JP7212599B2 - Information provision system - Google Patents

Description

One aspect of the present disclosure relates to an information providing system.

Techniques for proposing keywords for use in computer processing to users are known. For example, Patent Literature 1 describes a keyword providing system that automatically provides users with keywords related to broadcast content. This system extracts keywords that match keywords corresponding to broadcast content from a predetermined keyword group, and provides the extracted keywords to user terminal devices as keywords related to broadcast information.

JP 2006-319456 A

It would be more convenient if keywords that are likely to be used by the user could be presented to the user with higher accuracy. Therefore, a mechanism for presenting such keywords with higher accuracy is desired.

An information providing system according to one aspect of the present disclosure includes at least one processor. At least one processor refers to a first database that stores browsing histories indicating that a plurality of viewers, including the target user, have accessed first content provided from a first information source, and based on the browsing histories, selecting at least one first keyword, referring to a second database storing meta information indicating frequency of occurrence of the keyword in second content provided from a second information source, and based on the meta information, at least one selecting a second keyword, generating a keyword list including at least one of the at least one first keyword and at least one of the at least one second keyword, and displaying the keyword list on the terminal of the target user; Let

In such an aspect, a keyword list including both a first keyword selected based on the browsing history regarding the first information source and a second keyword selected based on the appearance frequency in the second information source is provided. Displayed on the terminal of the target user. It can be said that the first keyword is a keyword that is presumed to be of high interest to the target user, and that the second keyword is a keyword that is presumed to be of high interest to people. Therefore, by displaying a mixture of these two types of keywords on the terminal, it is possible to accurately provide keywords that are likely to be used by the target user.

According to one aspect of the present disclosure, it is possible to accurately provide keywords that are highly likely to be used by users.

It is a figure which shows an example of utilization of the information provision system which concerns on embodiment. It is a figure showing an example of composition of an information service system concerning an embodiment. It is a flow chart which shows an example of operation of an information service system concerning an embodiment. 9 is a flow chart showing an example of processing for extracting a first candidate keyword; It is a figure which shows an example of a keyword dictionary. It is a figure which shows an example of the intermediate record for extracting a 1st candidate keyword. FIG. 5 is a diagram showing an example of clustering of viewers; It is a figure which shows an example of the intermediate record for extracting a 1st candidate keyword. 10 is a flowchart showing an example of processing for selecting a second keyword; It is a figure which shows an example of the hardware constitutions of the computer used with the information provision system which concerns on embodiment.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same or equivalent elements are denoted by the same reference numerals, and overlapping descriptions are omitted.

The information providing system 1 according to the embodiment is a computer system that proposes a keyword to be used for processing on a computer to a target user. By transmitting one or more keywords to the user terminal of the target user, the information providing system 1 displays the keywords on the user terminal, so that the target user can use the suggested keywords. A target user is a user to whom a keyword is provided.

The purpose and usage of keywords are not limited. In one example, the information providing system 1 may suggest keywords that are used to search for information. FIG. 1 is a diagram showing an example of use of the information providing system 1. As shown in FIG. In this example, the user terminal 20 is running a news application program that displays various information such as news, and displays a plurality of articles 201 and a keyword list 202 consisting of a plurality of keywords. By selecting and registering a favorite keyword from the keyword list, the target user can retrieve an article corresponding to the keyword and display the article on the user terminal 20 .

The information providing system 1 selects keywords using two types of techniques, and provides the user terminal 20 with a mixture of keywords obtained by the respective techniques as a keyword list. A first method is to select at least one first keyword based on viewing histories indicating that a plurality of viewers, including the target user, have accessed first content provided from a first information source. A second method is to select at least one second keyword based on the appearance frequency of the keyword in the second content provided from a second information source different from the first information source. The keyword list 202 shown in FIG. 1 consists of at least one first keyword and at least one second keyword.

The first keyword is a keyword presented based on the tendency of the target user to browse the first content, and therefore can be said to be a keyword that is presumed to be of high interest to the target user. On the other hand, the second keyword is a keyword that is estimated based on public topicality, and therefore can be said to be a keyword that is highly likely to be of interest to the target user as well as other people. By including these two types of keywords in the keyword list, it is possible to effectively expand the range of keyword selection. As a result, it is possible to accurately provide keywords that are highly likely to be used by the target user.

FIG. 2 is a diagram showing an example of the configuration of the information providing system 1. As shown in FIG. The information providing system 1 includes a server 10 which is a computer that provides keywords to target users. The server 10 can perform data communication with the user terminal 20 via the communication network. Although only one user terminal 20 is shown in FIG. 2, the number of user terminals 20 that communicate with the server 10 is not limited, and the server 10 may be connected to a plurality of user terminals 20 for communication. Furthermore, the server 10 can access the database group 30 via a communication network. The configuration of the communication network is not limited and may be designed according to any policy. For example, each communication network may include at least one of a mobile communication network, the Internet, an intranet, and a WAN (Wide Area Network).

The server 10 includes a viewing history analysis unit 11, a reception unit 12, a first selection unit 13, a second selection unit 14, a list generation unit 15, and a transmission unit 16 as functional elements. The viewing history analysis unit 11 is a functional element that analyzes viewing histories indicating that a plurality of viewers, including the target user, have accessed first content provided from a first information source, and extracts first candidate keywords. . A first candidate keyword is a phrase that is a candidate for the first keyword. The receiving unit 12 is a functional element that receives an instruction to provide a keyword. The first selection unit 13 is a functional element that selects at least one first keyword. The second selection unit 14 is a functional element that selects at least one second keyword based on the appearance frequency of keywords in the second content provided from the second information source. The list generator 15 is a functional element that generates a keyword list including at least one first keyword and at least one second keyword. The transmission unit 16 is a functional element that transmits the keyword list to the user terminal 20 , whereby the keywords are displayed on the user terminal 20 .

The server 10 is configured using at least one computer. When a plurality of computers are used, one server 10 is logically constructed by connecting these computers to each other via a communication network.

The user terminal 20 is a computer operated by the target user. The type of user terminal 20 is not limited. For example, the user terminal 20 may be a portable terminal such as a mobile phone, a high-performance mobile phone (smartphone), a tablet terminal, a wearable terminal (for example, a smart watch, a head-mounted display (HMD), etc.), or a laptop. Alternatively, the user terminal 20 may be a stationary personal computer.

The database group 30 is a set of databases that store necessary data in the information providing system 1 . In this embodiment, the database group 30 includes a browsing history database 31 , a first content database 32 , a first candidate keyword database 33 , a meta information database 34 and a user database 35 .

The viewing history database 31 is a non-temporary storage medium or storage device that stores viewing histories indicating that a plurality of viewers including the target user have accessed the first content provided from the first information source. In one example, each record of viewing history includes a user ID, a content ID, a content date and time, and an operation type. A user ID is an identifier that uniquely identifies a user (that is, a viewer) who has accessed the first content. A content ID is an identifier that uniquely identifies each first content. The content date and time is the date and time when the first content was generated or published. The operation type indicates the type of user's (viewer's) operation on the first content. For example, the operation type may be "browse" indicating that the user has viewed a specific first content on the user terminal 20, or "click" indicating that the user has clicked on a link in a specific first content. can represent various manipulations of

The type of the first information source is not limited, and correspondingly, the type of the first content is also not limited. For example, the first information source may be an information service or information originator that provides information to any terminal or device over a communication network. In one example, the first information source may be an information service or information originator that provides first content for an application program capable of displaying a keyword list. In the example of FIG. 1, the primary information source may be an information publisher or information service that provides primary content for a news application program. Alternatively, the first information source may be an information originator or information service that provides the first content for another application program independent of the application program having the function of displaying the keyword list. The first content includes visible elements, such as text, images (still or moving images), or a combination thereof. The first content may be an article created by an individual or a corporation, such as an article provided by newspapers, magazines, online news, blogs, social networking services (SNS), and the like. An article is a piece of writing that tells a story. An article includes at least a character string and may further include an image (still image or moving image).

The browsing history is generated by the access management system and stored in the browsing history database 31 . The configuration of the access management system is not limited. For example, the information providing system 1 may have a function as an access management system. Alternatively, a computer system different from the information providing system 1 may function as the access management system. The access management system monitors access to the first content from one or more user terminals 20 , generates a browsing history record based on the monitoring results, and stores the record in the browsing history database 31 . A browsing history is accumulated in the browsing history database 31 by monitoring individual accesses to individual first contents.

The first content database 32 is a non-temporary storage medium or storage device that stores first content. Each first content is associated with a content ID.

The first candidate keyword database 33 is a non-temporary storage medium or storage device that stores first candidate keyword information related to first candidate keywords extracted based on browsing history. In one example, each record of first candidate keyword information includes a genre ID, a cluster ID, and a feature vector for one or more first candidate keywords. A genre ID is an identifier for uniquely identifying a genre, which is a classification or type of content. A cluster ID is an identifier for uniquely identifying a cluster to which a user belongs. Clusters of individual users are determined by clustering, which is the process of classifying a set of data into multiple clusters (subsets). The details of clustering will be described later. A feature vector includes one or more components expressed by a combination of a first candidate keyword and a score. Details of the feature vector will also be described later.

The meta-information database 34 is a non-temporary storage medium or storage device that permanently stores meta-information indicating the appearance frequency of keywords in the second content provided from the second information source. In one example, each record of meta information includes keywords and frequency of occurrence. A keyword is a phrase that appears on the second content. Appearance frequency is an index that indicates the extent to which the keyword appears in one or more second contents during a predetermined period.

The type of the second information source is not limited, and correspondingly, the type of the second content is also not limited. However, the second information source is different from the first information source. For example, the second information source may be an information service or information originator capable of providing information to any terminal or device via a communication network or broadcast network. In one example, the second source may be a broadcast station that broadcasts television or radio programs over a broadcast or communications network, or a publisher that provides articles over the Internet. The second content includes visible elements, such as text, images (still or moving images), or a combination thereof. The secondary content may be television programs, radio programs, or articles produced by individuals or corporations.

Meta information is generated by the meta information management system and stored in the meta information database 34 . The configuration of the meta information management system is not limited. For example, the information providing system 1 may have a function as a meta information management system. Alternatively, a computer system different from the information providing system 1 may function as the meta information management system. The meta-information management system analyzes each of the secondary contents broadcasted or distributed within a predetermined period of time to extract predetermined keywords represented by text, images, or sounds in each of the secondary contents. . Then, the meta-information management system counts the number of appearances of each keyword, generates a meta-information record based on the result of counting, and stores the record in the meta-information database 34 . Meta information is accumulated in the meta information database 34 by analyzing each second content. The setting method of appearance frequency is not limited. For example, when a certain keyword appears one or more times in one or more second contents, the meta information management system may set the number of times of appearance as the frequency of appearance, or the second contents in which the keyword appears. may be set as the appearance frequency.

The user database 35 is a non-temporary storage medium or storage device that permanently stores keyword information indicating preferred keywords selected and registered by the target user. In one example, each record of keyword information includes a user ID, a keyword, and a keyword type. A user ID is an identifier that uniquely identifies a target user who has selected and registered a keyword. A keyword refers to a keyword selected and registered by a target user, and can be, for example, a keyword selected from the keyword list 202 shown in FIG. The keyword type is a data item indicating the origin of the keyword, and indicates, for example, whether the keyword was the first keyword or the second keyword. Keyword information is generated by the keyword management system and stored in the user database 35 . The configuration of the keyword management system is not limited. For example, the information providing system 1 may have a function as a keyword management system. Alternatively, a computer system different from the information providing system 1 may function as the keyword management system. The keyword management system receives from the user terminal 20 the keyword selected by the user terminal 20, the keyword type associated with the keyword, and the user ID. Then, the keyword management system generates a keyword information record based on these data items and stores the record in the user database 35 .

The data structure of each piece of information stored in each database is not limited, and may be designed according to any policy. For example, at least one of browsing history, first candidate keyword information, meta information, and keyword information may be normalized or non-normalized according to an arbitrary policy and stored on one or more data tables.

FIG. 3 is a flow chart showing an example of the operation of the information providing system 1 as a processing flow S1. In step S11, the receiving unit 12 receives a request for a keyword list. This request is a data signal for instructing provision of the keyword list. The request includes the user ID of the target user corresponding to the user terminal 20 to which the keyword list is sent. The request acceptance method is not limited. For example, the reception unit 12 may receive a request transmitted from the user terminal 20 based on a predetermined operation on the user terminal 20 . Alternatively, the reception unit 12 may acquire requests input from other functional elements within the information providing system 1 . The request may include at least one genre ID, in which case a keyword list consisting of keywords corresponding to each genre ID is sent to the user terminal 20 .

At step S12, the first selection unit 13 selects at least one first keyword in response to the request. For this selection, the browsing history analysis unit 11 extracts first candidate keywords in advance and stores first candidate keyword information in the first candidate keyword database 33 . FIG. 4 is a flow chart showing an example of processing for extracting the first candidate keyword as a processing flow S2. In one example, the browsing history analysis unit 11 executes the process flow S2 by periodic (for example, hourly) batch processing, thereby updating the first candidate keyword information to the latest state.

In step S21, the browsing history analysis unit 11 calculates the feature vector of the first candidate keyword for each record of the browsing history. The browsing history analysis unit 11 identifies one or more first candidate keywords from the first content for each record of the browsing history, that is, for each access indicated by the browsing history. The viewing history analysis unit 11 reads one record from the viewing history database 31 and reads the first content corresponding to the content ID from the first content database 32 . The browsing history analysis unit 11 identifies one or more first candidate keywords from the first content by analyzing at least one of the title and text of the first content. The viewing history analysis unit 11 executes the processing for each record of the viewing history.

Subsequently, the browsing history analysis unit 11 calculates the feature amount of each of the one or more first candidate keywords for each record of the browsing history (each access indicated in the browsing history), and calculates the first candidate keyword and the feature amount. generate a feature vector containing one or more combinations of

For this process, the browsing history analysis unit 11 refers to a keyword dictionary that indicates the association between the first candidate keyword, the reference feature amount, and the genre ID. This keyword dictionary is prepared in advance and stored in an arbitrary storage device within the information providing system 1 . The keyword dictionary may further indicate alternatives, synonyms, or synonyms for at least some of the first candidate keywords. FIG. 5 shows an example of a keyword dictionary for the first candidate keyword. In this example, each record in the keyword dictionary contains the subject phrase that is the first candidate keyword, the sub-phrase corresponding to the subject phrase, and the reference feature amount of each sub-phrase (numerical values shown in parentheses in FIG. 5). and a genre ID. One first candidate keyword may be associated with multiple genres.

The browsing history analysis unit 11 refers to the keyword dictionary to specify the first candidate keyword and the reference feature amount corresponding to the genre ID of the first content. Regarding the example of FIG. 5, when the first candidate keyword "Japanese representative" is obtained from the subphrase "National Team", the browsing history analysis unit 11 sets the reference feature amount of the first candidate keyword to 0.5. do. The browsing history analysis unit 11 applies a weight based on at least one of the elapsed time after the generation of the first content and the type of operation on the first content to the specified reference feature value to determine the feature value. can be calculated. For example, the browsing history analysis unit 11 may obtain a feature amount by multiplying the reference feature amount by a weight. The elapsed time since the first content was generated can be obtained based on the date and time of the content. For example, the weight may be set such that the shorter the elapsed time (that is, the newer the date and time of the content), the higher the feature amount. Alternatively, the weight may be set so that the feature amount of "click" is higher than that of "view".

The browsing history analysis unit 11 calculates the feature vector of the first candidate keyword for each record of the browsing history, and generates a first intermediate record indicating the feature vector. Each first intermediate record contains a user ID, a content ID, and a feature vector. FIG. 6 shows an example of the first intermediate record. In this example, for convenience of explanation, only five first intermediate records 301 related to user A, who is a specific viewer, are shown. is calculated to generate a first intermediate record. In the example of FIG. 6, there are two records with the content ID "C4042", which means that the user A has accessed the first content identified by the content ID twice.

In step S22, the viewing history analysis unit 11 sums the feature vectors for each combination of the viewer and the genre of the first content. The browsing history analysis unit 11 processes a certain browsing person as follows. That is, the viewing history analysis unit 11 identifies the genre ID of the first content for each of the one or more first intermediate records of the viewer, thereby identifying one or more genre IDs corresponding to the viewer. Then, the browsing history analysis unit 11 sums up the feature vectors of the genre IDs for each of the specified one or more genre IDs, and generates a second intermediate record indicating the calculation result. Summation of feature vectors specifically refers to a process of obtaining the sum of feature amounts for each of the one or more first candidate keywords. The viewing history analysis unit 11 executes such a series of processes for each of a plurality of viewers.

FIG. 6 also shows an example of the second intermediate record obtained by summing the feature vectors. In this example, three records with content IDs "C4042", "C4042", and "C4053" correspond to genre ID "3", and two records with content IDs "C4001", "C4101" correspond to genre ID "C4042", "C4042", and "C4053". 15". The browsing history analysis unit 11 generates two second intermediate records 302 by adding feature vectors for these first intermediate records 301 . For the second intermediate record 302 with the genre ID "3", the browsing history analysis unit 11 sums the feature amount of the first candidate keyword "soccer" as 1+1.5=2.5. Similarly, the feature amount of the first candidate keyword "Japan national team" is 1+1.5+0.7=3.2, and the feature amount of the first candidate keyword "team R" is 0.9+1.4=2.3. added up. Since the first candidate keyword "Soccer World Cup" appears in only one record, the total value of this first candidate keyword is 0.7.

In step S23, the viewing history analysis unit 11 performs clustering of viewers based on feature vectors for each genre. A plurality of viewers are classified into a plurality of clusters by clustering performed by the viewing history analysis unit 11, thereby generating a plurality of clusters each including one or more viewers having common features. The clustering method is not limited, and the viewing history analysis unit 11 may cluster viewers using one or more arbitrary methods. For example, the viewing history analysis unit 11 may cluster viewers using cosine similarity and Locality Sensitive Hashing (LSH). More specifically, the browsing history analysis unit 11 may perform first clustering using cosine similarity, and may readjust clusters by performing second clustering using LSH.

FIG. 7 is a diagram showing an example of viewer clustering in a certain genre. In this example, users A and B are classified into cluster 401 , user C is classified into cluster 402 , and users D and E are classified into cluster 403 . The point drawn at the center of each cluster indicates the centroid of the cluster. Although FIG. 7 shows the space in which individual clusters exist in three-dimensional coordinates for the sake of convenience, the number of dimensions considered in clustering is not limited and may be set arbitrarily.

In each genre, the viewing history analysis unit 11 identifies the cluster to which each viewer belongs, and adds a cluster ID to each second intermediate record. FIG. 8 is a diagram showing an example of a second intermediate record to which a cluster ID is added. This example shows the second intermediate record 303 of five users A, B, C, D, and E for genre ID "3". Users A and B are classified into cluster "1", user C is classified into cluster "2", and users D and E are classified into cluster "3".

In step S24, the viewing history analysis unit 11 generates first candidate keyword information by summing the feature vectors for each combination of genre and cluster. For each combination of genre and cluster, browsing history analysis unit 11 sums the feature vectors of one or more second intermediate records corresponding to the combination, and generates a third intermediate record indicating this calculation result. This addition is also a process of obtaining the sum of feature amounts for each of the one or more first candidate keywords. The third intermediate record corresponds to the record of the first candidate keyword information. FIG. 8 further illustrates the process of summing the feature vectors of the second intermediate record 303 to generate the third intermediate record 304 . Regarding the combination of the genre ID “3” and the cluster ID “1”, the browsing history analysis unit 11 sums the feature amount of the first candidate keyword “soccer” as 2.5+1.0=3.5, and obtains the first candidate The feature amount of the keyword “soccer world cup” is summed up as 0.7+1.0=1.7. Since the first candidate keywords "Japan national team", "Team R", and "England national team" appear only in one record each, the feature values of these three words are incorporated into the third intermediate record 304 as they are. The browsing history analysis unit 11 similarly generates the third intermediate records 304 for each of the cluster IDs "2" and "3".

In step S25, the browsing history analysis unit 11 registers the generated one or more third intermediate records in the first candidate keyword database 33 as records of first candidate keyword information. If the first candidate keyword database 33 already stores a record corresponding to the combination of genre and cluster, the browsing history analysis unit 11 overwrites the record with the third intermediate record. Update the first candidate keyword information.

Returning to FIG. 3, in step S12, the first selection unit 13 selects at least one first keyword based on the first candidate keyword information prepared in advance by the process flow S2. The first selection unit 13 selects at least one of the one or more first candidate keywords corresponding to the combination of the genre corresponding to the request and the cluster to which the target user belongs, as the first keyword. The first selection unit 13 refers to the first candidate keyword database 33, reads a record corresponding to the combination, and selects a first candidate keyword having a relatively high feature amount as the first keyword. For example, the first selection unit 13 may arrange the first candidate keywords in descending order of feature amount, and then select one or more first candidate keywords from the top as the first keyword. Thus, the first selection unit 13 selects at least one first keyword from a plurality of first candidate keywords based on one or more feature vectors corresponding to the cluster to which the target user belongs. Specifically, the first selection unit 13 selects one or more first keywords based on one or more feature vectors corresponding to a combination of genres and clusters to which the target user belongs. Typically, the first selection unit 13 selects one or more first keywords based on one or more feature vectors corresponding to the genre corresponding to the request and the cluster to which the target user belongs.

In step S13, the second selection unit 14 selects at least one second keyword in response to the request. Details of step S13 are shown in FIG. FIG. 9 is a flowchart showing an example of processing for selecting a second keyword.

In step S131, the second selection unit 14 refers to the meta information database and acquires keywords. For example, the second selection unit 14 acquires keywords whose frequency of appearance is higher than a predetermined standard. Specifically, the second selection unit 14 may acquire a predetermined number of keywords in descending order of appearance frequency, or may acquire keywords whose appearance frequency is equal to or higher than a predetermined threshold. If one or more genres are specified by the request, the second selection unit 14 acquires keywords belonging to the specified genres.

In step S132, the second selection unit 14 identifies the second candidate keyword by absorbing spelling variations. The second selection unit 14 refers to the keyword dictionary, specifies the subject phrase for each of the keywords acquired in step S131, and specifies the subject phrase as the second candidate keyword. If the keyword is a subject phrase, the second selection unit 14 identifies the keyword as it is as the second candidate keyword, and if the keyword is a subphrase, identifies the subject phrase corresponding to the keyword as the second candidate keyword. As a result of this processing, when a plurality of keywords correspond to one subject phrase, the second selection unit 14 adds up the frequency of appearance of the plurality of keywords to obtain the frequency of appearance of the second candidate keyword. Through this process, the second selection unit 14 obtains an intermediate list indicating the appearance frequency of each second candidate keyword.

In step S133, the second selection unit 14 excludes specific second candidate keywords. Conditions for exclusion are not limited and may be set by any policy. For example, the second selection unit 14 may prevent a second candidate keyword having a long number of characters from being selected as the second keyword by excluding second candidate keywords having a number of characters equal to or greater than a predetermined threshold. Alternatively, the second selection unit 14 may exclude second candidate keywords that are inappropriate from the viewpoint of public order and morals, based on predetermined rules. Alternatively, the second selection unit 14 searches for the first content corresponding to the second candidate keyword, acquires the number of the first content extracted by the search as the number of hits, and if the number of hits is less than a predetermined threshold, Certain second candidate keywords may be excluded. This processing can prevent a second candidate keyword with few corresponding first contents from being selected as a second keyword. In other words, the second selection unit 14 leaves the second candidate keywords whose number of hits is equal to or greater than the predetermined threshold. The second selection unit 14 may exclude the second candidate keyword using any two or more of these three types of conditions.

In step S134, the second selection unit 14 selects the remaining second candidate keywords as second keywords. Through the above processing, the second selection unit 14 selects one or more second keywords.

Returning to FIG. 3, in step S14, the list generator 15 generates a keyword list including at least one first keyword and at least one second keyword. In one example, the list generator 15 randomly selects some of the plurality of first keywords and randomly selects some of the plurality of second keywords.

In another example, the list generating unit 15 accesses the user database 35 and reads out keyword information corresponding to the target user, thereby determining the number of keywords presented by the target user as the second keywords and selected by the target user. identify. Then, the list generation unit 15 sets the ratio of the second keywords in the keyword list to Pa when the number is less than the predetermined threshold, and sets the ratio to Pb ( However, it is set to Pb<Pa). This is intended to present more keywords that other people are interested in to target users who tend to select more keywords that interest them. The ratios Pa and Pb may be set so that Pa+Pb=100(%).

Alternatively, the list generator 15 identifies the number of combinations of genre IDs and cluster IDs corresponding to user IDs. Then, the list generating unit 15 sets the ratio of the second keywords in the keyword list to Pc when the number is less than the predetermined threshold, and sets the ratio to Pd when the number is equal to or greater than the threshold. (However, Pd<Pc). This is intended to present more keywords in various fields to target users who tend to have narrower interests. The ratios Pc and Pd may be set so that Pc+Pd=100(%).

The list generator 15 may shuffle the first keyword and the second keyword within the keyword list. When the same word/phrase is selected from both the first keyword and the second keyword, the list generation unit 15 does not duplicate the word/phrase in the keyword list, but includes only one word/phrase in the keyword list. In one example, the list generator 15 associates each of the first keyword and the second keyword with the corresponding keyword type.

In step S<b>15 , the transmission unit 16 transmits the keyword list to the user terminal 20 . User terminal 20 receives and displays the keyword list. For example, the user terminal 20 displays the keyword list 202 shown in FIG. The transmitting unit 16 may cause the keyword list to be displayed on the user terminal 20 in order to provide the target user with keywords used for searching for the first content in the first information source.

The genre of content is not an essential component, and therefore the information providing system 1 may perform a series of processes for generating and transmitting keyword lists without considering genre.

The viewing history analysis unit 11 and the first candidate keyword database 33 are not essential components, and the first selection unit 13 may also play the role of the viewing history analysis unit 11 . In this case, the first selection unit 13 refers to the browsing history database 31 and the first content database 32 in response to the request, and selects at least one first keyword based on the browsing history. That is, a series of processes for selecting at least one first keyword based on browsing history may include periodic batch processing as in the above embodiment, or may be processed in real time.

The block diagrams used in the description of the above embodiments show blocks for each function. These functional blocks (components) are realized by any combination of at least one of hardware and software. Also, the method of implementing each functional block is not particularly limited. That is, each functional block may be implemented using one device that is physically or logically coupled, or directly or indirectly using two or more devices that are physically or logically separated (e.g. , wired, wireless, etc.) and may be implemented using these multiple devices. A functional block may be implemented by combining software in the one device or the plurality of devices.

Functions include judging, determining, determining, calculating, calculating, processing, deriving, investigating, searching, checking, receiving, transmitting, outputting, accessing, resolving, selecting, choosing, establishing, comparing, assuming, expecting, assuming, Broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, assigning, etc. can't For example, the functional block responsible for transmission is called a transmitting unit or transmitter. In either case, as described above, the implementation method is not particularly limited.

For example, the information providing system 1 or the server 10 in one embodiment of the present disclosure may function as a computer that performs the processing of the present disclosure. FIG. 10 is a diagram showing an example of a hardware configuration of a computer 100 functioning as the information providing system 1 or server 10. As shown in FIG. Computer 100 may physically include processor 1001, memory 1002, storage 1003, communication device 1004, input device 1005, output device 1006, bus 1007, and the like.

Note that in the following description, the term "apparatus" can be read as a circuit, device, unit, or the like. The hardware configuration of the server 10 may be configured to include one or more of each device shown in the figure, or may be configured without some of the devices.

Each function in the server 10 is performed by causing the processor 1001 to perform calculations, controlling communication by the communication device 1004, controlling communication by the communication device 1004, and controlling the communication by the memory 1002 and It is realized by controlling at least one of data reading and writing in the storage 1003 .

The processor 1001, for example, operates an operating system to control the entire computer. The processor 1001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic device, registers, and the like.

The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 to the memory 1002, and executes various processes according to these. As the program, a program that causes a computer to execute at least part of the operations described in the above embodiments is used. For example, each functional element of the server 10 may be stored in the memory 1002 and implemented by a control program running on the processor 1001 . Although it has been explained that the above-described various processes are executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. FIG. Processor 1001 may be implemented by one or more chips. Note that the program may be transmitted from a network via an electric communication line.

The memory 1002 is a computer-readable recording medium, and is composed of at least one of, for example, ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), and RAM (Random Access Memory). may be The memory 1002 may also be called a register, cache, main memory (main storage device), or the like. The memory 1002 can store executable programs (program code), software modules, etc. to perform a method according to an embodiment of the present disclosure.

The storage 1003 is a computer-readable recording medium, for example, an optical disc such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disc, a magneto-optical disc (for example, a compact disc, a digital versatile disc, a Blu-ray disk), smart card, flash memory (eg, card, stick, key drive), floppy disk, magnetic strip, and/or the like. Storage 1003 may also be called an auxiliary storage device. The storage medium described above may be, for example, a database, server, or other suitable medium including at least one of memory 1002 and storage 1003 .

The communication device 1004 is hardware (transmitting/receiving device) for communicating between computers via at least one of a wired network and a wireless network, and is also called a network device, a network controller, a network card, a communication module, or the like. The communication device 1004 includes a high-frequency switch, a duplexer, a filter, a frequency synthesizer, and the like, for example, in order to realize at least one of frequency division duplex (FDD) and time division duplex (TDD). may consist of

The input device 1005 is an input device (for example, keyboard, mouse, microphone, switch, button, sensor, etc.) that receives input from the outside. The output device 1006 is an output device (for example, display, speaker, LED lamp, etc.) that outputs to the outside. Note that the input device 1005 and the output device 1006 may be integrated (for example, a touch panel).

Devices such as the processor 1001 and the memory 1002 are connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between devices.

Further, the computer 100 includes hardware such as a microprocessor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), and an FPGA (Field Programmable Gate Array). A part or all of each functional block may be implemented by the hardware. For example, processor 1001 may be implemented using at least one of these pieces of hardware.

As described above, the information providing system according to one aspect of the present disclosure includes at least one processor. At least one processor refers to a first database that stores browsing histories indicating that a plurality of viewers, including the target user, have accessed first content provided from a first information source, and based on the browsing histories, selecting at least one first keyword, referring to a second database storing meta information indicating frequency of occurrence of the keyword in second content provided from a second information source, and based on the meta information, at least one selecting a second keyword, generating a keyword list including at least one of the at least one first keyword and at least one of the at least one second keyword, and displaying the keyword list on the terminal of the target user; Let

In such an aspect, a keyword list including both a first keyword selected based on the browsing history regarding the first information source and a second keyword selected based on the appearance frequency in the second information source is provided. Displayed on the terminal of the target user. It can be said that the first keyword is a keyword that is presumed to be of high interest to the target user, and that the second keyword is a keyword that is presumed to be of high interest to people. Therefore, by displaying a mixture of these two types of keywords on the terminal, it is possible to accurately provide keywords that are likely to be used by the target user.

In the information providing system according to another aspect, at least one processor identifies one or more first candidate keywords from the first content for each access indicated by the browsing history, and for each access indicated by the browsing history, A feature amount is calculated for each of the one or more first candidate keywords, a feature vector including one or more combinations of the first candidate keyword and the feature amount is generated, and a plurality of viewers are clustered based on each feature vector. By doing so, a plurality of clusters may be generated, and at least one first keyword may be selected from the plurality of first candidate keywords based on one or more feature vectors corresponding to the cluster to which the target user belongs. By clustering the viewers based on the feature vector indicating the feature amount of the first candidate keyword and selecting the first keyword based on the feature vector corresponding to the cluster to which the target user belongs, it is estimated that the target user is highly interested. It is possible to provide keywords with high accuracy.

In the information providing system according to another aspect, at least one processor sums the feature vectors for each combination of the viewer and the genre of the first content, and clusters the plurality of viewers for each genre. Clusters may be generated and at least one first keyword may be selected based on feature vectors corresponding to combinations of corresponding genres and clusters to which the target user belongs. By clustering viewers in consideration of the genre of the first content and selecting a feature vector, it is possible to provide keywords corresponding to the genre of which the target user is highly interested.

In the information providing system according to another aspect, at least one processor obtains a predetermined reference feature amount for each of the one or more first candidate keywords, and for each of the one or more first candidate keywords, obtains the first A weight is set based on at least one of the elapsed time since the first content corresponding to the candidate keyword was generated and the viewing operation for the first content, and for each of the one or more first candidate keywords , the feature amount may be calculated by applying a weight to the reference feature amount. Through this process, the feature quantity indicates the freshness of the first content and the degree of interest of the viewer in the first content. By selecting the first keyword based on such a feature amount, it is possible to provide a keyword that is estimated to be of high interest to the target user with high accuracy.

In the information providing system according to another aspect, at least one processor may select, as at least one second keyword, a keyword whose appearance frequency is higher than a predetermined standard. In this case, keywords that are presumed to be of particular interest to people can be provided.

In the information providing system according to another aspect, at least one processor acquires the number of hits of the first content corresponding to each of the one or more keywords indicated by the meta information, and the number of hits exceeds a predetermined threshold. If so, the keyword may be selected as at least one second keyword. Through this process, it is possible to provide keywords that are of high interest among people and that are estimated to contribute to searches for the first content.

In the information providing system according to another aspect, at least one processor causes a keyword list to be displayed on a terminal in order to provide a target user with keywords used for searching for first content in a first information source. may In this case, it is possible to accurately provide keywords that are highly likely to be used by the target user to search for the first content.

Although the present disclosure has been described in detail above, it should be apparent to those skilled in the art that the present disclosure is not limited to the embodiments described in this disclosure. The present disclosure can be practiced with modifications and variations without departing from the spirit and scope of the present disclosure as defined by the claims. Accordingly, the description of the present disclosure is for illustrative purposes and is not meant to be limiting in any way.

Notification of information is not limited to the aspects/embodiments described in this disclosure, and may be performed using other methods. For example, notification of information includes physical layer signaling (e.g., DCI (Downlink Control Information), UCI (Uplink Control Information)), higher layer signaling (e.g., RRC (Radio Resource Control) signaling, MAC (Medium Access Control) signaling, It may be implemented by broadcast information (MIB (Master Information Block), SIB (System Information Block)), other signals, or a combination thereof. RRC signaling may also be called an RRC message, and may be, for example, an RRC connection setup message, an RRC connection reconfiguration message, or the like.

Each aspect/embodiment described in the present disclosure includes LTE (Long Term Evolution), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), FRA (Future Radio Access), NR (new Radio), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark) )), IEEE 802.16 (WiMAX®), IEEE 802.20, UWB (Ultra-WideBand), Bluetooth®, and other suitable systems and extended It may be applied to at least one of the next generation systems. Also, a plurality of systems may be applied in combination (for example, a combination of at least one of LTE and LTE-A and 5G, etc.).

The processing procedures, sequences, flowcharts, etc. of each aspect/embodiment described in this disclosure may be rearranged as long as there is no contradiction. For example, the methods described in this disclosure present elements of the various steps using a sample order, and are not limited to the specific order presented.

Certain operations that are described in this disclosure as being performed by a base station may also be performed by its upper node in some cases. In a network consisting of one or more network nodes with a base station, various operations performed for communication with a terminal may be performed by the base station and other network nodes other than the base station (e.g. MME or S-GW, etc. (including but not limited to). Although the case where there is one network node other than the base station is exemplified above, it may be a combination of a plurality of other network nodes (for example, MME and S-GW).

Information, etc., may be output from a higher layer (or lower layer) to a lower layer (or higher layer). It may be input and output via multiple network nodes.

Input/output information and the like may be stored in a specific location (for example, memory), or may be managed using a management table. Input/output information and the like can be overwritten, updated, or appended. The output information and the like may be deleted. The entered information and the like may be transmitted to another device.

The determination may be made by a value represented by one bit (0 or 1), by a true/false value (Boolean: true or false), or by numerical comparison (for example, a predetermined value).

Each aspect/embodiment described in the present disclosure may be used alone, may be used in combination, or may be used by switching according to execution. In addition, the notification of predetermined information (for example, notification of “being X”) is not limited to being performed explicitly, but may be performed implicitly (for example, not notifying the predetermined information). good too.

Software, whether referred to as software, firmware, middleware, microcode, hardware description language or otherwise, includes instructions, instruction sets, code, code segments, program code, programs, subprograms, and software modules. , applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, and the like.

Software, instructions, information, etc. may also be sent and received over a transmission medium. For example, the software uses wired technology (coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), etc.) and/or wireless technology (infrared, microwave, etc.) to create websites, Wired and/or wireless technologies are included within the definition of transmission medium when sent from a server or other remote source.

Information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may refer to voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, light fields or photons, or any of these. may be represented by a combination of

The terms explained in this disclosure and the terms necessary for understanding the present disclosure may be replaced with terms having the same or similar meanings. For example, the channel and/or symbols may be signaling. A signal may also be a message. A component carrier (CC) may also be called a carrier frequency, a cell, a frequency carrier, or the like.

As used in this disclosure, the terms "system" and "network" are used interchangeably.

In addition, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values from a predetermined value, or may be expressed using other corresponding information. may be represented. For example, radio resources may be indexed.

The names used for the parameters described above are not limiting names in any way. Further, the formulas, etc., using these parameters may differ from those expressly disclosed in this disclosure. Since the various channels (e.g., PUCCH, PDCCH, etc.) and information elements can be identified by any suitable name, the various names assigned to these various channels and information elements are in no way restrictive names. is not.

In the present disclosure, "base station (BS)", "radio base station", "fixed station", "NodeB", "eNodeB (eNB)", "gNodeB (gNB)", " "access point", "transmission point", "reception point", "transmission/reception point", "cell", "sector", "cell group", " Terms such as "carrier", "component carrier" may be used interchangeably. A base station may also be referred to by terms such as macrocell, small cell, femtocell, picocell, and the like.

A base station may serve one or more (eg, three) cells. When a base station accommodates multiple cells, the overall coverage area of the base station can be partitioned into multiple smaller areas, each smaller area being associated with a base station subsystem (e.g., an indoor small base station (RRH: The term "cell" or "sector" refers to part or all of the coverage area of a base station and/or base station subsystem serving communication in this coverage. point to

In this disclosure, terms such as “Mobile Station (MS),” “user terminal,” “User Equipment (UE),” “terminal,” etc. may be used interchangeably. .

A mobile station is defined by those skilled in the art as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless It may also be called a terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable term.

At least one of a base station and a mobile station may be called a transmitter, a receiver, a communication device, and the like. At least one of the base station and the mobile station may be a device mounted on a mobile object, the mobile object itself, or the like. The mobile object may be a vehicle (e.g., car, airplane, etc.), an unmanned mobile object (e.g., drone, self-driving car, etc.), or a robot (manned or unmanned ). Note that at least one of the base station and the mobile station includes devices that do not necessarily move during communication operations. For example, at least one of the base station and the mobile station may be an IoT (Internet of Things) device such as a sensor.

Also, the base station in the present disclosure may be read as a user terminal. For example, communication between a base station and a user terminal is replaced with communication between multiple user terminals (for example, D2D (Device-to-Device), V2X (Vehicle-to-Everything), etc.) Regarding the configuration, each aspect/embodiment of the present disclosure may be applied. In this case, the user terminal may have the functions that the base station has. Also, words such as "up" and "down" may be replaced with words corresponding to inter-terminal communication (for example, "side"). For example, uplink channels, downlink channels, etc. may be read as side channels.

Similarly, user terminals in the present disclosure may be read as base stations. In this case, the base station may have the functions that the user terminal has.

As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Judgement", "determining" are, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (eg, lookup in a table, database, or other data structure), ascertaining as "judged" or "determined", and the like. Also, "judgment" and "decision" are used for receiving (e.g., receiving information), transmitting (e.g., transmitting information), input, output, access (accessing) (for example, accessing data in memory) may include deeming that something has been "determined" or "decided". In addition, "judgment" and "decision" are considered to be "judgment" and "decision" by resolving, selecting, choosing, establishing, comparing, etc. can contain. In other words, "judgment" and "decision" may include considering that some action is "judgment" and "decision". Also, "judgment (decision)" may be read as "assuming", "expecting", "considering", or the like.

The terms "connected," "coupled," or any variation thereof mean any direct or indirect connection or connection between two or more elements, It can include the presence of one or more intermediate elements between two elements being "connected" or "coupled." Couplings or connections between elements may be physical, logical, or a combination thereof. For example, "connection" may be read as "access". As used in this disclosure, two elements are defined using at least one of one or more wires, cables, and printed electrical connections and, as some non-limiting and non-exhaustive examples, in the radio frequency domain. , electromagnetic energy having wavelengths in the microwave and optical (both visible and invisible) regions, and the like.

As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly specified otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

Any reference to elements using the "first," "second," etc. designations used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, reference to a first and second element does not imply that only two elements can be employed or that the first element must precede the second element in any way.

Where "include," "including," and variations thereof are used in this disclosure, these terms are inclusive, as is the term "comprising." is intended. Furthermore, the term "or" as used in this disclosure is not intended to be an exclusive OR.

In this disclosure, where articles have been added by translation, such as a, an, and the in English, the disclosure may include the plural nouns following these articles.

In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean that "A and B are different from C". Terms such as "separate," "coupled," etc. may also be interpreted in the same manner as "different."

DESCRIPTION OF SYMBOLS 1... Information provision system, 10... Server, 11... Browsing history analysis part, 12... Reception part, 13... 1st selection part, 14... 2nd selection part, 15... List generation part, 16... Transmission part, 20... User Terminal, 30... Database group, 31... Browsing history database, 32... First content database, 33... First candidate keyword database, 34... Meta information database, 35... User database, 202... Keyword list.

Claims (7)

comprising at least one processor,
the at least one processor
Referring to a first database storing browsing histories indicating that a plurality of viewers, including the target user, have accessed first content provided from a first information source, and determining at least one first keyword based on the browsing histories. and select
referring to a second database storing meta information indicating the appearance frequency of keywords in the second content provided from a second information source, selecting at least one second keyword based on the meta information;
generating a keyword list including at least one of the at least one first keyword and at least one of the at least one second keyword;
displaying the keyword list on the terminal of the target user;
information system. the at least one processor
identifying one or more first candidate keywords from the first content for each access indicated by the browsing history;
calculating a feature amount for each of the one or more first candidate keywords for each access indicated by the browsing history, and generating a feature vector containing one or more combinations of the first candidate keyword and the feature amount;
generating a plurality of clusters by clustering the plurality of viewers based on their respective feature vectors;
Selecting the at least one first keyword from the plurality of first candidate keywords based on the one or more feature vectors corresponding to the cluster to which the target user belongs;
The information providing system according to claim 1. the at least one processor
summing the feature vectors for each combination of the viewer and the genre of the first content;
generating the plurality of clusters by clustering the plurality of viewers for each genre;
selecting the at least one first keyword based on the feature vector corresponding to the combination of the corresponding genre and the cluster to which the target user belongs;
The information providing system according to claim 2. the at least one processor
obtaining a predetermined reference feature amount for each of the one or more first candidate keywords;
for each of the one or more first candidate keywords, based on at least one of the elapsed time since the first content corresponding to the first candidate keyword was generated, and browsing operation on the first content to set the weights, and
calculating the feature amount by applying the weight to the reference feature amount for each of the one or more first candidate keywords;
The information providing system according to claim 2 or 3. The at least one processor selects, as the at least one second keyword, the keyword whose appearance frequency is greater than a predetermined criterion.
The information providing system according to any one of claims 1 to 4. the at least one processor
obtaining, for each of the one or more keywords indicated by the meta information, the number of hits of the first content corresponding to the keyword;
selecting the keyword as the at least one second keyword if the number of hits is greater than or equal to a predetermined threshold;
The information providing system according to any one of claims 1 to 5. the at least one processor causing the keyword list to be displayed on the terminal to provide the target user with keywords used for searching the first content at the first information source;
The information providing system according to any one of claims 1-6.

Images