a classification result for classifying the plurality of data into a plurality of quadrants based on the plurality of data and the specified information acquired by the acquisition unit 132. The provision unit 134 provides content indicating the classification result generated by the generation unit 133.

[0072] Thereby, the information processing apparatus 100 can automatically and appropriately set, for example, the threshold value of each indicator and the attributes of each quadrant, unlike the prior art in which they were set manually, so that a plurality of data can be easily classified.

[0073] Further, the generation unit 133 inputs the plurality of data and the specified information acquired by the acquisition unit 132 into a learned model that has been learned to output a character string following the input character string, and generates a classification result. Thereby, the information processing apparatus 100 can automatically generate a classification result using a learned model such as a generation AI, so that a plurality of data can be more easily classified.

[0074] Further, the generation unit 133 generates a classification result including threshold information using specified information including specified information to generate threshold information regarding the threshold values of each of a plurality of types of indicators for classifying a plurality of data into a plurality of quadrants. Thereby, the information processing apparatus 100 can set a more appropriate threshold value, so that a plurality of data can be more easily classified.

[0075] Further, the generation unit 133 generates a classification result including attribute information using designation information including designation information to generate attribute information indicating the attributes of each of the plurality of quadrants based on the content of the data classified into each of the plurality of quadrants. Thereby, the information processing apparatus 100 can set, for example, the name of each quadrant along the content of the data to be classified.

[0076] Also, the generation unit 133 generates attribute information using designation information including designation information to generate attribute information indicating, as an attribute, what data is classified into each of the plurality of quadrants. Thereby, the information processing apparatus 100 can set the name, summary, etc. of each quadrant indicating what the data to be classified is, such as the trend state of the search query.

[0077] Further, the providing unit 134 provides content indicating the classification result of classifying a plurality of data by the threshold value indicated by the threshold value information and the attribute information. Thereby, the information processing apparatus 100 can provide, for example, the quadrant diagram C1 of FIG. 3 in which each search query is classified into each of the above areas by the search count 2511 on the horizontal axis and the trend score 0.75 on the vertical axis, and the title of each area is visualized.

[0078] Also, the generation unit 133 generates threshold value information using designation information including designation information to generate threshold value information based on the similarity of each of the plurality of data. Thereby, the information processing apparatus 100 can set a threshold value so that, for example, similar data is included in the same quadrant.

[0079] Also, the generation unit 133 generates threshold value information using designation information including designation information to generate threshold value information based on the density of the data classified into each of the plurality of quadrants. Thereby, the information processing apparatus 100 can set a threshold value so that, for example, data satisfying a predetermined density or more is included in the same quadrant.

[0080] In addition, the acquisition unit 132 further acquires, as specified information, variation information indicating variation in the search mode of search queries corresponding to each of a plurality of data, and the generation unit 133 generates threshold information using specified information including specified information to generate threshold information based on the variation information. As a result, the information processing apparatus 100 can set a threshold value so as not to include data with a decreasing search count or trend score, for example, in a quadrant with a high value of these.

[0081] In addition, it has a reception unit 131 that receives quadrant number information regarding the number of a plurality of quadrants from a user, and the acquisition unit 132 acquires specified information including specified information to classify a plurality of data into a plurality of quadrants corresponding to the number indicated by the quadrant number information received by the reception unit 131. As a result, the information processing apparatus 100 can automatically acquire specified information for classifying a plurality of data into a desired number of quadrants for the user without receiving the prompt P in FIG. 4 from the user every time, for example, if the quadrant number information is received from the user.

[0082] In addition, it has a reception unit 131 that receives data number information regarding the number of data classified into each of a plurality of quadrants from a user, and the acquisition unit 132 acquires specified information including specified information to classify a plurality of data into a plurality of quadrants so that the conditions indicated by the data number information received by the reception unit 131 are satisfied by the number of data classified into each of the plurality of quadrants. As a result, the information processing apparatus 100 can automatically acquire specified information for classifying the number of data classified into each quadrant into a desired number for the user without receiving the prompt P in FIG. 4 from the user every time, for example, if the data number information is received from the user.

[0083] In addition, the acquisition unit 132 acquires data including at least one of the search count of a search query, the number of users who searched the search query, the degree of association with the attributes of a plurality of quadrants, and the trend score which is the degree of increase in the search of the search query. As a result, the information processing apparatus 100 can ultimately provide a quadrant diagram with at least one of these as an axis.

[0084] 〔7. Hardware Configuration〕 Further, the information processing apparatus 100 according to the above-described embodiment is realized by, for example, a computer 1000 having a configuration as shown in FIG. 8. FIG. 8 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing apparatus 100. The computer 1000 includes a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0085] The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 and controls each part. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, a program dependent on the hardware of the computer 1000, and the like.

[0086] The HDD 1400 stores a program executed by the CPU 1100, data used by such a program, and the like. The communication interface 1500 acquires data from other devices via a predetermined communication network and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via a predetermined communication network.

[0087] 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 device via the input / output interface 1600 and outputs the generated data to the output device via the input / output interface 1600.

[0088] The media interface 1700 reads a program or data stored in the recording medium 1800 and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads such a program from the recording medium 1800 onto the RAM 1200 via the media interface 1700 and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc), a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0089] For example, when the computer 1000 functions as the information processing apparatus 100 according to the embodiment, the CPU 1100 of the computer 1000 realizes the functions of the control unit 130 by executing the program loaded onto the RAM 1200. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800. As another example, these programs may be acquired from another device via a predetermined communication network.

[0090] 〔8. Others〕 Also, among the various processes described in the above embodiment, all or part of the processes described as being automatically performed can be manually performed, or all or part of the processes described as being manually performed can be automatically performed by a known method. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

[0091] In addition, each component of each illustrated device is functionally conceptual and does not necessarily have to be physically configured as shown in the drawings. That is, the specific form of distribution and integration of each device is not limited to that shown in the drawings, and all or part of it can be functionally or physically distributed and integrated in any unit according to various loads, usage situations, etc. Further, the above-described embodiments can be appropriately combined within a range that does not cause contradictions in the processing content.

[0092] As described above, some of the embodiments of the present application have been described in detail with reference to the drawings. However, these are examples, and the present invention can be implemented in other forms in which various modifications and improvements are made based on the knowledge of those skilled in the art, including the aspects described in the column of the disclosure of the invention.

[0093] Also, the above-mentioned "section, module, unit" can be read as "means", "circuit", etc. For example, the acquisition section can be read as an acquisition means or an acquisition circuit.

Description of Reference Numerals

[0094] 100 Information processing apparatus 110 Communication section 120 Storage section 130 Control section 131 Reception section 132 Acquisition section 133 Generation section 134 Provision section

Claims

1. An acquisition unit that acquires a plurality of types of numerical values of indicators, a plurality of data based on a search query history, and designation information regarding a designation for classification of the plurality of data; A generation unit that generates a classification result for classifying the plurality of data into a plurality of quadrants based on the plurality of data and the designation information acquired by the acquisition unit; A provision unit that provides content indicating the classification result generated by the generation unit An information processing apparatus characterized by comprising the above.

2. The generation unit inputs the plurality of data and the designation information acquired by the acquisition unit into a learned model that has been learned to output a character string following an input character string, and generates the classification result. The information processing apparatus according to claim 1, characterized in that

3. The generation unit uses the designation information including designation information for generating threshold value information regarding threshold values of each of the plurality of types of indicators for classifying the plurality of data into a plurality of quadrants, and generates the classification result including the threshold value information. The information processing apparatus according to claim 2, characterized in that

4. The generation unit uses the designation information including designation information for generating attribute information indicating attributes of each of the plurality of quadrants based on the content of the data classified into each of the plurality of quadrants, and generates the classification result including the attribute information. The information processing apparatus according to claim 3, characterized in that

5. The generation unit uses the designation information including designation information for generating the attribute information indicating, as the attribute, what kind of data each of the plurality of quadrants is classified from, and generates the attribute information. The information processing apparatus according to claim 4, characterized in that

6. The provision unit provides content indicating the classification result obtained by classifying the plurality of data according to the threshold value indicated by the threshold value information and the attribute information. The information processing apparatus according to claim 4, characterized in that

7. The generation unit uses the designation information including designation information for generating the threshold value information based on the similarity of each of the plurality of data, and generates the threshold value information. The information processing apparatus according to claim 3, characterized in that

8. The generation unit uses the designation information including designation information for generating the threshold value information based on the density of the data classified into each of the plurality of quadrants, and generates the threshold value information. The information processing apparatus according to claim 3, characterized in that

9. The acquisition unit further acquires, as the specified information, variation information indicating a variation in the search mode of a search query corresponding to each of the plurality of data, The generation unit generates the threshold information using the specified information including the specified information to the effect that the threshold information is generated based on the variation information. The information processing apparatus according to claim 3, characterized in that.

10. It has a reception unit that receives quadrant number information regarding the number of the plurality of quadrants from a user, The acquisition unit acquires the specified information including the specified information to the effect that the plurality of data are classified into the plurality of quadrants in the number indicated by the quadrant number information received by the reception unit. The information processing apparatus according to any one of claims 1 to 8, characterized in that.

11. It has a reception unit that receives data number information regarding the number of data classified into each of the plurality of quadrants from a user, The acquisition unit acquires the specified information including the specified information to the effect that the plurality of data are classified into the plurality of quadrants so that the conditions indicated by the data number information received by the reception unit are satisfied by the number of data classified into each of the plurality of quadrants. The information processing apparatus according to any one of claims 1 to 8, characterized in that.

12. The acquisition unit acquires the data including at least one of the number of searches of the search query, the number of users who searched the search query, the degree of relevance with the attributes of the plurality of quadrants, and a trend score which is the degree of increase in the search of the search query. The information processing apparatus according to any one of claims 1 to 8, characterized in that.

13. An information processing method executed by a computer, An acquisition step of acquiring specified information regarding designations about classification of a plurality of data based on a history of search queries, including numerical values of a plurality of types of indicators, and the plurality of data; A generation step of generating a classification result for classifying the plurality of data into a plurality of quadrants based on the plurality of data and the specified information acquired in the acquisition step; And a provision step of providing content indicating the classification result generated in the generation step An information processing method characterized by including.

14. An acquisition procedure for acquiring specified information regarding designations about classification of a plurality of data based on a history of search queries, including numerical values of a plurality of types of indicators, and the plurality of data, A generation procedure for generating a classification result for classifying the plurality of data into a plurality of quadrants based on the plurality of data and the specified information obtained by the acquisition procedure; A provision procedure for providing content indicating the classification result generated by the generation procedure; An information processing program, characterized by causing a computer to execute the above.

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