JP7159373B2 - Information processing device, information processing method and information processing program - Google Patents

Description

The present invention relates to an information processing device, an information processing method, and an information processing program.

2. Description of the Related Art In recent years, with the rapid spread of the Internet, techniques related to analysis using various information on the Internet, for example, have been provided. For example, there has been proposed a technique for extracting information on needs for a target provided by a predetermined business operator based on a search query input by a user.

JP 2019-32776 A

However, it is not always possible to obtain useful information with the above-described conventional techniques. For example, in the above-described prior art, since the information on the needs for the target provided by the predetermined business operator is only extracted, the information on the latent needs for the target provided by the predetermined business operator can be visually and appropriately displayed. cannot be presented to

The present application has been made in view of the above, and an object thereof is to provide an information processing apparatus, an information processing method, and an information processing program capable of providing useful information.

An information processing apparatus according to the present application provides a plurality of keyword maps that visualize co-occurrence relationships between keywords by connecting a plurality of nodes corresponding to keywords having co-occurrence relationships, and keywords having different input conditions. an acquisition unit that acquires a plurality of keyword maps that visualize the co-occurrence relationships of the above; an identification unit that identifies common keywords common to the plurality of keyword maps; and a common keyword map that visualizes the co-occurrence relationships between the common keywords. A generation unit that generates, the common keyword map, and the plurality of keyword maps excluding the nodes corresponding to the common keywords are combined into the common keywords corresponding to the nodes included in the common keyword map and the plurality of keyword maps. a display section for displaying in a visualized state the co-occurrence relationship between included nodes and corresponding keywords, wherein the display section reproduces the plurality of keyword maps and the common keyword map in chronological order in a time slider format. It is characterized by

According to one aspect of the embodiment, there is an effect that useful information can be obtained.

FIG. 1 is a diagram illustrating an overview of information processing according to the embodiment. FIG. 2 is a diagram illustrating an example of a screen of the terminal device according to the embodiment; FIG. 3 is a diagram illustrating a configuration example of an information processing system according to the embodiment; FIG. 4 is a diagram illustrating a configuration example of a terminal device according to the embodiment; FIG. 5 is a diagram illustrating a configuration example of an information providing apparatus according to the embodiment; FIG. 6 is a diagram showing an example of a user information database. FIG. 7 is a diagram showing an example of a history information database. FIG. 8 is a diagram showing an example of the keyword information database. FIG. 9 is a flow chart showing a processing procedure according to the embodiment. FIG. 10 is a diagram illustrating an example of a hardware configuration;

Embodiments for implementing an information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. The information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. Also, in the following embodiments, the same parts are denoted by the same reference numerals, and overlapping descriptions are omitted.

[1. Outline of information processing method]
First, an outline of an information processing method performed by an information processing apparatus according to an embodiment will be described with reference to FIG. FIG. 1 is an explanatory diagram showing an outline of an information processing method according to an embodiment. In FIG. 1, the information providing apparatus 100 provides a search query analysis tool. Further, the user U of the analysis tool wants to analyze the difference in search trends regarding the two keywords to be compared. In FIG. 1, the user U searches for "keyword #1", which is the company name of automobile company #1, and "keyword #2", which is the company name of automobile company #2 to be compared with automobile company #1. A case of analyzing differences in trends will be described as an example.

As shown in FIG. 1 , the information processing system 1 includes a terminal device 10 and an information providing device 100 . The terminal device 10 and the information providing device 100 are communicably connected to each other by wire or wirelessly via a network N (see FIG. 3).

The terminal device 10 is a smart device such as a smartphone or tablet used by the user U, and communicates with an arbitrary server device via a wireless communication network such as 4G (Generation) or LTE (Long Term Evolution). It is a portable terminal device that can The terminal device 10 has a screen such as a liquid crystal display, which has a touch panel function. Accepts various operations. An operation performed on an area where content is displayed on the screen may be an operation on the content. In addition, the terminal device 10 may be an information processing device such as a desktop PC (Personal Computer) or a notebook PC as well as a smart device.

In this embodiment, the terminal device 10 cooperates with the information providing device 100, and displays co-occurrence networks of categories based on two keywords input by the user U on a map mapping screen for co-occurring keywords. Display two keyword maps. A keyword map that shows a co-occurrence network of categories is a map of co-occurring keywords that is mapped so that co-occurrence relationships between keywords can be visually recognized after classifying each of multiple keywords into appropriate categories. . The terminal device 10 also displays a common keyword map that visualizes co-occurrence relationships between common keywords that are common to two keyword maps.

Note that a co-occurring keyword is a keyword that is searched at the same time as or close to the keyword to be searched. For example, a co-occurring keyword is a keyword related to a keyword to be searched, a keyword used for narrowing down search, or the like. A keyword that is frequently searched at the same time as or near the search target keyword is a co-occurring keyword that has a strong co-occurrence relationship with the search target keyword. The number of co-occurring keywords is not limited to one, and may be plural. For example, when three or more keywords are used at the same time or close to each other, the second and subsequent keywords may be co-occurring keywords of the first keyword.

For example, as shown in FIG. 1, the terminal device 10 determines a co-occurrence relationship between keywords by linking nodes indicating the respective keywords based on simultaneously searched (simultaneously input) keywords, the closeness of the searched times, and the like. A map KM1 (hereinafter sometimes referred to as keyword map KM1) and a map KM2 (hereinafter sometimes referred to as keyword map KM2) of the co-occurring keywords shown are generated and displayed. Here, the keyword map KM1 is a map that visualizes the co-occurrence relationship between co-occurring keywords searched at the same time as or close to "keyword #1" which is one of the two keywords received from the user. be. The keyword map KM2 is a map that visualizes the co-occurrence relationship between co-occurring keywords searched at the same time as or close to the other of the two keywords "keyword #2" received from the user. . Keywords having a co-occurrence relationship are mapped to close positions. Here, a node indicating a keyword is displayed as a figure (circle, rectangle, etc.), an icon, or the like. Also, the search volume of a keyword is represented by the size of a node. Co-occurrence relationships between keywords are represented by links connecting nodes.

In addition, as shown in FIG. 1, the terminal device 10 generates a common keyword map KM3 that visualizes co-occurrence relationships between common keywords that are common to the keyword map KM1 and the keyword map KM2. The terminal device 10 also displays the generated common keyword map KM3. In addition, the terminal device 10 includes the keyword maps KM1 and KM2 excluding the nodes corresponding to the common keywords in the common keywords and keyword maps KM1 and KM2 corresponding to the nodes included in the common keyword map KM3. displayed while maintaining the co-occurrence relationship between the node and the corresponding keyword (in other words, the connection relationship of the links connecting the nodes).

The information providing device 100 cooperates with the terminal device 10 of each user U, and provides the terminal device 10 of each user U with API services and the like for various applications and various data. and is realized by a server device, a cloud system, or the like.

In the present embodiment, the information providing apparatus 100 classifies keywords searched by an unspecified number of users using a search engine or the like into corresponding categories in advance, and calculates the search volume (the number of searches) for each keyword. Measure. At this time, the information providing apparatus 100 may create a learned model in advance by machine learning, which classifies and outputs a keyword into an appropriate category when the keyword is input. In addition, the information providing apparatus 100 presumes that keywords searched at the same time or close to each other are co-occurring keywords. Furthermore, the information providing apparatus 100 may calculate the degree of co-occurrence between keywords based on the number of times (frequency) that the keywords are searched at the same time or at close times, the closeness of the times when they were searched, and the like. Then, when the user U operates the terminal device 10 and uses a website or an application for map mapping of co-occurring keywords, information about categories and search volumes for each keyword and co-occurrence relationships between keywords is provided. do.

Also, the information providing device 100 may be an information processing device that provides some web service online to the terminal device 10 of each user U. FIG. For example, the information providing apparatus 100 provides web services such as Internet connection, search service, SNS (Social Networking Service), electronic commerce, electronic payment, online games, online banking, online trading, accommodation/ticket reservation, video/music distribution, and the like. service may be provided. In practice, the information providing apparatus 100 may cooperate with various servers that provide web services as described above and mediate web services.

Note that the information providing device 100 can acquire various types of information about the user U. FIG. For example, the information providing device 100 acquires information about attributes of the user U, such as the user's U gender, age, and area of residence. The information providing apparatus 100 stores and manages identification information indicating the user U (user ID, etc.) and information related to the attributes of the user U. FIG.

Further, the information providing apparatus 100 acquires various types of history information (log data) indicating actions of the user U from the terminal apparatus 10 of the user U or from various servers based on the user ID or the like. For example, the information providing device 100 acquires a location history, which is a history of the user U's location and date and time, from the terminal device 10 . The information providing apparatus 100 also acquires a search history, which is a history of search queries input by the user U, from a search server (search engine). Further, the information providing apparatus 100 acquires a viewing history, which is a history of content viewed by the user U, from the content server. In addition, the information providing apparatus 100 acquires the purchase history, which is the history of product purchases of the user U, from the electronic commerce server or the settlement server. Further, the information providing apparatus 100 may acquire the exhibition history and sales history, which are the history of the user U's exhibition in the marketplace, from the electronic commerce server or the settlement server. In addition, the information providing apparatus 100 acquires the posting history, which is the posting history of the user U, from a posting server that provides a word-of-mouth posting service or an SNS server.

In the present embodiment, the keywords searched by an unspecified number of users using a search engine or the like may be keywords included in the various types of history information (keywords appearing in the history information).

[1-1. basic action〕
For example, as shown in FIG. 1, the user U uses the terminal device 10 to access a website for map mapping of co-occurring keywords or activate an application, and on the screen for map mapping of co-occurring keywords, Two keywords are entered in two input fields (input boxes) (step S1). In FIG. 1, the user U enters "keyword #1", which is the company name of automobile company #1, in two input fields (input boxes) on the screen for map mapping of co-occurring keywords. "Keyword #2", which is the company name of automobile company #2 to be compared, is entered. In addition, the keywords to be entered are keywords that have been searched by an unspecified number of users in search engines, etc. (or there is a possibility that they are), and any character string such as words, combinations thereof, or phrases can be

Subsequently, the information providing apparatus 100 cooperates with the terminal device 10 to acquire two keywords input by the user U from the terminal device 10, and keywords having a co-occurrence relationship with each of the acquired two keywords (co-occurring keywords). ). For example, the information providing apparatus 100 estimates a keyword searched at the same time as or close to the acquired "keyword #1" as a co-occurring keyword of "keyword #1". In addition, the information providing apparatus 100 estimates a keyword searched at the same time as or close to the acquired "keyword #2" as a co-occurring keyword of "keyword #2". At this time, the information providing apparatus 100 may collect keywords searched at the same time or keywords searched at close times and register them in the database in advance. Then, the information providing apparatus 100 compares and collates each of the two acquired keywords with the keywords registered in the database, and presumes the corresponding keywords to be co-occurring keywords of each of the two keywords.

Subsequently, the information providing apparatus 100 estimates categories of the two acquired keywords. For example, the information providing apparatus 100 compares and collates each of the two acquired keywords with keywords classified in advance into categories, and classifies each of the two acquired keywords into the corresponding keyword category. At this time, the information providing apparatus 100 uses machine learning to create in advance a trained model that classifies an input keyword into an appropriate category and outputs it, and inputs each of the two acquired keywords into the trained model. , may be classified into corresponding categories and output.

In practice, the information providing apparatus 100 may estimate the category of the acquired keyword based not only on the acquired keyword, but also on the combination of the acquired keyword and the co-occurring keyword. For example, the information providing apparatus 100 compares and collates the set of the acquired keyword (for example, “keyword #1”) and the co-occurring keyword with the set of the previously categorized keyword and the co-occurring keyword, and acquires The pairs of keywords and co-occurring keywords obtained are classified into categories of corresponding pairs of keywords and co-occurring keywords. At this time, the information providing apparatus 100 uses machine learning to create in advance a trained model that, when a set of a keyword and a co-occurring keyword is input, classifies it into an appropriate category and outputs it. A combination with a keyword may be input to a learned model, classified into the corresponding category, and output.

Subsequently, the information providing apparatus 100 extracts the search volume of the keyword to be displayed. For example, the information providing apparatus 100 displays, as keywords to be displayed, the acquired keyword (for example, "keyword #1") and its co-occurring keywords, and the search volume of each of the keywords belonging to the same or related category as the acquired keyword. to extract At this time, the search volume may be measured for each keyword searched by an unspecified number of users using a search engine or the like, and registered in the database. Then, the information providing apparatus 100 compares and collates the keyword to be displayed with the keyword registered in the database, and extracts the search volume of the corresponding keyword.

Subsequently, the information providing apparatus 100 generates a keyword map KM1 related to the acquired "keyword #1" and a keyword map KM2 related to the acquired "keyword #2". Subsequently, the information providing device 100 acquires information regarding the keyword map KM1 and the keyword map KM2 (step S2).

Subsequently, when the information providing apparatus 100 acquires the information about the keyword maps KM1 and KM2, it identifies common keywords common to the keyword maps KM1 and KM2 (step S3). In the example shown in FIG. 1, the information providing apparatus 100 uses common keywords such as "CM", "stock price", "price", "light vehicle", "used vehicle", "new model", and "electric vehicle". Identify.

After specifying the common keywords, the information providing apparatus 100 then generates a common keyword map KM3 that visualizes the co-occurrence relationship between the common keywords (step S4).

Subsequently, the information providing device 100 provides the terminal device 10 with information necessary for controlling screen display for map mapping of co-occurring keywords (step S5). Alternatively, the information providing apparatus 100 cooperates with the terminal apparatus 10 to provide various data and instructions (commands, etc.) for controlling screen display for map mapping of co-occurring keywords, Control screen display.

Subsequently, the terminal device 10 cooperates with the information providing device 100 to display a keyword map KM1 showing co-occurrence networks of categories related to the two keywords input by the user U on the screen MC for map mapping of co-occurring keywords. And the keyword map KM2 and the common keyword map KM3 are displayed (step S6).

Subsequently, the terminal device 10 cooperates with the information providing device 100, and when the user U performs an operation to reproduce the keyword map showing the co-occurrence network of categories in chronological order, the keyword map KM1, the keyword map KM2, and the common The keyword map KM3 is reproduced in chronological order (step S7). For example, as shown in FIG. 1, when the user U presses the "time-series playback" button B1 displayed on the screen, the terminal device 10 displays a keyword map showing co-occurrence networks of categories in a time slider format. are played in chronological order. In the time-series-reproduced keyword map, the size of the node indicating the keyword changes according to the temporal change in the search volume of the keyword. In addition, the distance between nodes (link length) also changes according to the temporal change of the co-occurrence relationship between keywords.

Also, in the first displayed keyword map, you can browse by setting a period such as "last year", "2020", "2019", etc. However, since the search volume and the categories that can be divided differ depending on the year, how It's hard to tell what has changed. In order to visualize this process, we dynamically visualize changes in keyword search volume and categories in a time-slide format.

[1-2. Screen example]
Next, details of the screen of the terminal device according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram illustrating an example of a screen of the terminal device according to the embodiment; FIG. 2 is an enlarged view of the screen MC for map mapping of co-occurring keywords shown in FIG.

As shown in FIG. 2, the terminal device 10 cooperates with the information providing device 100 to display co-occurrence networks of categories related to two keywords input by the user U on a screen MC for map mapping of co-occurring keywords. Keyword map KM1, keyword map KM2, and common keyword map KM3 are displayed.

Here, in the common keyword map KM3 shown in FIG. 2, nodes corresponding to common keywords are indicated by circular figures. A circular figure indicating a node is composed of a pie chart inside the circle and an annulus along the outer circumference of the circle. The display unit 12 of the terminal device 10 displays such that the ratio of the ratio of the common keyword derived from each of the plurality of keyword maps is proportional to the length of the ring along the outer circumference of the circle indicating the node corresponding to the common keyword. Color-coded rings are displayed in .

For example, looking at the node corresponding to the common keyword "used car" shown in FIG. 2, the ring portion R1 and the remaining ring portion R2 are displayed in different colors. The display unit 12 of the terminal device 10 displays the percentage of the common keyword "used car" derived from the keyword maps KM1 and KM2, respectively, and the circle indicating the node corresponding to the common keyword "used car". Color-code the annulus in proportion to the length of the annulus along the outer circumference. Here, the fact that the common keyword "used car" is derived from the keyword map KM1 indicates that the common keyword "used car" was searched at the same time as or near the time of "keyword #1". Further, the fact that the common keyword "used car" is derived from the keyword map KM2 indicates that the common keyword "used car" was searched at the same time as or near the time of "keyword #2". For example, assuming that the common keyword "used car" is derived from both the keyword map KM1 and the keyword map KM2 at a rate of "1:1", a node corresponding to the common keyword "used car" is shown. The ring portion R1 obtained by dividing the length of the ring along the outer circumference of the circle at "1:1" and the remaining portion R2 of the ring are displayed in different colors.

Also, for example, if we focus on the node corresponding to the common keyword "used car" shown in FIG. The ratio of male to female searchers in the number of searches for the common keyword “used car” at the same time or in a close time is shown. For example, the area indicated by P1 in the pie chart indicates the ratio of male searchers among the number of searches in which the common keyword "used car" was searched at the same time as or close to "keyword #1". . In addition, the area indicated by P2 in the pie chart indicates the ratio of female searchers among the number of searches in which the common keyword "used car" was searched at the same time as or close to "keyword #1". .

Similarly, of the pie chart inside the circle, the portion corresponding to the remaining portion R2 of the circle is the number of searches for the common keyword “used car” at the same time as or close to “keyword #2”. Shows the male to female ratio of searchers in For example, the area indicated by P3 in the pie chart indicates the ratio of male searchers out of the number of searches in which the common keyword "used car" was searched at the same time as or close to "keyword #2". . In addition, the area indicated by P4 in the pie chart indicates the ratio of female searchers among the number of searches for the common keyword "used car" at the same time as or close to "keyword #2". .

Further, as shown in FIG. 2, the terminal device 10 cooperates with the information providing device 100 to display a keyword map KM1, a keyword map KM2, and a common keyword map KM3 on a screen MC for map mapping of co-occurring keywords in chronological order. Display a seek bar for playback on the screen. More specifically, the terminal device 10 displays a first icon PC1 that schematically shows all the reproduction positions of the keyword map KM1, the keyword map KM2, and the common keyword map KM3, and the icon that is reproduced by the terminal device 10 among the first icons PC1. A second icon PC2 schematically showing the playback position and the corresponding position are displayed as a seek bar. In other words, the second icon PC2 is a slider that indicates the current positions of the keyword map KM1, the keyword map KM2 and the common keyword map KM3. Also, the first icon PC1 is a slider bar, which is a bar-shaped area in which the slider can move. In FIG. 2, the keyword map KM1, keyword map KM2 and common keyword map KM3 as of 2020 are displayed.

Further, as shown in FIG. 2, the terminal device 10 displays each node corresponding to each common keyword included in the common keyword map KM3 inside a box indicating a category corresponding to each keyword. For example, focusing on the node corresponding to the common keyword "used car" shown in FIG. 2, the node corresponding to the common keyword "used car" is the category corresponding to the common keyword "used car". It is displayed inside the frame indicating "Hobby". Similarly, the terminal device 10 places the node corresponding to the common keyword "CM" included in the common keyword map KM3 inside the frame indicating the category "media" corresponding to the common keyword "CM". indicate. In addition, the terminal device 10 assigns each node corresponding to the common keywords "stock price" and "price" included in the common keyword map KM3 to the category "stock price" and "price" corresponding to the common keywords " Displayed inside the frame that indicates "business". In addition, the terminal device 10 assigns each node corresponding to the common keywords "light vehicle", "new model", and "electric vehicle" included in the common keyword map KM3 to the common keywords "light vehicle", " It is displayed inside the frame showing the category “hobby” corresponding to “new model” and “electric vehicle”.

Also, although illustration is omitted, when the user U clicks each node, the terminal device 10 displays additional information corresponding to each node. For example, when the user U clicks on each node, the terminal device 10 displays information on the date and time when each keyword corresponding to each node was first retrieved inside a balloon.

[2. Configuration example of information processing system]
Next, the configuration of the information processing system 1 including the information providing device 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. As shown in FIG. 3, the information processing system 1 according to the embodiment includes a terminal device 10 and an information providing device 100. As shown in FIG. These various devices are communicatively connected via a network N by wire or wirelessly. The network N is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet.

Also, the number of devices included in the information processing system 1 shown in FIG. 3 is not limited to the illustrated one. For example, only one terminal device 10 is shown in FIG. 3 for simplification of illustration, but this is only an example and is not limited, and two or more devices may be provided.

The terminal device 10 is an information processing device used by the user U. FIG. For example, the terminal device 10 may be a smart device such as a smartphone or a tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a game machine with a communication function, a car navigation system, a smart watch, or a head-mounted display. and other wearable devices, smart glasses, and the like.

In addition, the terminal device 10 is compatible with wireless communication networks such as LTE (Long Term Evolution), 4G (4th Generation), 5G (5th Generation: fifth generation mobile communication system), Bluetooth (registered trademark), wireless LAN (Local It is possible to communicate with the information providing apparatus 100 by connecting to the network N via short-range wireless communication such as Area Network).

The information providing device 100 is, for example, a PC, a server device, a mainframe, a workstation, or the like. Note that the information providing apparatus 100 may be realized by cloud computing.

[3. Configuration example of terminal device]
Next, the configuration of the terminal device 10 will be described with reference to FIG. FIG. 4 is a diagram showing a configuration example of the terminal device 10. As shown in FIG. As shown in FIG. 4, the terminal device 10 includes a communication unit 11, a display unit 12, an input unit 13, a positioning unit 14, a sensor unit 20, a control unit 30 (controller), and a storage unit 40. Prepare.

(Communication unit 11)
The communication unit 11 is connected to the network N (see FIG. 3) by wire or wirelessly, and transmits and receives information to and from the information providing apparatus 100 via the network N. FIG. For example, the communication unit 11 is implemented by a NIC (Network Interface Card), an antenna, or the like.

(Display unit 12)
The display unit 12 is a display device that displays various information such as position information. For example, the display unit 12 is a liquid crystal display (LCD) or an organic EL display (Organic Electro-Luminescent Display). Also, the display unit 12 is a touch panel display, but is not limited to this.

The display unit 12 also displays a plurality of keyword maps and a common keyword map received from the information providing device 100 under the control of the display control unit 34 .

(Input unit 13)
The input unit 13 is an input device that receives various operations from the user U. Further, the input unit 13 has, for example, buttons and the like for inputting characters, numbers, and the like. Moreover, when the display unit 12 is a touch panel display, a part of the display unit 12 functions as the input unit 13 . Note that the input unit 13 may be a microphone or the like that receives voice input from the user U. FIG. The microphone may be wireless.

(Positioning unit 14)
The positioning unit 14 receives signals (radio waves) transmitted from GPS (Global Positioning System) satellites, and based on the received signals, position information (for example, latitude and longitude). That is, the positioning unit 14 positions the position of the terminal device 10 . GPS is merely an example of GNSS (Global Navigation Satellite System).

Also, the positioning unit 14 can measure the position by various methods other than GPS. For example, the positioning unit 14 may measure the position using various communication functions of the terminal device 10 as described below as auxiliary positioning means for position correction and the like.

(Wi-Fi positioning)
For example, the positioning unit 14 measures the position of the terminal device 10 using the Wi-Fi (registered trademark) communication function of the terminal device 10 or the communication network provided by each communication company. Specifically, the positioning unit 14 performs Wi-Fi communication or the like and measures the position of the terminal device 10 by measuring the distance to a nearby base station or access point.

(beacon positioning)
The positioning unit 14 may also use the Bluetooth (registered trademark) function of the terminal device 10 to measure the position. For example, the positioning unit 14 measures the position of the terminal device 10 by connecting with a beacon transmitter connected by the Bluetooth (registered trademark) function.

(geomagnetic positioning)
Further, the positioning unit 14 positions the position of the terminal device 10 based on the geomagnetism pattern of the structure measured in advance and the geomagnetic sensor provided in the terminal device 10 .

(RFID positioning)
Further, for example, if the terminal device 10 has an RFID (Radio Frequency Identification) tag function equivalent to a contactless IC card used at station ticket gates, stores, etc., or has a function of reading an RFID tag In this case, the location used is recorded together with the information that the payment was made by the terminal device 10 . The positioning unit 14 may measure the position of the terminal device 10 by acquiring such information. Also, the position may be measured by an optical sensor provided in the terminal device 10, an infrared sensor, or the like.

The positioning unit 14 may measure the position of the terminal device 10 using one or a combination of the positioning means described above, if necessary.

(Sensor unit 20)
The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10 . The connection may be wired connection or wireless connection. For example, the sensors may be detection devices other than the terminal device 10, such as wearable devices and wireless devices. In the example shown in FIG. 4, the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, an atmospheric pressure sensor 23, an air temperature sensor 24, a sound sensor 25, an optical sensor 26, a magnetic sensor 27, and an image sensor ( camera) 28.

The sensors 21 to 28 described above are only examples and are not limited. That is, the sensor unit 20 may be configured to include a part of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or instead of the sensors 21 to 28. .

The acceleration sensor 21 is, for example, a three-axis acceleration sensor, and detects physical movements of the terminal device 10 such as movement direction, speed, and acceleration of the terminal device 10 . The gyro sensor 22 detects physical movements of the terminal device 10 such as inclination in three axial directions based on the angular velocity of the terminal device 10 and the like. The atmospheric pressure sensor 23 detects the atmospheric pressure around the terminal device 10, for example.

Since the terminal device 10 includes the above-described acceleration sensor 21, gyro sensor 22, barometric pressure sensor 23, etc., techniques such as pedestrian dead-reckoning (PDR: Pedestrian Dead-Reckoning) using these sensors 21 to 23, etc. , the position of the terminal device 10 can be determined. This makes it possible to acquire indoor position information that is difficult to acquire with a positioning system such as GPS.

For example, a pedometer using the acceleration sensor 21 can calculate the number of steps, walking speed, and distance walked. Further, by using the gyro sensor 22, it is possible to know the traveling direction, the direction of the line of sight, and the inclination of the body of the user U. Also, from the atmospheric pressure detected by the atmospheric pressure sensor 23, the altitude at which the terminal device 10 of the user U is present and the number of floors can be known.

The temperature sensor 24 detects the temperature around the terminal device 10, for example. The sound sensor 25 detects sounds around the terminal device 10, for example. The optical sensor 26 detects the illuminance around the terminal device 10 . The magnetic sensor 27 detects, for example, geomagnetism around the terminal device 10 . The image sensor 28 captures an image around the terminal device 10 .

The atmospheric pressure sensor 23, the temperature sensor 24, the sound sensor 25, the optical sensor 26, and the image sensor 28 described above detect the atmospheric pressure, temperature, sound, and illuminance, respectively, or capture an image of the surroundings to detect the terminal device 10. It is possible to detect the surrounding environment and situations. In addition, it is possible to improve the accuracy of the location information of the terminal device 10 based on the surrounding environment and situation of the terminal device 10 .

(control unit 30)
The control unit 30 includes, for example, a microcomputer having a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM, an input/output port, and various circuits. Also, the control unit 30 may be configured by hardware such as an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 30 includes a transmission unit 31 , a reception unit 32 , a processing unit 33 and a display control unit 34 .

(Sending unit 31)
The transmission unit 31 receives, for example, various information input by the user U using the input unit 13, various information detected by the sensors 21 to 28 mounted on or connected to the terminal device 10, and information measured by the positioning unit 14. The position information of the terminal device 10 and the like can be transmitted to the information providing device 100 via the communication unit 11 .

(Receiver 32)
The receiving unit 32 can receive various information provided by the information providing apparatus 100 and requests for various information from the information providing apparatus 100 via the communication unit 11 .

(Processing unit 33)
The processing unit 33 controls the entire terminal device 10 including the display unit 12 and the like. For example, the processing unit 33 can output various types of information transmitted by the transmitting unit 31 and various types of information received by the receiving unit 32 from the information providing apparatus 100 to the display unit 12 for display.

(Display control unit 34)
The display control unit 34 generates a plurality of keyword maps showing the co-occurrence relationship between the keywords by linking the nodes showing each keyword based on the keywords searched (simultaneously input) and the closeness of the searched time. displayed. Specifically, the display control unit 34 generates a plurality of keyword maps that visualize co-occurrence relationships between co-occurrence keywords searched at the same time as or close to each of the plurality of keywords received from the user. Keywords having a co-occurrence relationship are mapped to close positions. Here, a node indicating a keyword is displayed as a figure (circle, rectangle, etc.), an icon, or the like. Also, the search volume of a keyword is represented by the size of a node. Co-occurrence relationships between keywords are represented by links connecting nodes. Note that the display control unit 34 may be part of the processing unit 33 .

The display control unit 34 also generates and displays a common keyword map that visualizes co-occurrence relationships between common keywords common to a plurality of keyword maps. In addition to the common keyword map, the display control unit 34 also displays a plurality of keyword maps excluding the nodes corresponding to the common keyword, the common keywords corresponding to the nodes included in the common keyword map, and the nodes included in each of the plurality of keyword maps. is displayed while maintaining the co-occurrence relationship (in other words, the connection relationship of the links connecting the nodes) with the corresponding keyword. Here, a node indicating a common keyword is displayed as a circular figure, an icon, or the like. Also, the search volume of the common keyword is expressed by the size of the node. Co-occurrence relationships between common keywords are represented by links connecting nodes. Also, the ratio of the percentage of each common keyword derived from each of a plurality of keyword maps is expressed by color-coding the length of the ring along the outer circumference of the circle indicating the node. Also, the gender ratio of searchers in the number of searches for each common keyword is represented by a pie chart inside a circle indicating a node.

In addition, the display control unit 34 reproduces the plurality of keyword maps and the common keyword map in chronological order when the user U performs an operation to reproduce the plurality of keyword maps and the common keyword map of the category in chronological order. For example, when the user U presses a "time-series playback" button displayed on the screen, the display control unit 34 plays back multiple keyword maps and common keyword maps in time-slider format. In the time-series-reproduced keyword map, the size of the node indicating the keyword changes according to the temporal change in the search volume of the keyword. In addition, the distance between nodes (link length) also changes according to the temporal change of the co-occurrence relationship between keywords.

The display control unit 34 also displays each node corresponding to each common keyword included in the common keyword map inside a frame (box) indicating a category corresponding to each keyword. For example, the display control unit 34 generates and displays a frame (box) indicating the category corresponding to the common keyword based on the information of the category corresponding to the common keyword received from the information providing apparatus 100 by the receiving unit 32. . Subsequently, the display control unit 34 displays inside a frame (box) indicating the category corresponding to each keyword.

Further, when the user clicks each node, the display control unit 34 displays additional information corresponding to each node. For example, when the user clicks on each node, the display control unit 34 displays information on the date and time when each keyword corresponding to each node was first searched in a balloon.

(storage unit 40)
The storage unit 40 is realized by, for example, a semiconductor memory device such as RAM (Random Access Memory) or flash memory, or a storage device such as HDD (Hard Disk Drive), SSD (Solid State Drive), or optical disk. be. Various programs, various data, and the like are stored in the storage unit 40 .

[4. Configuration example of information providing device]
Next, the configuration of the information providing device 100 according to the embodiment will be described using FIG. FIG. 5 is a diagram showing a configuration example of the information providing device 100 according to the embodiment. As shown in FIG. 5, the information providing device 100 has a communication section 110, a storage section 120, and a control section .

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. Also, the communication unit 110 is connected to the network N (see FIG. 3) by wire or wirelessly.

(storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 5 , storage unit 120 has user information database 121 , history information database 122 , and keyword information database 123 .

(User information database 121)
The user information database 121 stores various information about the user U. FIG. For example, the user information database 121 stores various information such as user U attributes. FIG. 6 is a diagram showing an example of the user information database 121. As shown in FIG. In the example shown in FIG. 6, the user information database 121 has items such as "user ID (Identifier)", "age", "sex", "home", "place of work", and "interest".

“User ID” indicates identification information for identifying the user U. "Age" indicates the age of the user U identified by the user ID. Note that the “age” may be a specific age of the user U identified by the user ID, such as 35 years old. "Gender" indicates the gender of the user U identified by the user ID.

"Home" indicates location information of the home of the user U identified by the user ID. In the example shown in FIG. 6, "home" is represented by an abstract code such as "LC11", but may be latitude/longitude information or the like. Also, for example, "home" may be an area name or an address.

"Place of work" indicates location information of the place of work (school in the case of a student) of the user U identified by the user ID. In the example shown in FIG. 6, the "place of work" is illustrated as an abstract code such as "LC12", but may be latitude/longitude information or the like. Also, for example, the "place of work" may be an area name or an address.

"Interest" indicates the interest of the user U identified by the user ID. That is, "interest" indicates an object in which the user U identified by the user ID is highly interested. For example, the "interest" may be a search query (keyword) that the user U has entered into a search engine and searched for. In the example shown in FIG. 6, one "interest" is shown for each user U, but there may be more than one.

For example, in the example shown in FIG. 6, the age of the user U identified by the user ID "U1" is "twenties" and the gender is "male". Also, for example, the user U identified by the user ID "U1" indicates that the home is "LC11". Also, for example, the user U identified by the user ID "U1" indicates that the place of work is "LC12". Also, for example, the user U identified by the user ID "U1" indicates that he is interested in "sports".

Here, in the example shown in FIG. 6 , abstract values such as “U1”, “LC11” and “LC12” are used, but “U1”, “LC11” and “LC12” have specific values. It is assumed that information such as character strings and numerical values is stored. Hereinafter, abstract values may also be illustrated in diagrams relating to other information.

The user information database 121 is not limited to the above, and may store various types of information depending on the purpose. For example, the user information database 121 may store various types of information regarding the user U's terminal device 10 . In addition, the user information database 121 stores user U's demographics (demographic attributes), psychographics (psychological attributes), geographics (geographical attributes), behavioral attributes (behavioral attributes), etc. Information about attributes may be stored. For example, the user information database 121 includes name, family structure, hometown (local), occupation, position, income, qualification, residence type (detached house, condominium, etc.), presence or absence of car, commuting time, commuting time, commuting time. Information such as routes, commuter pass sections (stations, lines, etc.), frequently used stations (other than the nearest station to your home or place of work), lessons (places, time zones, etc.), hobbies, interests, lifestyle, etc. may

(History information database 122)
The history information database 122 stores various types of information related to history information (log data) indicating user U's actions. FIG. 7 is a diagram showing an example of the history information database 122. As shown in FIG. In the example shown in FIG. 7, the history information database 122 has items such as "user ID", "location history", "search history", "browsing history", "purchase history", and "posting history".

“User ID” indicates identification information for identifying the user U. "Position history" indicates a position history, which is a history of the user's U position and movement. Also, "search history" indicates a search history that is a history of search queries input by the user U. FIG. "Browsing history" indicates a browsing history that is a history of contents browsed by the user U. FIG. "Purchase history" indicates the purchase history of the user U's purchases. In addition, “posting history” indicates a posting history that is a history of posts by the user U. FIG. In addition, the “posting history” may include questions about user U's property.

For example, in the example shown in FIG. 7, the user U identified by the user ID "U1" moves along the "location history #1", searches along the "search history #1", and performs the "viewing". It indicates that the content was browsed according to the "Purchase history #1", the predetermined product etc. was purchased at the predetermined store etc. according to the "Purchase history #1", and the content was posted according to the "Posting history".

Here, in the example shown in FIG. 7, abstract history such as "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1" and "posting history #1" "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1" and "posting history #1" , information such as specific character strings and numerical values are stored.

Note that the history information database 122 may store various types of information, not limited to the above, depending on the purpose. For example, the history information database 122 may store the user U's usage history of a predetermined service. In addition, the history information database 122 may store the user U's store visit history, facility visit history, and the like. Also, the history information database 122 may store a history of user U's electronic payment and the like.

(Keyword information database 123)
The keyword information database 123 stores various information related to keywords searched by an unspecified number of people. FIG. 8 is a diagram showing an example of the keyword information database 123. As shown in FIG. In the example shown in FIG. 8, the keyword information database 123 has items such as "keyword", "co-occurrence keyword", "category", "search volume", and "degree of co-occurrence".

"Keyword" indicates a keyword searched by an unspecified number of users using a search engine or the like. Also, "co-occurring keyword" indicates a co-occurring keyword of the keyword. For example, a co-occurring keyword is a keyword that is searched at the same time as or close to the keyword in question. Also, when there is no co-occurring keyword (eg, when a search is performed using only a single keyword), the column for that co-occurring keyword is blank. "Category" indicates the category to which the keyword belongs. Note that the categories may be classified by a set of the keyword and the co-occurring keyword. "Search volume" indicates the search volume (the number of searches) of the keyword. Note that the search volume may be measured for each set of the keyword and the co-occurring keyword. In this case, the total value of the search volumes measured for each set of the keyword and the co-occurring keyword is the search volume of the keyword itself. "Co-occurrence degree" indicates the degree of co-occurrence between the keyword and the co-occurrence keyword. Note that the degree of co-occurrence may be calculated based on the search volume of the keyword. In addition, when there is no co-occurrence keyword (when a search is performed using only a single keyword, etc.), the co-occurrence degree column is blank.

For example, in the example shown in FIG. 8, "keyword #1" is searched together with "co-occurring keyword #11", is classified into "category #11", has "search volume #11", and is associated with the co-occurring keyword. The degree of co-occurrence is “co-occurrence #11”.

Here, in the example shown in FIG. 8, abstract values such as "keyword #1", "co-occurrence keyword #11", "category #11", "search volume #11", and "co-occurrence degree #11" are , specific character strings and numerical values and other information are stored.

It should be noted that the keyword information database 123 may store various types of information, not limited to the above, depending on the purpose. For example, the keyword information database 123 may store information on the total value of search volumes (the search volume of the keyword itself) measured for each set of the keyword and the co-occurring keyword. Further, the keyword information database 123 may store information on categories of co-occurring keywords together with the categories of the keywords. The keyword information database 123 may also store information on the number of PV (Page Views), CTR (Click Through Rate), CVR (Conversion Rate), etc. of the website selected as the search result of the keyword.

(control unit 130)
Returning to FIG. 5, the description is continued. The control unit 130 is a controller, and for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like controls the information providing apparatus 100. Various programs (corresponding to an example of an information processing program) stored in the internal storage device are executed by using a storage area such as a RAM as a work area. In the example shown in FIG. 5, the control unit 130 includes an acquisition unit 131, an estimation unit 132, a measurement unit 133, a reception unit 134, an extraction unit 135, an identification unit 136, a generation unit 137, and a provision unit 138. and

(Acquisition unit 131)
Acquisition unit 131 acquires, from various servers and the like via communication unit 110, information related to keywords used by user U for searching with a search engine or the like.

At this time, the acquiring unit 131 acquires various information about the user U from the terminal device 10, various servers, and the like via the communication unit 110. FIG. For example, the acquisition unit 131 acquires information indicating the user U (user ID, etc.), location information of the user U, attribute information of the user U, and the like. Acquisition unit 131 then registers in user information database 121 of storage unit 120 .

In addition, the acquisition unit 131 acquires various types of history information (log data) indicating actions of the user U from various servers and the like via the communication unit 110 . Acquisition unit 131 then registers in history information database 122 of storage unit 120 .

The keyword used by the user U for searching with a search engine or the like may be a keyword included in various types of history information (keyword appearing in history information).

In addition, the acquisition unit 131 acquires information about each of the plurality of keyword maps corresponding to each of the plurality of keywords received by the reception unit 134 . For example, the acquisition unit 131 acquires information about co-occurring keywords and search volumes for each of the multiple keywords extracted by the extraction unit 135, categories corresponding to each of the received multiple keywords, and the like.

(Estimation unit 132)
The estimation unit 132 estimates a co-occurring keyword for each keyword searched by an unspecified number of users using a search engine or the like. For example, the estimation unit 132 estimates keywords searched at the same time or at close times as co-occurring keywords. Then, the estimating unit 132 registers in the keyword information database 123 of the storage unit 120 .

In addition, the estimation unit 132 estimates a corresponding category for each keyword searched by an unspecified number of users using a search engine or the like. Then, the estimating unit 132 registers in the keyword information database 123 of the storage unit 120 . For example, the estimating unit 132 compares and collates the acquired keyword with keywords classified into categories in advance, and classifies the acquired keyword into the corresponding category of the keyword. At this time, the estimating unit 132 may create a learned model in advance by machine learning, which, when a keyword is input, classifies it into an appropriate category and outputs it.

For example, the estimation unit 132 creates a trained model for classifying keyword categories by machine learning using RNN (Recurrent Neural Network), LSTM (Long short-term memory), or the like. As for the model, a model of any type and any format can be adopted. For example, the estimation unit 132 may adopt SVM (Support Vector Machine) or DNN (Deep Neural Network) as a model. Here, DNN may be CNN (Convolutional Neural Network) or RNN. The model may also be a model realized by combining a plurality of models, such as a model combining CNN and RNN.

Note that the RNN and LSTM may be neural networks based on an attention mechanism. Also, the estimation unit 132 may use a similar natural language processing model. Data mining and other machine learning algorithms may also be used. The estimating unit 132 can perform model learning using the various learning methods described above.

In practice, the estimating unit 132 may estimate the keyword category based on a combination of the keyword and the co-occurring keyword instead of the keyword alone.

(Measuring unit 133)
The measurement unit 133 measures the search volume for each keyword searched by an unspecified number of users using a search engine or the like. For example, the measurement unit 133 counts the number of searches for the keyword based on the information about the keyword used by the user U for searching with a search engine or the like obtained from a search server or the like, the search history, or the like. Then, the measurement unit 133 registers in the keyword information database 123 of the storage unit 120 .

At this time, the measurement unit 133 may measure the search volume of a combination of the keyword and the co-occurring keyword instead of the search volume of the keyword alone.

The measurement unit 133 also calculates the degree of co-occurrence between keywords based on the search volume of a set of a keyword and a co-occurring keyword searched by an unspecified number of users using a search engine or the like. Then, the measurement unit 133 registers in the keyword information database 123 of the storage unit 120 .

(Reception unit 134)
The accepting unit 134 accepts a plurality of keywords input by the user U from the terminal device 10 via the communication unit 110 . For example, the receiving unit 134 receives a plurality of keywords respectively input into a plurality of input fields (input boxes) on the map mapping screen for co-occurring keywords.

(Extraction unit 135)
The extraction unit 135 compares and collates each of the received multiple keywords with the keywords registered in the keyword information database 123, and extracts the co-occurrence keywords and search volumes of each of the received multiple keywords, and the degree of co-occurrence between the keywords. , extracts information about the category to which each of the received multiple keywords belongs. The category to which each of the received keywords belongs may be estimated by the estimation unit 132 based on the received keywords. The extracted various information becomes information necessary for controlling the screen display of the UI for map mapping of co-occurring keywords.

(Specifying unit 136)
The identifying unit 136 identifies common keywords common to the plurality of keyword maps acquired by the acquiring unit 131 . For example, the specifying unit 136 compares the co-occurring keywords of each of the multiple keywords acquired by the acquiring unit 131, and specifies a co-occurring keyword common to both as a common keyword.

(Generating unit 137)
The generating unit 137 generates a common keyword map that visualizes the co-occurrence relationship between the common keywords identified by the identifying unit 136 . For example, the generation unit 137 merges nodes corresponding to common keywords included in each of the plurality of keyword maps acquired by the acquisition unit 131 . Subsequently, the generation unit 137 moves the merged nodes to the display area of the common keyword map while maintaining the connection relationship with other nodes included in each of the plurality of keyword maps.

(Providing unit 138)
When the generating unit 137 generates the common keyword map, the providing unit 138 transmits the information about the plurality of keyword maps acquired by the acquiring unit 131 and the common keyword map generated by the generating unit 137 to the terminal device 10 via the communication unit 110 . Submit information about keyword maps.

In addition, the providing unit 138 provides the terminal device 10 with information necessary for controlling screen display of a UI for map mapping of co-occurring keywords via the communication unit 110 . Alternatively, the providing unit 138 cooperates with the terminal device 10 via the communication unit 110 to provide various data and instructions (commands, etc.) for controlling the screen display, and the UI screen for map mapping of co-occurring keywords. Control display.

[5. Processing procedure]
Next, processing procedures by the terminal device 10 and the information providing device 100 according to the embodiment will be described with reference to FIG. FIG. 9 is a flow chart showing a processing procedure according to the embodiment. The processing procedure described below is repeatedly executed by the control unit 30 of the terminal device 10 and the control unit 130 of the information providing device 100 .

As shown in FIG. 9, the acquisition unit 131 of the information providing apparatus 100 acquires information about keywords used by the user U for searching with a search engine or the like from various servers or the like via the communication unit 110 (step S101).

Subsequently, the estimating unit 132 of the information providing apparatus 100 estimates a co-occurring keyword for each keyword searched by an unspecified number of users using a search engine or the like (step S102). For example, the estimation unit 132 estimates keywords searched at the same time or at close times as co-occurring keywords. Then, the estimating unit 132 registers in the keyword information database 123 of the storage unit 120 .

Subsequently, the estimation unit 132 of the information providing apparatus 100 estimates a corresponding category for each keyword searched by an unspecified number of users using a search engine or the like (step S103). For example, the estimating unit 132 uses machine learning to create in advance a trained model that classifies and outputs a keyword into an appropriate category when the keyword is input, inputs the acquired keyword into the trained model, and classifies the keyword into the appropriate category. Categorize and output. At this time, the estimating unit 132 uses machine learning to create in advance a trained model that, when a set of a keyword and a co-occurring keyword is input, classifies it into an appropriate category and outputs it. may be input to the trained model, and may be output after being classified into the corresponding category. Then, the measurement unit 133 registers in the keyword information database 123 of the storage unit 120 .

Subsequently, the measurement unit 133 of the information providing apparatus 100 measures the search volume for each keyword searched by an unspecified number of users using a search engine or the like (step S104). At this time, the measurement unit 133 may measure the search volume of a combination of the keyword and the co-occurring keyword instead of the search volume of the keyword alone. The measurement unit 133 may also calculate the degree of co-occurrence between keywords based on the search volume of a set of a keyword and a co-occurring keyword searched by an unspecified number of users using a search engine or the like. . Then, the measurement unit 133 registers in the keyword information database 123 of the storage unit 120 .

Subsequently, when the receiving unit 134 of the information providing apparatus 100 accesses a map mapping site for co-occurring keywords or starts an application from the terminal device 10 via the communication unit 110, the user U Using the input unit 13 of 10, a plurality of keywords respectively input into a plurality of input fields (input boxes) on the map mapping screen for co-occurring keywords are received (step S105).

Subsequently, the extraction unit 135 of the information providing apparatus 100 compares and collates each of the received multiple keywords with the keywords registered in the keyword information database 123, and extracts co-occurring keywords and search results for each of the received multiple keywords. Information related to volume, category corresponding to each of the received multiple keywords, etc. is extracted (step S106). Note that the category corresponding to each of the received multiple keywords may be estimated by the estimation unit 132 described above. Further, if there is information about the degree of co-occurrence between keywords, the extracting unit 135 may also extract information about the degree of co-occurrence.

Subsequently, the acquisition unit 131 of the information providing apparatus 100 acquires information on each of the plurality of keyword maps corresponding to each of the received plurality of keywords (step S107). For example, the acquisition unit 131 of the information providing apparatus 100 acquires information about co-occurring keywords and search volumes of each of the multiple keywords extracted by the extraction unit 135, categories corresponding to each of the received multiple keywords, and the like.

Subsequently, the identifying unit 136 of the information providing apparatus 100 identifies a common keyword common to the plurality of acquired keyword maps (step S108). For example, the specifying unit 136 of the information providing device 100 compares the co-occurring keywords of the respective keywords acquired by the acquiring unit 131, and specifies a co-occurring keyword common to both as a common keyword.

Subsequently, the generation unit 137 of the information providing apparatus 100 generates a common keyword map that visualizes the co-occurrence relationship between the identified common keywords (step S109). For example, the generation unit 137 of the information providing apparatus 100 merges nodes corresponding to common keywords included in each of the plurality of keyword maps. Subsequently, the generation unit 137 of the information providing apparatus 100 moves the merged nodes to the display area of the common keyword map while maintaining the connection relationship with other nodes included in each of the plurality of keyword maps. When the common keyword map is generated, the providing unit 138 of the information providing apparatus 100 transmits information about a plurality of keyword maps and information about the common keyword map to the terminal device 10 .

Subsequently, the processing unit 33 of the terminal device 10 displays a plurality of keyword maps and a common keyword map on the display unit 12 based on the information received from the information providing device 100 via the receiving unit 32 (step S110). At this time, the providing unit 138 of the information providing device 100 provides the terminal device 10 with information necessary for controlling the screen display of the UI for map mapping of co-occurring keywords via the communication unit 110. . Alternatively, the providing unit 138 cooperates with the terminal device 10 via the communication unit 110 to provide various data and instructions (commands, etc.) for controlling the screen display, and the UI screen for map mapping of co-occurring keywords. Control display.

Subsequently, the display control unit 34 of the terminal device 10 displays the plurality of keyword maps and the common keyword map in chronological order when the user U performs an operation to reproduce the plurality of keyword maps and the common keyword map of the category in chronological order. Play back (step S111). For example, when the user U presses a "time-series playback" button displayed on the screen, the display control unit 34 plays back multiple keyword maps and common keyword maps in time-slider format.

[6. Modification]
The terminal device 10 and the information providing device 100 described above may be implemented in various different forms other than the above embodiments. So, below, the modification of embodiment is demonstrated.

In the above embodiment, the processing executed by the information providing device 100 may actually be executed by the terminal device 10 . That is, the processing may be completed standalone (by the terminal device 10 alone). In this case, it is assumed that the terminal device 10 has the functions of the information providing device 100 in the above embodiment.

In the above embodiment, the estimating unit 132 of the information providing apparatus 100 creates in advance a trained model for estimating and outputting co-occurring keywords when a keyword is input by machine learning. Accepted keywords may be input to a trained model, and co-occurring keywords may be estimated and output.

Further, in the above embodiment, the terminal device 10 may measure the number of times a keyword is input by the user U on the map mapping screen for co-occurring keywords as the search volume. In addition, the terminal device 10 may estimate, as co-occurring keywords, keywords that are input by the user U at the same time or close to each other on the map mapping screen for co-occurring keywords.

[7. effect〕
As described above, the information processing device (the terminal device 10 and the information providing device 100) according to the present application includes the acquisition unit 131, the identification unit 136, the generation unit 137, and the display unit 12. The acquisition unit 131 is a plurality of keyword maps that visualize co-occurrence relationships between keywords by connecting keywords having co-occurrence relationships and a plurality of corresponding nodes, and the co-occurrence relationships between keywords with different input conditions. Get multiple keyword maps that visualize The identifying unit 136 identifies common keywords common to a plurality of keyword maps. The generation unit 137 generates a common keyword map that visualizes co-occurrence relationships between common keywords. The display unit 12 associates the common keyword map and a plurality of keyword maps excluding the nodes corresponding to the common keywords with the common keywords corresponding to the nodes included in the common keyword map and the nodes included in the plurality of keyword maps. Display the co-occurrence relationship with the keyword in a visualized state.

In addition, the display unit 12 displays a circle so that the ratio of the percentage of common keywords derived from each of a plurality of keyword maps and the length of the ring along the outer circumference of the circle indicating the nodes corresponding to the common keywords are proportional to each other. Display rings in different colors.

In addition, the display unit 12 displays a pie chart indicating the gender ratio of searchers who searched for the common keyword inside the circle indicating the node corresponding to the common keyword.

In addition, the display unit 12 displays nodes corresponding to the common keywords inside the frames indicating the categories into which the common keywords are classified.

Moreover, the display unit 12 displays the additional information of the common keyword when the node corresponding to the common keyword is selected by the user. For example, the display unit 12 displays, as additional information, information indicating the date and time when the common keyword was first searched.

In addition, the display unit 12 visualizes chronological changes in the multiple keyword maps and the common keyword map. For example, the display unit 12 reproduces a plurality of keyword maps and a common keyword map in chronological order in a time slider format.

The information processing apparatus according to the present application can obtain useful information by any one or a combination of the processes described above. For example, the information processing apparatus provides the user with information on co-occurrence relationships between co-occurrence keywords specific to each of the two keywords to be compared, and co-occurrence relationships between common keywords common to the two keywords to be compared. Information that visualizes relationships can be provided. Thereby, the information processing device enables the user to grasp at a glance the similarities and differences in the search trends regarding the two keywords to be compared. In addition, the information processing device enables the user to perform a deeper analysis of search trends regarding two keywords to be compared.

In addition, the information processing device visualizes chronological changes in a plurality of keyword maps and a common keyword map in a time slider format, so that the user can identify common points and differences in search trends for two keywords to be compared. It makes it possible to analyze the time of occurrence and the time of disappearance along the time series. Thereby, the information processing device enables the user to perform a deeper analysis of the search trends regarding the two keywords to be compared.

[8. Hardware configuration]
Also, the terminal device 10 and the information providing device 100 according to the above-described embodiments are implemented by a computer 1000 configured as shown in FIG. 10, for example. Hereinafter, the terminal device 10 will be described as an example. FIG. 10 is a diagram illustrating an example of a hardware configuration; The computer 1000 is connected to an output device 1010 and an input device 1020, and an arithmetic device 1030, a primary storage device 1040, a secondary storage device 1050, an output I/F (Interface) 1060, an input I/F 1070, and a network I/F 1080 are buses. It has a form connected by 1090.

The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and the like, and executes various processes. The arithmetic unit 1030 is implemented by, for example, a CPU (Central Processing Unit), MPU (Micro Processing Unit), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), or the like.

The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used for various calculations by the arithmetic device 1030 . The secondary storage device 1050 is a storage device in which data used for various calculations by the arithmetic device 1030 and various databases are registered. State Drive), flash memory, or the like. The secondary storage device 1050 may be an internal storage or an external storage. Also, the secondary storage device 1050 may be a removable storage medium such as a USB memory or an SD (Secure Digital) memory card. Also, the secondary storage device 1050 may be a cloud storage (online storage), a NAS (Network Attached Storage), a file server, or the like.

The output I/F 1060 is an interface for transmitting information to be output to the output device 1010 that outputs various information such as a display, a projector, and a printer. (Digital Visual Interface), HDMI (registered trademark) (High Definition Multimedia Interface), and other standardized connectors. Also, the input I/F 1070 is an interface for receiving information from various input devices 1020 such as a mouse, keyboard, keypad, buttons, scanner, etc., and is realized by, for example, USB.

Also, the output I/F 1060 and the input I/F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, the output device 1010 and the input device 1020 may be wireless devices.

Also, the output device 1010 and the input device 1020 may be integrated like a touch panel. In this case, the output I/F 1060 and the input I/F 1070 may also be integrated as an input/output I/F.

Note that the input device 1020 includes, for example, optical recording media such as CDs (Compact Discs), DVDs (Digital Versatile Discs), PDs (Phase change rewritable discs), magneto-optical recording media such as MOs (Magneto-Optical discs), and tapes. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like.

Network I/F 1080 receives data from other devices via network N and sends the data to arithmetic device 1030, and also transmits data generated by arithmetic device 1030 via network N to other devices.

Arithmetic device 1030 controls output device 1010 and input device 1020 via output I/F 1060 and input I/F 1070 . For example, arithmetic device 1030 loads a program from input device 1020 or secondary storage device 1050 onto primary storage device 1040 and executes the loaded program.

For example, when the computer 1000 functions as the terminal device 10 , the arithmetic device 1030 of the computer 1000 implements the functions of the control unit 30 by executing programs loaded on the primary storage device 1040 . Further, arithmetic device 1030 of computer 1000 may load a program acquired from another device via network I/F 1080 onto primary storage device 1040 and execute the loaded program. Further, the arithmetic unit 1030 of the computer 1000 may cooperate with another device via the network I/F 1080, and call functions, data, etc. of the program from another program of the other device for use.

[9. others〕
Although the embodiments of the present application have been described above, the present invention is not limited by the contents of these embodiments. In addition, the components described above include those that can be easily assumed by those skilled in the art, those that are substantially the same, and those within the so-called equivalent range. Furthermore, the components described above can be combined as appropriate. Furthermore, various omissions, replacements, or modifications of components can be made without departing from the gist of the above-described embodiments.

Further, among the processes described in the above embodiments, all or part of the processes described as being automatically performed can be manually performed, or the processes described as being performed manually can be performed manually. All or part of this can also be done automatically by known methods. In addition, information including processing procedures, specific names, 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 drawing is not limited to the illustrated information.

Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the illustrated one, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

For example, the information providing apparatus 100 described above may be implemented by a plurality of server computers, and depending on the function, may be implemented by calling an external platform or the like using an API (Application Programming Interface), network computing, or the like. can be changed flexibly.

Also, the above-described embodiments and modifications can be appropriately combined within a range that does not contradict the processing content.

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

1 information processing system 10 terminal device 12 display unit 34 display control unit 100 information providing device 121 user information database 122 history information database 123 keyword information database 131 acquisition unit 132 estimation unit 133 measurement unit 134 reception unit 135 extraction unit 136 identification unit 137 Generating unit 138 Providing unit

Claims (8)

A plurality of keyword maps that visualize co-occurrence relationships between keywords by connecting keywords having co-occurrence relationships and a plurality of corresponding nodes, wherein the co-occurrence relationships between keywords with different input conditions are visualized. an acquisition unit for acquiring a keyword map of
an identification unit that identifies a common keyword common to the plurality of keyword maps;
a generation unit that generates a common keyword map that visualizes the co-occurrence relationship between the common keywords;
The common keyword map and the plurality of keyword maps excluding the nodes corresponding to the common keywords are associated with the common keywords corresponding to the nodes included in the common keyword map and the nodes included in the plurality of keyword maps. a display section for displaying the co-occurrence relationship with the keyword in a visualized state;
with
The display unit
chronologically reproducing the plurality of keyword maps and the common keyword map in a time slider format;
An information processing device characterized by: The display unit
Displaying a pie chart showing the gender ratio of searchers who searched for the common keyword inside the circle indicating the node corresponding to the common keyword;
The information processing apparatus according to claim 1, characterized by: The display unit
displaying a node corresponding to the common keyword inside a frame indicating a category into which the common keyword is classified;
3. The information processing apparatus according to claim 1, wherein: The display unit
displaying additional information of the common keyword when a user selects a node corresponding to the common keyword;
4. The information processing apparatus according to any one of claims 1 to 3, characterized by: The display unit
displaying, as the additional information, information indicating the date and time when the common keyword was first searched;
5. The information processing apparatus according to claim 4, characterized by: The display unit
Visualizing chronological changes in the plurality of keyword maps and the common keyword map;
6. The information processing apparatus according to any one of claims 1 to 5, characterized by: A computer-executed information processing method comprising:
A plurality of keyword maps that visualize co-occurrence relationships between keywords by connecting keywords having co-occurrence relationships and a plurality of corresponding nodes, wherein the co-occurrence relationships between keywords with different input conditions are visualized. an obtaining step of obtaining a keyword map of
an identifying step of identifying a common keyword common to the plurality of keyword maps;
a generation step of generating a common keyword map that visualizes the co-occurrence relationship between the common keywords;
The common keyword map and the plurality of keyword maps excluding the nodes corresponding to the common keywords are associated with the common keywords corresponding to the nodes included in the common keyword map and the nodes included in the plurality of keyword maps. a display step of displaying the co-occurrence relationship with the keyword in a visualized state;
including
In the display step,
chronologically reproducing the plurality of keyword maps and the common keyword map in a time slider format;
An information processing method characterized by: A plurality of keyword maps that visualize co-occurrence relationships between keywords by connecting keywords having co-occurrence relationships and a plurality of corresponding nodes, wherein the co-occurrence relationships between keywords with different input conditions are visualized. an acquisition procedure for acquiring the keyword map of
an identifying procedure for identifying a common keyword common to the plurality of keyword maps;
a generating procedure for generating a common keyword map that visualizes co-occurrence relationships between the common keywords;
The common keyword map and the plurality of keyword maps excluding the nodes corresponding to the common keywords are associated with the common keywords corresponding to the nodes included in the common keyword map and the nodes included in the plurality of keyword maps. a display procedure for displaying the co-occurrence relationship with the keyword in a visualized state;
on the computer, and
In the display procedure ,
chronologically reproducing the plurality of keyword maps and the common keyword map in a time slider format;
An information processing program characterized by:

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