WO2015182391A1 - Information processing device, information processing method, and program - Google Patents

Abstract

The present technology relates to an information processing device, an information processing method, and a program that enable presentation of useful information to a user. A presentation information generation unit generates presentation information, which is information to be presented to a user, on the basis of the level of knowledge of the user with respect to one or more items. The presentation information generation unit supplies the generated presentation information to a presentation control unit. The presentation control unit controls the presentation of the presentation information supplied from the presentation information generation unit. The present technology is applicable to portable information terminals, such as smartphones, tablets, and portable telephone machines.

Description

Information processing apparatus, information processing method, and program

The present technology relates to an information processing device, an information processing method, and a program, and more particularly, to an information processing device, an information processing method, and a program that can present appropriate information to a user.

Conventionally, collaborative filtering, content-based filtering, and the like have been used as a method for recommending information that meets user preferences (see, for example, Patent Document 1).

JP 2009-266096 A

However, even if the information meets the user's preference, for example, information known to the user or information difficult to understand is recommended, it is not very useful for the user.

This technology has been made in view of such a situation, and makes it possible to present useful information to the user.

An information processing apparatus according to an aspect of the present technology provides a presentation information generation unit that generates presentation information that is information to be presented to the user based on the degree of knowledge of the user with respect to one or more items, and presents the presentation information. Provided with a presentation control unit to control.

The presentation information generation unit can generate the presentation information for the user based on a difference in the degree of knowledge of the item between the user and the other user.

The presentation information generation unit can further generate the presentation information to the user based on the user and other users' preference for the item.

In the presentation information generation unit, based on the difference in the degree of knowledge of the item of the user and the other user, the preference level of the user and the other user is selected from the items having a predetermined level or more. A topic recommended to the user with the other user can be selected, and the presentation information including the recommended topic can be generated.

In the presentation information generation unit, a user who recommends the user to the user among the other users based on a difference in the degree of knowledge with respect to the item having a preference level of the user and the other user equal to or higher than a predetermined level. The presentation information including the recommended user can be generated by selection.
Based on the difference in the degree of knowledge about the item between the user and the other user, the presentation information generation unit includes a topic recommended to the user among the other user from the items. The presentation information including the recommended topic can be generated by selection.

The presentation information generation unit can further select the recommended topic based on the relationship between the user and the other user.

The presentation information generation unit can further select the recommended topic based on the situation of the user and the other user.

The presentation information generation unit can generate the presentation information including information indicating a degree of knowledge of the other user with respect to the recommended topic.

The presentation information generation unit is configured to select a user to be recommended to the user from among the other users based on a difference in the degree of knowledge of the item between the user and the other user, and to select the recommended user. The presenting information including can be generated.

The presentation information generation unit can select the recommended user from other users who have knowledge from the user for the specified item.

It is possible to further provide a communication unit that communicates with another information processing apparatus and acquires information indicating the degree of knowledge of the item of the other user from the other information processing apparatus.

The presentation information generation unit can further generate the presentation information to the user based on the user's preference for the item.

The presentation information generating unit causes the user to select an item to be presented to the user from the items based on a degree of knowledge and a preference degree of the user with respect to the item, and includes the presentation information including information on the selected item. Can be generated.

A learning unit that learns the degree of knowledge of the user by the item can be further provided.

The presentation control unit can control presentation of the presentation information in another information processing apparatus.

A presentation unit that presents the presentation information may be further provided, and the presentation control unit may control presentation of the presentation information in the presentation unit.

An information processing method according to an aspect of the present technology includes a presentation information generation step of generating presentation information that is information to be presented to the user based on a degree of knowledge of the user with respect to one or more items, and presentation of the presentation information. And a presentation control step for controlling.

A program according to an aspect of the present technology controls a presentation information generation step of generating presentation information, which is information to be presented to the user, based on a degree of knowledge of the user with respect to one or more items, and presentation of the presentation information. Causing the computer to execute a process including a presentation control step.

In one aspect of the present technology, presentation information that is information to be presented to the user is generated based on the degree of knowledge of the user with respect to one or more items, and the presentation of the presentation information is controlled.

According to one aspect of the present technology, useful information can be presented to the user.

It should be noted that the effects described here are not necessarily limited, and may be any of the effects described in the present disclosure.

1 is a block diagram illustrating an embodiment of an information processing system to which the present technology is applied. It is a block diagram which shows the structural example of the function of a server. It is a block diagram which shows the structural example of the function of a client. It is a flowchart for demonstrating 1st Embodiment of a topic recommendation process. It is a figure which shows the example of table type knowledge and preference information and integrated knowledge and preference information. It is a figure which shows the example of tree type knowledge and preference information. It is a figure which shows the example of tree type integrated knowledge and preference information. It is a figure which shows the 1st example of a display of presentation information. It is a figure which shows the 2nd example of a display of presentation information. It is a figure which shows the 3rd example of a display of presentation information. It is a flowchart for demonstrating 2nd Embodiment of a topic recommendation process. It is a flowchart for demonstrating a user recommendation process. It is a figure for demonstrating the specific example of a user recommendation process. It is a flowchart for demonstrating an information presentation process. It is a figure for demonstrating the specific example of an information presentation process. It is a figure which shows the 4th example of a display of presentation information. It is a figure for demonstrating the 1st learning method of the detail with respect to each item of a user. It is a figure for demonstrating the 2nd learning method of the detail with respect to each item of a user. It is a block diagram which shows the structural example of a computer.

Hereinafter, modes for carrying out the present technology (hereinafter referred to as embodiments) will be described.

<Embodiment>
{Configuration example of information processing system 1}
FIG. 1 shows a configuration example of an information processing system 1 that is an embodiment of an information processing system to which the present technology is applied.

The information processing system 1 recommends, for example, topics to other users or other users suitable for providing desired information to each user, or information that matches each user's knowledge and preferences. It is a system that can be presented.

The information processing system 1 is configured to include a server 11 and clients 12-1 and 12-2. In this figure, only one server and two clients are shown for easy understanding, but the number of servers and clients is not particularly limited and can be set to an arbitrary number. .

The server 11 and the clients 12-1 and 12-2 are connected via a network 13 constituted by the Internet or the like, and can communicate with each other. In addition, the client 12-1 and the client 12-2 can communicate with each other via the network 13 or not via the network 13. Note that the server 11 and the client 12-1 or 12-2 can directly communicate with each other without going through the network 13.

In the following description, when it is not necessary to distinguish the clients 12-1 and 12-2 from each other, they are simply referred to as clients 12.

For example, the server 11 is suitable for providing topics recommended to other users and desired information based on knowledge / preference information indicating details and preference levels of one or more items of each user. Presentation information including information indicating other users is generated. Moreover, the server 11 produces | generates the presentation information containing the information suitable for each user's knowledge and preference based on the knowledge and preference information of the user of each client 12, for example. Then, the server 11 transmits the generated presentation information to the client 12.

Each client 12 includes, for example, a smartphone, a tablet, a mobile phone, a laptop personal computer, a desktop personal computer, or the like. Each client 12 receives the presentation information transmitted from the server 11 via the network 13, for example, and presents the received presentation information.

Each client 12 receives the knowledge / preference information of another user from the other client 12, and recommends between the user of the client 12 and the other user based on the knowledge / preference information of the other user. The presentation information including the topic to be generated is generated. Moreover, each client 12 produces | generates the presentation information containing the information suitable for the knowledge and preference of the user based on the knowledge and preference information of the user of the said client 12, for example. Then, the client 12 presents the generated presentation information to the user.

It should be noted that the items of knowledge / preference information are not particularly limited, and any item that can set the user's details and preference can be used. A specific example of knowledge / preference information will be described later with reference to FIGS.

{Example of configuration of function of server 11}
FIG. 2 shows a configuration example of functions of the server 11. The server 11 is configured to include a communication unit 51, a calculation unit 52, and a storage unit 53. The calculation unit 52 is configured to include a learning unit 61, a presentation information generation unit 62, and a presentation control unit 63.

The communication unit 51 communicates with each client 12 via the network 13 and transmits / receives various information to / from each client 12. In addition, the communication unit 51 supplies information received from each client 12 to the calculation unit 52 and acquires information to be transmitted to each client 12 from the calculation unit 52.

It should be noted that the communication unit 51 can employ any communication method regardless of wired or wireless.

The learning unit 61 learns the knowledge and preference of each user according to a predetermined method, generates knowledge / preference information of each user based on the learning result, and stores it in the storage unit 53. Note that, for example, the learning unit 61 may acquire the knowledge / preference information of each user from each client 12 instead of generating the knowledge / preference information by itself.

The presentation information generation unit 62 generates presentation information to be presented to each user based on the knowledge / preference information of each user stored in the storage unit 53 and other various information. The presentation information generation unit 62 supplies the generated presentation information to the presentation control unit 63.

The presentation control unit 63 transmits the presentation information to each client 12 via the communication unit 51 and the network 13, and causes each client 12 to present the presentation information.

The storage unit 53 stores the knowledge / preference information of each user, various information that can be presented to each user, and the like.

{Configuration example of client 12 function}
FIG. 3 shows a functional configuration example of the client 12. The client 12 is configured to include a communication unit 71, a calculation unit 72, an input unit 73, a presentation unit 74, and a storage unit 75. The calculation unit 72 is configured to include a learning unit 81, a presentation information generation unit 82, and a presentation control unit 83.

The communication unit 71 communicates with the server 11 via the network 13 and transmits / receives various information to / from the server 11. In addition, the communication unit 71 communicates with other clients 12 via the network 13 or not via the network 13, and transmits / receives various information to / from the other clients 12. The communication unit 71 supplies information received from the server 11 and other clients 12 to the calculation unit 72, and acquires information to be transmitted to the server 11 or other clients 12 from the calculation unit 72.

Note that any communication method can be adopted as the communication method of the communication unit 71 regardless of wired or wireless. For example, the communication unit 71 performs short-range wireless communication such as NFC (Near Field Communication) with other clients 12.

The learning unit 81 learns the knowledge and preferences of the user who uses the client 12 according to a predetermined method, generates the knowledge / preference information of the user based on the learning result, and stores the knowledge / preference information in the storage unit 75. Note that, for example, the learning unit 81 may acquire the knowledge / preference information of the user from the server 11 instead of generating the knowledge / preference information of the user himself / herself.

The presentation information generation unit 82 generates the presentation information to be presented to the user based on the user's knowledge / preference information stored in the storage unit 75 and other various information. The presentation information generation unit 82 supplies the generated presentation information to the presentation control unit 83.

The presentation control unit 83 controls the presentation information received from the server 11 and the presentation information supplied from the presentation information generation unit 82 by the presentation unit 74. In addition, the presentation control unit 83 controls presentation by the presentation unit 74 such as a screen for using the client 12 and voice.

The transmission control unit 84 acquires information to be transmitted to the server 11 or another client 12 from the storage unit 75 and transmits the information via the communication unit 71.

The input unit 73 is configured by various input devices such as a keyboard, a mouse, a key, a button, and a microphone, and is used by a user to operate or input information. The input unit 73 supplies information indicating the operation contents of the user and input information to the calculation unit 72.

The presentation unit 74 includes, for example, a device for presenting visual information such as a display to the user, and a device for presenting auditory information such as an audio reproduction device, a speaker, and an audio output terminal to the user. Then, for example, the presentation unit 74 presents presentation information or presents a screen, sound, or the like for using the client 12 under the control of the presentation control unit 83.

The storage unit 75 stores knowledge / preference information of the user of the client 12 and various information that can be presented to the user.

{Processing of information processing system 1}
Next, processing of the information processing system 1 will be described with reference to FIGS. 4 to 18.

(First embodiment of topic recommendation processing)
First, the topic recommendation process executed by the client 12-1 will be described with reference to the flowchart of FIG. Hereinafter, a case where the user of the client 12-1 recommends a topic to the target user when communicating with the user of the client 12-2 will be described as an example. In addition, hereinafter, a user (in this case, a user of the client 12-1) as a target for presenting presentation information is referred to as a target user, and a user (in this case, a user of the client 12-2) with whom the target user communicates is a partner. Called.

This process is executed, for example, when the target user directly meets and communicates with the other party. Further, for example, this processing is started when a predetermined operation is performed in the client 12-1 in a state where the client 12-1 can directly communicate with the client 12-2 without going through the network 13.

In step S1, the client 12-1 acquires the knowledge / preference information of the other party. Specifically, the communication unit 71 of the client 12-1 communicates with the communication unit 71 of the client 12-2 and requests transmission of the partner's knowledge / preference information.

The transmission control unit 84 of the client 12-2 transmits the knowledge / preference information of the user (that is, the other party) of the client 12-2 stored in the storage unit 75 to the client 12-1 via the communication unit 71.

The communication unit 71 of the client 12-1 receives the partner's knowledge / preference information from the client 12-2 and supplies the received partner's knowledge / preference information to the presentation information generation unit 83.

In step S2, the presentation information generation unit 82 of the client 12-1 integrates the knowledge and preference information of the target user and the partner. That is, the presentation information generation unit 82 acquires the knowledge / preference information of the target user from the storage unit 75 and integrates it with the partner's knowledge / preference information received from the client 12-2.

Here, a specific example of the processing in step S2 will be described with reference to FIGS.

FIG. 5 shows an example of table-type knowledge / preference information. An example of the knowledge / preference information of the target user is shown in the upper left of FIG. 5, an example of the knowledge / preference information of the partner is shown in the lower left, and the knowledge / preference information of the target user and the partner is shown on the right. An example of integrated integrated knowledge / preference information is shown.

The knowledge / preference information of each user includes information indicating the user's details and preference for each item.

The details are represented by five levels from 1 to 5, each of which is set to a larger value as the user becomes more detailed about the target item, and set to a smaller value as the user becomes less sparse about the target item. For example, if the user's knowledge of the target item is a general average level, the value of detail is set to 3. Also, for example, if the user's knowledge of the target item exceeds the average level, the value of detail is set to 4, and the user is very detailed or has expert knowledge about the target item. In this case, the value of detail is set to 5. Further, for example, when the user's knowledge about the target item is below the average level, the detail value is set to 2, and when there is little user knowledge about the target item, the detail value is 1 Set to

Like the details, the degree of preference is also represented by five levels from 1 to 5, each being set to a larger value as the user's preference or interest in the target item is stronger, and a smaller value as the preference or interest is weaker. Set to For example, if the user's preference or interest in the target item is a general average level, the preference level is set to 3. Also, for example, when the user's preference or interest for the target item exceeds the average level, the preference level is set to 4, and when the user's preference or interest for the target item is very strong, the preference level is Set to 5. Furthermore, for example, when the user's preference or interest in the target item is below the average level, the preference level is set to 2, and when the user dislikes the target item or is almost indifferent, the preference level Is set to 1.

Therefore, by using this knowledge / preference information, it is possible to know the degree of knowledge for each item in addition to the degree of preference for each item of each user. For example, the detail value of the target user for baseball is set to 5, and the preference level is set to 5. Therefore, it can be seen that the target user likes baseball and is very detailed. Also, for example, the detail value for the opponent's movie is set to 1 and the preference level is set to 3. Therefore, it can be seen that the other party is interested in the movie as much as possible but has little knowledge.

Then, the presentation information generation unit 82 generates integrated knowledge / preference information by integrating the knowledge / preference information of the target user and the other party. At this time, the presentation information generation unit 82 calculates the difference between the details of the target user and the other party for the same item. Therefore, the integrated knowledge / preference information includes information indicating the degree of preference for each item of the target user and the partner, and the difference in detail between the target user and the partner.

For example, the value of the detail of the target user for the car is 1, and the preference level is 3. On the other hand, the value of the detail of the opponent with respect to the car is 5, and the preference level is 5. Therefore, in the integrated knowledge / preference information, the value of the difference in detail with respect to the car is set to 4, the target user's preference level is set to 3, and the opponent's preference level is set to 5.

Also, for example, the value of the detail of the target user for the camp is 3, and the preference level is 4. On the other hand, the details and preference of the other party to the camp are unknown. In this case, the detail value and the preference level of the opponent for the camp are each set to 0. In other words, it is considered that the opponent has no interest in the camp and has no knowledge. Therefore, in the integrated knowledge / preference information, the detail difference with respect to the camp is set to 3, the target user's preference level is set to 4, and the opponent's preference level is set to 0.

In addition, you may make it attach | subject a positive / negative code | symbol to the value of the difference of detail so that the case where a target user is more detailed than a partner and the case where a partner is more detailed than a target user can be identified. For example, when the target user is more detailed than the partner, the detail difference may be expressed as a positive value, and when the partner is more detailed than the target user, the detail difference may be expressed as a negative value.

FIG. 6 shows an example of tree-type knowledge / preference information. The upper side of FIG. 6 shows an example of the knowledge / preference information of the target user, and the lower side shows an example of the other party's knowledge / preference information.

In this example, item names are shown in each node of the tree. In addition, items go up to a higher concept (aggregate) as you go up the tree, and items go down to a lower concept (subdivide) as you go down. For example, from the “sports” node, subordinate concepts “baseball” and “soccer” are branched.

Also, in the knowledge / preference information of the target user, a node with detailed items that the target user likes (or is interested in) has a diagonal line with a narrow left-down interval. In addition, a node of an item that the target user likes (or is interested in) but is not familiar with is displayed with a diagonal line with a wide left-down interval. Thereby, for example, it is understood that the target user likes baseball and is detailed, likes a car but is not detailed. In addition, diagonal lines are not displayed in the nodes of other items. The other items are items that the target user does not like, or items in which at least one of the detail and preference level of the target user is unknown.

On the other hand, in the partner's knowledge / preference information, nodes with detailed items that the partner likes (or is interested in) are displayed with diagonal lines with narrow right-down intervals. In addition, a node of an item that the partner likes (or is interested in) but is not familiar with is indicated by a diagonal line with a wide interval at the lower right. Thereby, for example, it can be seen that the opponent likes soccer and is detailed, likes a movie but is not detailed. Similarly to the knowledge / preference information of the target user, the nodes of other items are not displayed with diagonal lines.

Then, the presentation information generation unit 82 generates integrated knowledge / preference information by integrating the knowledge / preference information of the target user and the other party. FIG. 7 shows an example of integrated knowledge / preference information obtained by integrating the target user and the partner's knowledge / preference information of FIG.

In this example, the knowledge and preference for the item of the target user are shown on the left half of each node, and the knowledge and preference for the item of the other party are shown on the right half of each node.

For example, the left half of the baseball node is displayed with a narrow diagonal line with a lower left interval, and the right half is not displayed with a diagonal line. Also, for example, the right half of a soccer node has a narrow diagonal line with a lower right-down interval, and the left half has no diagonal line. Therefore, it can be seen that, for baseball and soccer, one likes and is detailed, but the other does not like or at least one of detail and preference is unknown. On the other hand, the left half of the sports node is displayed with a wide diagonal line with a lower left interval, and the right half is displayed with a wide diagonal line with a lower right interval. Therefore, it can be seen that both are interested in sports in general, which is a superordinate concept of baseball and soccer, but are not detailed.

Also, for example, the left half of the car node has a diagonal line with a wide left-down interval, and the right half has a diagonal line with a narrow right-down interval. Therefore, it can be seen that both are interested in the car and only one (ie, the other party) is detailed.

Furthermore, for example, the left half of the wine node is displayed with a narrow diagonal line with a lower left interval, and the right half is displayed with a wide diagonal line with a lower right interval. Therefore, it is clear that both are interested and detailed about wine.

In this way, by referring to the integrated knowledge / preference information, it is possible to easily grasp the difference between the detail and the preference level for each item of the target user and the other party.

Returning to FIG. 4, in step S <b> 3, the presentation information generation unit 82 of the client 12-1 determines the detail and preference level for each item of the target user and the partner, and the difference in detail for each item of the target user and the partner. Based on this, the recommended topic is selected.

For example, when the table-type integrated knowledge / preference information of FIG. 5 is used, the presentation information generation unit 82 selects a recommended topic from items whose preference levels of the target user and the other party are equal to or higher than a predetermined threshold. For example, when the main purpose is to provide information from one to the other, the presentation information generation unit 82 provides details of the target user and the partner from items whose preference levels of the target user and the partner are equal to or higher than a predetermined threshold. Items whose difference is equal to or greater than a predetermined threshold are selected as recommended topics.

For example, when the threshold value for the preference level and the threshold value for the difference in detail are set to 3, respectively, “car” is selected as the recommended topic. In this case, both are more interested in cars than the average level. Further, while the opponent is very detailed about the car, the target user has little knowledge about the car. Therefore, when the target user talks about the car with the other party, the other party can talk about the car that is very interested and detailed, and the target user has the knowledge of the car that is interested but not detailed. You can expect to get. As a result, communication between the target user and the other party becomes smooth, and the target user can be expected to obtain useful information from the other party.

On the contrary, for example, the target user and the partner may be selected as a topic that recommends an item in which the target user is interested in more than the average level and the target user is familiar and the partner is not familiar with. As a result, the target user can talk about an interesting and detailed topic, and the other party can be expected to obtain knowledge about an interesting but not detailed topic. As a result, communication between the target user and the other party is facilitated, and the target user can be expected to be provided with useful information for the other party.

In addition, for example, when the main purpose is to discuss or exchange information, or to have a deep story, the presentation information generation unit 82 selects items whose preference between the target user and the other party is greater than or equal to a predetermined threshold. Then, an item in which the details of the target user and the partner are equal to or larger than a predetermined threshold and the difference in the details of the target user and the partner is equal to or smaller than the predetermined threshold is selected as a recommended topic.

For example, when the threshold for preference and the threshold for detail are each set to 3 and the threshold of detail difference is set to 1, “wine” is selected as the recommended topic. In this case, both of them are more interested in wine than ordinary people, and are familiar with the target user and the partner's wine. Therefore, it can be expected that when the target user talks about wine with the other party, the talk is lost, communication between the target user and the other party becomes smooth, and useful information can be exchanged with each other.

At this time, a plurality of items may be selected as recommended topics.

Also, for example, recommended topics may be switched according to conditions.

For example, the recommended topic may be switched according to the relationship between the target user and the other party. For example, if the partner is the boss of the target user, select a hard topic such as economy preferentially, and if the partner is a subordinate of the target user, select a soft topic such as sports or entertainment preferentially You may make it do. Thereby, the target user can select an appropriate topic in accordance with the relationship with the other party.

Also, for example, the recommended topic may be switched according to the situation of the target user and the other party. For example, when both are in a company, a hard topic may be preferentially selected, and when both are in a bar, a soft topic may be preferentially selected. Further, for example, general topics such as weather and traffic may be preferentially selected in the morning, and specialized topics such as economy and sports may be preferentially selected at night. Further, for example, topics related to work may be preferentially selected on weekdays, and topics related to leisure may be preferentially selected on weekends. Thereby, the target user can select a topic suitable for the situation where the target user or the other party is placed.

Furthermore, for example, a topic that is popular at that time or a topic that has a high freshness level may be preferentially selected. For example, in the Olympic season, topics related to the Olympics may be preferentially selected, and in the election season, topics related to elections may be preferentially selected. Further, for example, even in the same genre, a popular topic (for example, popular entertainment information) may be preferentially selected. For example, new topics and popular topics are topics that many people want to know or teach. Also, even if you are not usually interested, many people are interested in new or trending topics. Therefore, it can be expected that the target user will be more interested by selecting the seasonal topic recommended by the target user.

Moreover, in the above description, the example which selects the topic to recommend from the item whose target user and the other party's preference level are more than a predetermined threshold was shown, but for example, one of the preference levels is more than a predetermined threshold It is also possible to select a recommended topic from among the items. Further, for example, it is possible to select a topic to be recommended based only on the difference in detail between the target user and the partner without considering the degree of preference between the target user and the partner.

In step S4, the presentation information generation unit 82 of the client 12-1 generates presentation information including a recommended topic. That is, the presentation information generation unit 82 generates presentation information for presenting the recommended topic selected in the process of step S3 to the target user. The presentation information generation unit 82 supplies the generated presentation information to the presentation control unit 83. Note that the presentation information may include, for example, information indicating the detail and preference of the target user and the partner with respect to the recommended topic, and the detail difference between the target user and the partner.

In step S5, the presentation unit 74 of the client 12-1 presents the presentation information under the control of the presentation control unit 83, and the topic recommendation process ends. Here, an example of a presentation information presentation method will be described with reference to FIGS. 8 to 10.

8 to 10 show examples of presentation information displayed on the display when the client 12-1 is a portable information terminal such as a smartphone or a mobile phone and the presentation unit 74 is a display.

In the example of FIG. 8, a car is presented as a topic to recommend with the other party (Mr. A). Thereby, the target user can appropriately select a topic with the other party, and as a result, communication can be facilitated.

In the example of FIG. 9, the content of the topic to be recommended is shown in more detail than the example of FIG. That is, as a topic with the partner (Mr. A), an outside car is recommended among cars. As a result, the target user can appropriately narrow down the topic with the other party, and as a result, communication can be facilitated.

In the example of FIG. 10, along with the topic to recommend, the other party's knowledge level for the topic is presented. Thereby, the target user can appropriately select the topic with the other party and can set the content related to the topic to an appropriate level. As a result, for example, it is possible to avoid the target user from talking too much difficult for the other party or only talking about the other party already knowing.

It should be noted that the method of presenting the recommended topic is not limited to these examples, and other methods can be employed.

For example, a plurality of recommended topics may be presented. Further, when recommending a plurality of topics, for example, the topics may be presented in order of recommendation. Thereby, the choice of a topic spreads, for example, the object user can select the topic which suits both preference more, or can change a topic appropriately in the middle.

In addition, for example, when the client 12 can output a voice, the presentation information may be presented by voice in addition to visually presenting the presentation information.

In this way, the target user can quickly obtain useful information such as an appropriate topic with the other party by a simple operation. Further, since the recommended topic is selected based on not only the preference of both but also the detail, it is possible to recommend a topic more suitable for both.

(Second embodiment of topic recommendation processing)
Next, the topic recommendation process executed by the information processing system 1 will be described with reference to the flowchart of FIG. Hereinafter, a case where the server 11 recommends a topic to the target user when the user (target user) of the client 12 communicates with a desired partner will be described as an example.

This process enables, for example, a topic to be recommended to the target user even when the target user communicates without directly meeting the other party. This process is started when the target user performs a predetermined operation on the client 12 and designates a desired partner, for example.

In step S51, the transmission control unit 84 of the client 12 transmits the target user and the user ID of the other party via the communication unit 71. Here, the user ID is an ID given in advance to uniquely identify each user.

In step S52, the communication unit 51 of the server 11 receives the target user and the partner user ID transmitted from the client via the network 13. The communication unit 51 supplies the received target user and the user ID of the other party to the presentation information generation unit 62.

In step S53, the presentation information generation unit 62 of the server 11 integrates the knowledge and preference information of the target user and the partner. Specifically, the presentation information generation unit 62 acquires knowledge / preference information of the target user and the partner from the storage unit 53 based on the user IDs of the target user and the partner. Then, the presentation information generation unit 62 integrates the knowledge / preference information of the target user and the other party and generates integrated knowledge / preference information by the same processing as step S2 in FIG.

In step S54, the presentation information generation unit 62 of the server 11 performs the same process as in step S3 of FIG. 4 to provide details and preference levels for each item of the target user and the partner, and details for each item of the target user and the partner. A recommended topic is selected based on the difference in strength.

In step S55, the presentation information generation unit 62 of the server 11 generates presentation information including a recommended topic by the same process as in step S4 of FIG. The presentation information generation unit 62 supplies the generated presentation information to the presentation control unit 63.

In step S56, the presentation control unit 63 of the server 11 transmits the presentation information to the client 12 via the communication unit 51, and the processing of the server 11 ends.

In step S57, the communication unit 71 of the client 12 receives the presentation information transmitted from the server 11 via the network 13. The communication unit 71 supplies the received presentation information to the presentation control unit 83.

In step S58, presentation information is presented in the same manner as in step S5 of FIG. 4, and the processing of the client 12 ends.

Thereby, the target user can easily and quickly obtain useful information such as an appropriate topic with the other party without simply meeting with the other party by simply specifying the desired party. Then, the target user can establish a good relationship with the partner through the recommended topic using means such as social media or e-mail. Further, for example, when the target user meets with the partner at a later date, the target user can establish a good relationship with the partner through the recommended topic.

(User recommendation process)
Next, user recommendation processing executed by the information processing system 1 will be described with reference to the flowchart of FIG. This process is a process of recommending a user suitable for providing information desired by the target user.

In step S101, the client 12 requests the recommendation of a user who can provide desired information. Specifically, the target user inputs an item for which he / she wants to obtain information (hereinafter referred to as a designated item) via the input unit 73 of the client 12. The transmission control unit 84 generates request information for requesting the recommendation of a user who can provide information related to the specified item input by the target user. The transmission control unit 84 transmits the generated request information via the communication unit 71.

Hereinafter, as shown in FIG. 13, a case where the target user desires information about wine and inputs wine as a specified item will be described as a specific example.

In step S102, the server 11 receives a recommendation request from a user who can provide desired information. That is, the communication unit 51 of the server 11 receives the request information transmitted from the client 12 via the network 13. The communication unit 51 supplies the received request information to the presentation information generation unit 62.

In step S103, the presentation information generation unit 62 of the server 11 selects a user to be recommended based on the knowledge / preference information of each user. For example, the presentation information generation unit 62 extracts, from the knowledge / preference information of each user including the target user stored in the storage unit 53, information indicating the detail and preference level of each user with respect to an item that matches the specified item. To do. Then, the presentation information generation unit 62 selects a user who is more detailed about the specified item than the target user and whose preference for the item is equal to or higher than a predetermined threshold as a user recommended to the target user.

For example, in the case of the example of FIG. On the other hand, user C is more familiar with wine than user B, but user C's preference for wine is 1, which is very low. Therefore, for example, when the threshold value for the preference level is set to 4, the user B is selected.

Thus, a user who is not only familiar with wine but also has a high preference for wine is selected. For example, a user who is familiar with wine and likes a topic about wine is selected. On the other hand, for example, users who are not very familiar with wine and users who do not like wine-related topics are excluded from the selection. Thereby, the target user can expect to obtain useful information about wine from the recommended users.

In step S104, the presentation information generation unit 62 of the server 11 generates presentation information including a recommended user. That is, the presentation information generation unit 62 generates presentation information for presenting the user selected in the process of step S103 to the client 12. The presentation information generation unit 62 supplies the generated presentation information to the presentation control unit 63. The presentation information may include, for example, information indicating the detail and preference of the target user and the partner with respect to the specified item, and the detail difference between the target user and the partner.

In step S105, the server 11 transmits the presentation information as in the process of step S56 in FIG. 11, and the process of the server 11 ends.

In steps S106 and S107, the client 12 receives the presentation information and presents the received presentation information in the same manner as the processing in steps S57 and S58 of FIG. 11, and the processing of the client 12 ends.

Thereby, the target user can quickly obtain useful information as a user suitable for providing information desired by the user by a simple operation. Thereafter, the target user can obtain desired information by communicating with the recommended user.

It should be noted that a threshold value may be provided not only for the degree of preference but also for details. For example, you may make it recommend from a target user the user who is detailed about a designated item and whose detail value and preference degree with respect to a designated item are more than a predetermined threshold value, respectively. Alternatively, for example, the condition that it is more detailed than the target user may be removed, and a user who simply has a detail value and a preference level for a specified item may be recommended.

Also, for example, it is possible to select a recommended user based only on the details of the specified item without considering the preference level.

Furthermore, for example, the range of searching for recommended users may be limited. For example, the search range may be limited to friends or acquaintances of the target user on social media.

Further, the number of users recommended for the target user may be two or more. For example, the recommendation level may be calculated based on the details and the preference level for the designated item, and a predetermined number of users may be recommended in descending order of the recommendation level. In this case, the recommended users may be presented to the target user so that the order of recommendation can be understood.

Furthermore, information indicating the details and the preference level of the designated item of the user to be recommended may be presented to the target user.

Also, for example, it is possible to recommend a user who desires information that can be provided by the target user. For example, when a target user inputs soccer as a designated item, it is possible to search for a user who has less knowledge than the target user and who has a preference level equal to or higher than a predetermined threshold, and can recommend it to the target user. is there. In this case, for example, a user who is very interested in soccer but is not familiar with soccer is recommended as the target user.

Then, the target user can provide useful information about soccer to the recommended user by communicating with the recommended user. Thereby, for example, it becomes possible to satisfy the desire of the target user who wants to share the knowledge he possesses with others, or to expand the friendship of the target user through the knowledge he possesses.

Furthermore, for example, it is possible to recommend a user who is suitable for the target user to discuss or exchange information on a desired topic. For example, when the target user inputs jazz as the designated item, the user is searched for a user whose difference in detail with respect to the jazz is within a predetermined threshold and whose preference is equal to or higher than the predetermined threshold. It is possible to recommend to users. In this case, for example, a user who likes jazz and has similar knowledge about jazz as the target user is recommended to the target user. And the target user can perform information exchange and discussion about the user and jazz by communicating with the recommended user.

Further, for example, the target user may input two or more items (for example, soccer, world cup) as designated items, and the server 11 may select a user to be recommended based on the two or more designated items. Is possible.

Furthermore, for example, the target user may input a sentence or phrase (for example, “I want to know about Kyoto temples”), and the server 11 or the client 12 may extract a specified item from the input sentence or phrase. And you may make it the server 11 select the user to recommend based on the extracted designation | designated item.

Further, for example, the knowledge / preference information of the target user may be transmitted from the client 12 to the server 11 together with the target user and the other user ID.

Further, for example, knowledge / preference information of other users may be accumulated in advance in the client 12 of the target user, and the client 12 may recommend the user alone.

(Information provision processing)
Next, information presentation processing executed by the information processing system 1 will be described with reference to the flowchart of FIG. This process is a process in which the server 11 presents information that matches the knowledge and preference of the target user for a predetermined item.

In step S151, the client 12 transmits the knowledge / preference information of the target user. Specifically, the transmission control unit 84 of the client 12 acquires the knowledge / preference information of the target user from the storage unit 75, and transmits the acquired knowledge / preference information via the communication unit 71.

In step S152, the communication unit 51 of the server 11 receives the knowledge / preference information of the target user transmitted from the client 12 via the network 13. The communication unit 51 supplies the acquired knowledge / preference information to the presentation information generation unit 62.

In step S153, the presentation information generation unit 62 of the server 11 selects information to be presented based on the knowledge / preference information of the target user. Here, a specific example of step S153 will be described with reference to FIG. In this example, the server 11 is shown as an agent 101 that holds various information related to Kinkakuji and presents it to the user.

For example, when the target user is the user D, the user D has a detail value of 1 for Kinkakuji and a preference level of 3. That is, the user D has a level of interest in Kinkakuji but has little knowledge. Therefore, the agent 101 selects information regarding the outline of Kinkakuji as information presented to the user D.

Also, for example, when the target user is the user E, the user E has a detail value of 3 for Kinkakuji and a preference level of 4. The user E has a detail value of 2 for the building and a preference level of 5. That is, the user E has a level of knowledge about Kinkakuji and is more interested than a general person. Moreover, although the user is not so familiar with architecture, the user is more interested than the general public. Therefore, the agent 101 selects information related to the architectural form of the temple of Kinkakuji as information to be presented to the user E.

Also, for example, when the target user is the user F, the user F has a detail value of 5 for Kinkakuji and a preference level of 5. The user F has a detail value of 3 for literature and a preference level of 4. That is, the user F is very knowledgeable and interested in Kinkakuji. Moreover, the user F has human knowledge about literature, and has a higher interest than a general person. Therefore, the agent 101 assumes that the user F knows almost all information related to the Kinkakuji alone, and selects information related to the relationship between Kinkakuji and the writer Yukio Mishima as information to be presented to the user F.

In step S154, the presentation information generation unit 62 of the server 11 generates presentation information including the selected information. That is, the presentation information generation unit 62 generates presentation information for presenting the information selected in the process of step S153 to the client 12. The presentation information generation unit 62 supplies the generated presentation information to the presentation control unit 63.

In step S155, as in the process of step S56 of FIG. 11, the server 11 transmits the presentation information, and the process of the server 11 ends.

In steps S156 and S157, similar to the processing in steps S57 and S58 in FIG. 11, the client 12 receives the presentation information, presents the received presentation information, and the processing of the client 12 ends. For example, in the example described above with reference to FIG. 15, as illustrated in FIG. 16, a screen explaining the outline of Kinkakuji is displayed on the client 12 of the user D.

Thereby, based on the details and preferences of the target user for the subject item (for example, Kinkakuji) and the related items (for example, architecture and literature), among the information related to the subject item, Information useful for the target user is presented. For example, information in which the target user is interested and understandable is presented. On the other hand, for example, information that is not very useful to the target user such as information that the target user does not show interest, information that the target user already knows, information that is difficult to understand is prevented from being presented.

This process can be applied to, for example, providing information about a predetermined item such as a place, a product, a performer, an event, etc. to a user at a specific place such as a sightseeing spot, a commercial facility, an amusement facility, or an event venue. For example, the target user holds a portable information terminal (client 12) such as a smartphone near the communication antenna of the information terminal (server 11) installed at a predetermined location. Then, the portable information terminal of the target user communicates with the information terminal, and the above-described processing is performed. Information related to the predetermined item and corresponding to the knowledge and preference of the target user is presented on the portable information terminal of the target user.

Note that, for example, the knowledge / preference information of the target user stored in advance in the server 11 may be used without transmitting the knowledge / preference information of the target user from the client 12 to the server 11.

{About knowledge / preference information generation method}
Next, an example of a method for generating knowledge / preference information will be described. Note that the degree of preference of each user for each item can be learned using various methods such as collaborative filtering and content-based filtering. Thus, a method for obtaining details of each item of each user will be mainly described below.

For example, each user may input details for each item by a questionnaire or the like, and set the detail value of the knowledge / preference information of each user based on the information.

Further, for example, the learning unit 61 of the server 11 or the learning unit 81 of the client 12 predicts the details for each item of each user based on the occupation, educational background, place of residence, hometown, etc. of each user. Also good. For example, for an item related to the user's occupation, the user can be predicted to be very detailed.

Further, for example, the learning unit 61 or the learning unit 81 may learn details about each item of each user based on a browsing log of a web page browsed by each user. For example, as shown in FIG. 17, when the user G often browses a web page related to baseball, the user G can be predicted to be detailed about baseball. In this case, the user G is predicted to have a high preference for baseball.

In addition, for example, the difficulty level is assigned to each web page, and the learning unit 61 or the learning unit 81 learns the details of each item of each user based on the difficulty level of the web page viewed by each user. It may be. For example, in the case of the example of FIG. 17, when the difficulty level of the web page browsed by the user G is low, the user G can be predicted to be interested in baseball but not so detailed. Conversely, if the difficulty level of the web page viewed by the user G is high, the user G can be predicted to be very detailed about baseball.

The difficulty level of each web page may be given by the creator of the web page or may be set automatically by machine learning or the like. In the latter case, for example, the difficulty level of each web page can be set based on the length of the text in the web page, the number of appearances of technical terms, the number of browsing web pages, and the like. Here, for example, a web page with a long sentence or a large number of appearances of technical terms is predicted to have a high degree of difficulty. Further, for example, a web page with a small number of browsing is predicted to have a high degree of difficulty.

In addition, for example, the learning unit 61 or the learning unit 81 learns details about each item of each user based on the content posted to each user's social media (for example, social network service, blog, etc.). Also good. For example, the learning unit 61 or the learning unit 81 may extract a main topic from each user's posts and learn details about each item of each user based on the number of posts for each topic. For example, an item corresponding to a topic corresponding to a topic having a large number of posts by the user may be predicted to be detailed, and an item corresponding to a topic corresponding to a topic having a small number of posts by the user may be predicted not to be detailed. it can. Moreover, the learning part 61 or the learning part 81 calculates | requires the difficulty of a user's contribution content by the method similar to the web page mentioned above, and learns the detail with respect to each item of each user based on the calculated | required difficulty. It is also possible.

Further, for example, the learning unit 61 or the learning unit 81 may learn details about each item of each user on the basis of the friendship on each user's social media. For example, as shown in FIG. 18, when user H has many friends of math specialists on social media, user H can also be predicted to be familiar with mathematics.

The knowledge / preference information can be in any form as long as it can define the detail and preference of each user for each item and can define the difference in detail between users. is there. Further, the generation method of knowledge / preference information is not particularly limited, and any method can be adopted. For example, any learning model and learning method can be adopted.

In addition, for example, the server 11 or the client 12 constructs a learning model that predicts the detail and preference for each item of each user, and using the constructed learning model, the detail and preference of each user for each item May be obtained for each process.

In the above explanation, the degree of knowledge of the user for each item is defined by a scale of “detail”, but it can be defined by other scales. For example, it is possible to define the degree of knowledge of the user on two scales of knowledge “depth” and “broadness” or one of them.

{Function sharing between server 11 and client 12}
The above-described function sharing between the server 11 and the client 12 is an example, and can be arbitrarily changed. For example, some or all of the functions of the server 11 described above can be provided in the client 12. When all the functions of the server 11 are provided in the client 12, for example, the above-described user recommendation process in FIG. 12 and the information presentation process in FIG. 14 can be executed by the client 12 alone.

{Example of computer configuration}
The series of processes described above can be executed by hardware or can be executed by software. When a series of processing is executed by software, a program constituting the software is installed in the computer. Here, the computer includes, for example, a general-purpose personal computer capable of executing various functions by installing various programs by installing a computer incorporated in dedicated hardware.

FIG. 19 is a block diagram showing an example of the hardware configuration of a computer that executes the above-described series of processing by a program.

In the computer, a CPU (Central Processing Unit) 301, a ROM (Read Only Memory) 302, and a RAM (Random Access Memory) 303 are connected to each other by a bus 304.

An input / output interface 305 is further connected to the bus 304. An input unit 306, an output unit 307, a storage unit 308, a communication unit 309, and a drive 310 are connected to the input / output interface 305.

The input unit 306 includes a keyboard, a mouse, a microphone, and the like. The output unit 307 includes a display, a speaker, and the like. The storage unit 308 includes a hard disk, a nonvolatile memory, and the like. The communication unit 309 includes a network interface and the like. The drive 310 drives a removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory.

In the computer configured as described above, the CPU 301 loads the program stored in the storage unit 308 to the RAM 303 via the input / output interface 305 and the bus 304 and executes the program, for example. Is performed.

The program executed by the computer (CPU 301) can be provided by being recorded on the removable medium 311 as a package medium or the like, for example. The program can be provided via a wired or wireless transmission medium such as a local area network, the Internet, or digital satellite broadcasting.

In the computer, the program can be installed in the storage unit 308 via the input / output interface 305 by attaching the removable medium 311 to the drive 310. Further, the program can be received by the communication unit 309 via a wired or wireless transmission medium and installed in the storage unit 308. In addition, the program can be installed in advance in the ROM 302 or the storage unit 308.

The program executed by the computer may be a program that is processed in time series in the order described in this specification, or in parallel or at a necessary timing such as when a call is made. It may be a program for processing.

In this specification, the system means a set of a plurality of components (devices, modules (parts), etc.), and it does not matter whether all the components are in the same housing. Accordingly, a plurality of devices housed in separate housings and connected via a network and a single device housing a plurality of modules in one housing are all systems. .

Furthermore, embodiments of the present technology are not limited to the above-described embodiments, and various modifications can be made without departing from the gist of the present technology.

For example, the present technology can take a cloud computing configuration in which one function is shared by a plurality of devices via a network and is jointly processed.

Further, each step described in the above flowchart can be executed by one device or can be shared by a plurality of devices.

Further, when a plurality of processes are included in one step, the plurality of processes included in the one step can be executed by being shared by a plurality of apparatuses in addition to being executed by one apparatus.

Further, the effects described in the present specification are merely examples and are not limited, and other effects may be obtained.

Furthermore, for example, the present technology can take the following configurations.

(1)
A presentation information generation unit that generates presentation information that is information to be presented to the user based on the degree of knowledge of the user with respect to one or more items;
An information processing apparatus comprising: a presentation control unit that controls presentation of the presentation information.
(2)
The information processing apparatus according to (1), wherein the presentation information generation unit generates the presentation information to the user based on a difference in the degree of knowledge of the item between the user and the other user.
(3)
The information processing apparatus according to (2), wherein the presentation information generation unit further generates the presentation information to the user based on a preference degree of the user and the other user with respect to the item.
(4)
The presentation information generation unit, based on the difference in the degree of knowledge of the user and the other user with respect to the item, the preference level of the user and the other user from the items of a predetermined level or more, The information processing apparatus according to (3), wherein a topic recommended for the user is selected with another user, and the presentation information including the recommended topic is generated.
(5)
The presentation information generation unit selects a user to be recommended to the user from the other users based on a difference in the degree of knowledge about the item having a preference level of the user and the other user equal to or higher than a predetermined level. The information processing apparatus according to (3) or (4), wherein the presentation information including the recommended user is generated.
(6)
The presentation information generation unit selects, from the items, a topic recommended to the user between the other user based on a difference in the degree of knowledge of the item between the user and the other user. The information processing apparatus according to (2), wherein the presentation information including the recommended topic is generated.
(7)
The information processing apparatus according to (4) or (6), wherein the presentation information generation unit further selects the recommended topic based on a relationship between the user and the other user.
(8)
The information processing apparatus according to (4), (6), or (7), wherein the presentation information generation unit further selects the recommended topic based on a situation of the user and the other user.
(9)
The information according to any one of (4) and (6) to (8), wherein the presentation information generation unit generates the presentation information including information indicating a degree of knowledge of the other user with respect to the recommended topic. Processing equipment.
(10)
The presentation information generation unit selects a user to be recommended to the user from the other users based on a difference in knowledge level of the item between the user and the other user, and includes the user to be recommended The information processing apparatus according to any one of (2) to (4) and (6) to (9), which generates the presentation information.
(11)
The information processing apparatus according to (5) or (10), wherein the presentation information generation unit selects the recommended user from among other users who have knowledge from the user with respect to the designated item.
(12)
Any of (2) to (11), further comprising a communication unit that communicates with another information processing device and acquires information indicating the degree of knowledge of the item of the other user from the other information processing device. The information processing apparatus described in 1.
(13)
The presentation information generation unit further generates the presentation information to the user based on the user's preference for the item. Information processing according to any one of (1) and (6) to (12) apparatus.
(14)
The presentation information generation unit selects an item to be presented to the user from the items based on a degree of knowledge and a preference degree of the user for the item, and generates the presentation information including information on the selected item. The information processing apparatus according to (13).
(15)
The information processing apparatus according to any one of (1) to (14), further including a learning unit that learns the degree of knowledge of the user by the item.
(16)
The information processing apparatus according to any one of (1) to (15), wherein the presentation control unit controls presentation of the presentation information in another information processing apparatus.
(17)
A presentation unit for presenting the presentation information;
The information processing apparatus according to any one of (1) to (15), wherein the presentation control unit controls presentation of the presentation information in the presentation unit.
(18)
A presentation information generation step for generating presentation information that is information to be presented to the user based on the degree of knowledge of the user with respect to one or more items;
A presentation control step for controlling presentation of the presentation information.
(19)
A presentation information generation step for generating presentation information that is information to be presented to the user based on the degree of knowledge of the user with respect to one or more items;
A program for causing a computer to execute processing including a presentation control step for controlling presentation of the presentation information.

1 information processing system, 11 server, 12-1, 12-2 client, 51 communication unit, 52 calculation unit, 53 storage unit, 61 learning unit, 62 presentation information generation unit, 63 presentation control unit, 71 communication unit, 72 calculation Part, 73 input part, 74 presentation part, 75 storage part, 81 learning part, 82 presentation information generation part, 83 presentation control part, 84 transmission control part, 101 agent

Claims (19)

1. A presentation information generation unit that generates presentation information that is information to be presented to the user based on the degree of knowledge of the user with respect to one or more items;
   An information processing apparatus comprising: a presentation control unit that controls presentation of the presentation information.
2. The information processing apparatus according to claim 1, wherein the presentation information generation unit generates the presentation information to the user based on a difference in the degree of knowledge of the item between the user and the other user.
3. The information processing apparatus according to claim 2, wherein the presentation information generation unit further generates the presentation information to the user based on a preference degree of the user and the other user with respect to the item.
4. The presentation information generation unit, based on the difference in the degree of knowledge of the user and the other user with respect to the item, the preference level of the user and the other user from the items of a predetermined level or more, The information processing apparatus according to claim 3, wherein a topic recommended for the user is selected with another user, and the presentation information including the recommended topic is generated.
5. The presentation information generation unit selects a user to be recommended to the user from the other users based on a difference in the degree of knowledge about the item having a preference level of the user and the other user equal to or higher than a predetermined level. The information processing apparatus according to claim 3, wherein the presentation information including the recommended user is generated.
6. The presentation information generation unit selects, from the items, a topic recommended to the user between the other user based on a difference in the degree of knowledge of the item between the user and the other user. The information processing apparatus according to claim 2, wherein the presentation information including the recommended topic is generated.
7. The information processing apparatus according to claim 6, wherein the presentation information generation unit further selects the recommended topic based on a relationship between the user and the other user.
8. The information processing apparatus according to claim 6, wherein the presentation information generation unit further selects the recommended topic based on a situation of the user and the other user.
9. The information processing apparatus according to claim 6, wherein the presentation information generation unit generates the presentation information including information indicating a degree of knowledge of the other user with respect to the recommended topic.
10. The presentation information generation unit selects a user to be recommended to the user from the other users based on a difference in knowledge level of the item between the user and the other user, and includes the user to be recommended The information processing apparatus according to claim 2, wherein the presentation information is generated.
11. The information processing apparatus according to claim 10, wherein the presentation information generation unit selects the recommended user from among other users who have knowledge from the user with respect to the designated item.
12. The information processing apparatus according to claim 2, further comprising a communication unit that communicates with another information processing apparatus and acquires information indicating a degree of knowledge of the item of the other user from the other information processing apparatus.
13. The information processing apparatus according to claim 1, wherein the presentation information generation unit further generates the presentation information to the user based on a degree of preference of the user for the item.
14. The presentation information generation unit selects an item to be presented to the user from the items based on a degree of knowledge and a preference degree of the user for the item, and generates the presentation information including information on the selected item. The information processing apparatus according to claim 13.
15. The information processing apparatus according to claim 1, further comprising a learning unit that learns a degree of knowledge of the item for the user.
16. The information processing apparatus according to claim 1, wherein the presentation control unit controls presentation of the presentation information in another information processing apparatus.
17. A presentation unit for presenting the presentation information;
    The information processing apparatus according to claim 1, wherein the presentation control unit controls presentation of the presentation information in the presentation unit.
18. A presentation information generation step for generating presentation information that is information to be presented to the user based on the degree of knowledge of the user with respect to one or more items;
    A presentation control step for controlling presentation of the presentation information.
19. A presentation information generation step for generating presentation information that is information to be presented to the user based on the degree of knowledge of the user with respect to one or more items;
    A program for causing a computer to execute processing including a presentation control step for controlling presentation of the presentation information.

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