JP2018195187A - Information providing device, information providing method, and information providing device program - Google Patents

Abstract

To provide information more suited to an object by using a user's behavior information and gene information.SOLUTION: An information providing device according to the present application comprises an acquisition part and a providing part. The acquisition part acquires behavior information indicating a user's behavior on a network and the user's gene information. The providing part provides information based on the user's behavior information to an object having gene information related to the user's gene information.SELECTED DRAWING: Figure 3

Description

  Embodiments described herein relate generally to an information providing apparatus, an information providing method, and an information providing apparatus program.

  Conventionally, genetic information obtained by genetic testing has been used in various fields. For example, Patent Literature 1 discloses a method for utilizing genetic test data that can be suitably used by life insurance companies, pharmaceutical companies, food companies, and the like.

JP 2001-256305 A

  However, in the above-described conventional technology, it is not always possible to provide more suitable information to the target person using the user behavior information and genetic information. For example, in the above-mentioned conventional technology, a genetic information file in which genetic information obtained by genetic testing is associated with medical history information of the examinee is created and provided to a medical, pharmaceutical, food development or manufacturing organization To do. In addition, the organization that has received the gene information file provides information (for example, medicine, food, etc.) based on the gene information file to the individual.

  As described above, since the above-described conventional technology merely provides information based on genetic information and the medical history information of the examinee, it is not always necessary for the subject to use the user's behavior information and genetic information. Therefore, it is not always possible to provide more suitable information.

  The present application has been made in view of the above, and an object thereof is to provide an information providing apparatus capable of providing more appropriate information to a target person using user behavior information and genetic information. And

  An information providing apparatus according to the present application includes an acquisition unit that acquires behavior information indicating a behavior of a user on a network and the genetic information of the user, and a target person having genetic information related to the genetic information of the user And a providing unit that provides information based on the behavior information of the user.

  According to one aspect of the embodiment, there is an effect that more suitable information can be provided to the target person using the behavior information and genetic information of the user.

FIG. 1 is a diagram illustrating an example of a providing process according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of the information providing system according to the embodiment. FIG. 3 is a diagram illustrating a configuration example of the information providing apparatus according to the embodiment. FIG. 4 is a diagram illustrating an example of a gene information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of a purchase history storage unit according to the embodiment. FIG. 6 is a diagram schematically illustrating an example of an analysis method for analyzing the relationship between behavior information and gene information. FIG. 7 is a diagram schematically illustrating an example of an analysis method for analyzing the relationship between behavior information and gene information. FIG. 8 is a diagram schematically illustrating an example of an analysis method for analyzing the relationship between behavior information and gene information. FIG. 9 is a flowchart illustrating an overall flow of a providing process performed by the information providing apparatus according to the embodiment. FIG. 10 is a diagram illustrating an example of a search history storage unit according to the embodiment. FIG. 11 is a diagram illustrating an example of a browsing history storage unit according to the embodiment. FIG. 12 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the information providing apparatus.

  Hereinafter, a mode for implementing an information providing apparatus, an information providing method, and an information providing apparatus program according to the present application (hereinafter referred to as “embodiment”) will be described with reference to the drawings. Note that the information providing apparatus, the information providing method, and the information providing apparatus program according to the present application are not limited to the embodiment. Moreover, in the following embodiment, the same code | symbol is attached | subjected to the same site | part and the overlapping description is abbreviate | omitted.

[1. Provision processing)
First, an example of a providing process according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of a providing process according to the embodiment. The providing process according to the embodiment is performed by the information providing apparatus 100 illustrated in FIG.

  In addition, the information providing system 1 according to the embodiment includes a user terminal 10 and an information providing apparatus 100 as shown in FIG. The user terminal 10 and the information providing apparatus 100 are connected to be communicable by wire or wireless via a network. Note that the information providing system 1 illustrated in FIG. 1 may include a plurality of user terminals 10 and a plurality of information providing apparatuses 100. As will be described later, the information providing system 1 includes an inspection organization server 30 and an external server 60.

  The user terminal 10 is a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. For example, the user terminal 10 displays information received from the information providing apparatus 100 on a screen or outputs a voice.

  Here, the premise of this embodiment is demonstrated. For example, based on the relationship between the purchase behavior of users on the network (for example, the behavior of buying a product that is a site) and the search behavior (for example, behavior of searching for information using a certain search keyword), a specific There is a data analysis technique (also referred to as “quality extended search” or “quality extended search”) in which a user who is not performing a purchase action searches for what kind of purchase action is performed.

  “Quality expansion search” will be described in more detail using an example. For example, a user who performs purchasing behavior such as “buy liquor” tends to search for information using the search keyword “beer”. To do. In such a case, if an unknown subject among the subjects whose purchase behavior is unknown performs an information search using the search keyword “beer”, this unknown subject may also “buy sake”. Predict that there is. In this way, “quality extended search” is a user who is predicted to take a certain action from a group of users using a plurality of types of information (in this example, there is a possibility of “buying alcohol”). It effectively searches for a certain user.

  The providing process performed by the information providing apparatus 100 according to the embodiment pays attention to such “quality extended search” and provides information by applying the gene information of the user to “quality extended search”. Specifically, the information providing apparatus 100 according to the embodiment acquires behavior information indicating behavior on a user's network and genetic information of the user. And the information provision apparatus 100 provides the information based on the said user's action information with respect to the subject who has the genetic information relevant to a user's genetic information.

  As described above, in this embodiment, “quality extension search” using genetic information refers to a target person (for example, a person whose behavior is unknown) having genetic information related to the user's genetic information. To search for a person who might behave in the same way. More specifically, “quality-enhanced search” using genetic information refers to a relationship between behavioral information and genetic information that a user who performs a specific behavior tends to have a specific gene. If it is issued, a target person having genetic information related to this genetic information is predicted from among target persons whose behavior is unknown as a person who may behave in the same manner as the user. Hereinafter, the providing process according to the embodiment will be described using an example.

  First, the information providing apparatus 100 acquires behavior information indicating the behavior of the user on the network and the genetic information of the user (Step S1). The gene information is a test result obtained by the genetic test, for example, a list of genes possessed by the user. The gene information is information indicating what type (genotype) the gene is associated with the occurrence of a specific disease. For example, a gene related to the onset of “cancer” is referred to as “GINE1” for convenience of explanation. And if a person whose type of “GINE1” is “a” type is known to have a particularly high incidence of “cancer”, the user can determine whether his “GINE1” You can know whether it is “a” type or not.

  The information providing apparatus 100 acquires such genetic information from a testing institution that has performed a genetic test. For example, the information providing apparatus 100 acquires gene information by accessing a server device (testing institution server) belonging to the testing institution. In addition, a predetermined contract is signed between the management company that manages the information providing apparatus 100 (hereinafter referred to as “management company T”) and the testing institution, and the user who has undergone the genetic test obtains consent. In such a case, it is possible to obtain such genetic information. The information providing apparatus 100 may receive gene information directly from a user who has undergone a genetic test. That is, it is not limited in what form the information providing apparatus 100 acquires the gene information.

  Further, the information providing apparatus 100 stores the acquired gene information in the gene information storage unit 121 which is a storage unit in the own apparatus. The genetic information storage unit 121 is a storage unit that stores genetic information obtained by genetic testing, and as shown in FIG. 1, identification information (user ID) for identifying each user who has undergone genetic testing, The user's genetic information is stored in association with each other.

  That is, the gene information storage unit 121 stores, as gene information, what type of gene each user has. For example, the gene information storage unit 121 stores, as gene information, what type of gene each user has among genes having a plurality of types by having SNP (Single Nucleotide Polymorphism). In addition, the gene information storage unit 121 stores, as gene information, what type of gene each user has in genes involved in the onset of disease.

  For example, in the gene information storage unit 121 illustrated in FIG. 1, the gene information of the user U1 indicates that the user U1 has genes “G1a”, “G2a”, “G3a”, “G4a”,. . Here, in this embodiment, the lower case alphabets assigned to the gene titles indicate the gene type. For example, the gene “G1a” indicates the “a” type gene “G1”. That is, it is indicated that the user U1 has the “a” type gene “G1” in the gene “G1” in which a plurality of types exist by SNP. Similarly, in the example of FIG. 1, the user U2 indicates that the gene “G1” having a plurality of types has the “b” type gene “G1”.

  Moreover, the information provision apparatus 100 acquires the purchase information which is the information regarding the purchase which the user performed as a user's action information. The purchase information is information indicating purchase behavior such as which user purchased what and when. That is, purchase information can be rephrased as purchase history. For example, the information providing apparatus 100 acquires purchase information from a predetermined server device (for example, a shopping server). And the information provision apparatus 100 stores the acquired purchase information in the purchase history storage part 122 which is a memory | storage part in an own apparatus.

  As shown in FIG. 1, the purchase history storage unit 122 stores identification information (user ID) for identifying each user and purchase information of the user in association with each other. That is, in the example of FIG. 1, the purchase history storage unit 122 stores purchase information such as what each user has purchased. The example of FIG. 1 shows an example in which the user U1 has performed a purchase action such as “buy a notebook computer P1”. Note that the information providing apparatus 100 may acquire purchase information at an arbitrary timing. For example, the information providing apparatus 100 periodically acquires purchase information.

  Moreover, each gene information memorize | stored in the gene information memory | storage part 121 and action information memorize | stored in the purchase history memory | storage part 122 are linked | related by common user ID for every user. In the example of FIG. 1, the gene information associated with the user ID “U1” and the purchase information associated with the user ID “U1” are associated with each other by the user ID “U1”. Further, such a user ID is account information uniquely issued when a user registers as a member to the management company T.

  Next, the information providing apparatus 100 analyzes the relationship between the purchase information acquired in step S1 and the gene information (step S2). Specifically, the information providing apparatus 100 analyzes whether or not a predetermined relationship is established between the behavior information and the gene information. For example, the information providing apparatus 100 analyzes whether or not the relationship based on the tendency between the behavior information and the gene information is established as the predetermined relationship. The relationship based on the tendency indicates a correlation.

  More specifically, the information providing apparatus 100 analyzes whether or not a correlation is established between each behavior information and each gene information by performing a correlation analysis between each behavior information and each gene information. . As an example, the information providing apparatus 100 indicates that a user who performs a purchase action such as “buy a notebook computer P1” tends to have a gene “G1a”, that is, a purchase action “buy a notebook computer P1”. It is analyzed whether or not a correlation is established with “G1a”. A specific analysis method will be described later.

  Next, the information providing apparatus 100 specifies behavior information and gene information that are correlated from the result of the correlation analysis (step S3). For example, when there is a gene that is correlated with the purchase behavior such as “buy notebook PC P1”, the information providing apparatus 100 is the gene stored in the gene information storage unit 121. Determine if it exists. In this example, it is assumed that the information providing apparatus 100 specifies that the purchase behavior “buy sake P3” and the gene “G2b” are correlated. In other words, the information providing apparatus 100 specifies a tendency indicating a correlation such that a user “buying sake P3” tends to have the gene “G2b”.

  In addition, the constitution that the gene “G2” gives to the user is related as a factor for obtaining such a tendency. For example, the gene “G2” is a gene involved in the enzyme activity of the alcohol metabolizing enzyme, and the alcohol metabolizing enzyme based on the “b” type gene “G2b” has a stronger enzyme activity. In such a case, the user having the gene “G2b” has a constitution that is “resistant to alcohol”, and as a result, the user likes liquor and tends to easily buy alcohol. Here, the constitution is taken as an example, but the same can be said for a disease. For example, users who have a gene that causes a particular disease tend to be more likely to perform purchasing behaviors related to the disease (for example, buying drugs related to the disease) and search behaviors (checking for diseases). It leads to.

  Therefore, the information processing apparatus 100 predicts not only the behavior information but also the correlation between the prediction information predicted from the behavior information (for example, constitution and disease) and the genetic information. It is also possible to make recommendations based on information.

  Then, the information providing apparatus 100 determines that if there is a subject having a gene related to (for example, the same or similar to) the gene “G2b” based on the above correlation, the subject is also “Sake P3 It is predicted that purchasing behavior such as “buy” will be performed. Then, the information providing apparatus 100 provides information to the target person. Here, a process in which the information providing apparatus 100 extracts a subject having the gene “G2b” will be described.

  For example, since the information providing apparatus 100 is a user who provides gene information and is registered as a member of the management company T, among the users who have an account with the management company T, the gene “G2b "Is extracted from the gene information storage unit 121. Next, the information providing apparatus 100 selects a user who has never performed a purchasing action with an account issued with the management company T among the users extracted from the genetic information storage unit 121, or “Sake” Users who have never performed purchasing behavior such as “buy P3”, that is, users whose purchasing behavior is unknown are extracted as target users. Here, it is assumed that the information providing apparatus 100 has extracted the user Ux.

  Therefore, the information providing apparatus 100 predicts that the user Ux extracted as the target person also performs a purchase action such as “buy sake P3”. And the information provision apparatus 100 provides the information based on purchasing action "buy sake P3" with respect to the user Ux (step S4). For example, when receiving a web page distribution request from the user terminal 10 of the user Ux, the information providing apparatus 100 distributes a web page on which an advertisement related to sake is displayed to the user terminal 10.

  In addition, as described above, from the relationship between the gene and the constitution or the disease, the information providing apparatus 100 predicts that “the constitution is strong against alcohol and may drink too much”, and is careful about excessive drinking. A web page that displays a reminder may be distributed.

  As described above, the information providing apparatus 100 according to the embodiment acquires behavior information indicating behavior on a user's network and genetic information of the user. And the information provision apparatus 100 provides the information based on the said user's action information that the target person who has the gene information relevant to a user's gene information may also take the same action as a user. .

  As described above, the information processing apparatus 100 can provide more appropriate information to the target person by using the behavior information and gene information of the user. For example, the information processing apparatus 100 uses a user's behavior information and genetic information, and a target person who cannot acquire purchase information (what kind of purchase is unknown) will purchase what product in the future. Since it is possible to predict whether or not there is a possibility, accurate advertisement distribution can be performed to the target person.

  In addition, the information processing apparatus 100 can predict the constitution and illness of the target person by using the behavior information and genetic information of the user. Therefore, the information processing apparatus 100 makes recommendations on the constitution and illness and contributes to the prevention of the disease. Can do.

[2. System configuration
Next, the configuration of the information providing system according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram illustrating a configuration example of the information providing system 1 according to the embodiment. As shown in FIG. 2, the information providing system 1 includes a user terminal 10, an inspection organization server 30, an external server 60, and an information providing apparatus 100. The user terminal 10, the inspection organization server 30, the external server 60, and the information providing apparatus 100 are connected via the network N so as to be communicable by wire or wirelessly.

  Although omitted in FIG. 1, the information providing system 1 according to the embodiment further includes an inspection organization server 30 and an external server 60 as shown in FIG. 2. The inspection institution server 30 is a server device belonging to a predetermined inspection institution that conducts a genetic test, and stores genetic information that is a test result. For example, the testing institution server 30 transmits genetic information to the information providing apparatus 100 in response to a request from the information providing apparatus 100.

  The external server 60 is a server device that is a source of various behavior information. For example, the external server 60 is a shopping server that provides an EC (Electronic Commerce) site such as a shopping site or an electronic mall. The shopping server accumulates purchase information (an example of behavior information) that is information related to purchase performed by the user.

  For example, the external server 60 is a search server that provides a search service. The search server stores search behavior information (an example of behavior information) that is information related to a search performed by a user using a search keyword.

  For example, the external server 60 is a content server that distributes web pages including advertisement content and article content. The content server stores advertisement browsing information (an example of behavior information), which is information related to browsing behavior when a user browses advertisement content. Further, the content server stores article browsing information (an example of behavior information) that is information related to browsing behavior in which a user browses article content.

  For example, the external server 60 is a stock transaction management server that provides content related to stock transactions. The stock transaction management server stores stock transaction information (an example of behavior information) that is information related to stock transactions performed by the user.

[3. Configuration of information providing device]
Next, the information providing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram illustrating a configuration example of the information providing apparatus 100 according to the embodiment. As illustrated in FIG. 3, the information providing apparatus 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

(About the communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). The communication unit 110 is connected to the network N by wire or wirelessly, and transmits / receives information to / from the user terminal 10, the inspection organization server 30, and the external server 60, for example.

(About the storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 120 includes a gene information storage unit 121 and a purchase history storage unit 122. Although not shown, the storage unit 120 further includes a storage unit in which information provided by the providing unit 134 is stored. As an example of this, the storage unit 120 includes an advertisement content storage unit that stores advertisement content.

(Regarding the gene information storage unit 121)
The genetic information storage unit 121 is a storage unit that stores genetic information obtained by genetic testing. Further, the gene information stored in the gene information storage unit 121 is acquired by the acquisition unit 131. Here, FIG. 4 shows an example of the gene information storage unit 121 according to the embodiment. In the example of FIG. 4, the gene information storage unit 121 includes items such as “user ID”, “gene information”, “name”, “address”, and “date of birth”.

  “User ID” indicates identification information for identifying a user. As described in FIG. 1, “gene information” indicates gene information based on an analysis result obtained by analyzing a user's gene by genetic testing. Specifically, the gene information is information such as what type of gene each user has among genes having a plurality of types by having an SNP. The gene information is information such as what type of gene each user has in genes involved in the onset of disease.

  “Name” indicates the name of the user. “Address” indicates the address of the user. “Birth date” indicates the date of birth of the user. The “name”, “address”, and “date of birth” are, for example, input by the user when applying for genetic testing.

  That is, in the example of FIG. 4, the user U1 has the gene “G1a” that is the gene “G1” of the “a” type among the genes “G1” having a plurality of types by SNP. Similarly, in the example of FIG. 1, the user U2 indicates that the gene “G1b” that is the gene “G1” of the “b” type among the genes “G1” having a plurality of types exists. In addition, as shown in FIG. 4, the code | symbol for identifying each gene information is attached | subjected to each gene information memorize | stored in the gene information storage part 121. FIG. For example, the symbol “rd11” is attached to the gene information corresponding to the user U1. Hereinafter, such gene information is referred to as “gene information rd11”. The same applies to other gene information.

(About the purchase history storage unit 122)
The purchase history storage unit 122 is a storage unit that stores a history of purchase information (an example of behavior information) that is information related to purchase performed by a user, that is, a purchase history. The purchase history storage unit 122 stores information such as when and what each user has purchased as purchase information. The purchase information stored in the purchase history storage unit 122 is acquired by the acquisition unit 131. Here, FIG. 5 shows an example of the purchase history storage unit 122 according to the embodiment. In the example of FIG. 5, the purchase history storage unit 122 includes items such as “user ID”, “purchased product”, and “purchase date / time”.

  “User ID” indicates identification information for identifying a user. The gene information stored in the gene information storage unit 121 and the purchase information stored in the purchase history storage unit 122 are associated with the same user ID. That is, gene information and purchase information associated with the same “user ID” are obtained from the same user. “Purchased product” indicates a product purchased by the corresponding user. “Purchase date” indicates the date and time when the “purchased product” was purchased by the corresponding user.

  That is, the example of FIG. 5 shows an example in which the user U1 performs a purchase action such as “buy the notebook computer P1” on “January 10, 2017”. As shown in FIG. 5, the purchase information stored in the purchase history storage unit 122 is assigned a code for identifying each purchase information. For example, the purchase information corresponding to the user U1 is given the code “pd11”. Hereinafter, such purchase information is referred to as “purchase information pd11”. The same applies to other purchase information.

(About the control unit 130)
Returning to FIG. 3, the control unit 130 executes various programs stored in a storage device inside the information providing apparatus 100 by using a RAM as a work area by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. Is realized. The control unit 130 is realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  As illustrated in FIG. 3, the control unit 130 includes an acquisition unit 131, an analysis unit 132, a specification unit 133, and a provision unit 134, and realizes or executes functions and operations of information processing described below. . Note that the internal configuration of the control unit 130 is not limited to the configuration illustrated in FIG. 3, and may be another configuration as long as the information processing described below is performed. In addition, the connection relationship between the processing units included in the control unit 130 is not limited to the connection relationship illustrated in FIG. 2, and may be another connection relationship.

(About the acquisition unit 131)
The acquisition unit 131 acquires behavior information indicating the behavior of the user on the network and the genetic information of the user. For example, the acquisition unit 131 acquires genetic information from a testing organization that has performed a genetic test. For example, the acquisition unit 131 acquires genetic information by accessing the inspection organization server 30 that is a server device belonging to the inspection organization. For example, the acquisition unit 131 periodically accesses the inspection organization server 30 and acquires gene information. Moreover, the acquisition part 131 stores the acquired gene information in the gene information storage part 121 as shown in FIG.

  Further, for example, the acquisition unit 131 acquires purchase information that is information related to purchase performed by the user as the behavior information of the user. For example, the acquisition unit 131 acquires purchase information by accessing the external server 60 (for example, a shopping server). For example, the acquisition unit 131 periodically accesses the external server 60 and acquires purchase information. Further, the acquisition unit 131 stores the acquired purchase information in the purchase history storage unit 122 as shown in FIG.

(About the analysis unit 132)
The analysis unit 132 analyzes the relationship between the behavior information acquired by the acquisition unit 131 and the gene information. Specifically, the analysis unit 132 analyzes whether or not a predetermined relationship is established between the behavior information and the gene information. For example, the analysis unit 132 analyzes whether the relationship based on the tendency between the behavior information and the gene information is established as the predetermined relationship. In the present embodiment, the analysis unit 132 analyzes whether or not a correlation is established between the behavior information and the gene information.

  For example, when the purchase information is acquired by the acquisition unit 131, the analysis unit 132 analyzes the relationship between the purchase information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether or not a correlation is established between purchase information and gene information. The following three patterns can be considered as analysis methods. Below, each pattern is demonstrated using purchase information as an example of action information.

(Pattern 1)
First, the pattern 1 will be described with reference to FIG. FIG. 6 is a diagram schematically illustrating an example of an analysis method for analyzing the relationship between behavior information and gene information. In pattern 1, the analysis unit 132 analyzes whether or not a correlation is established between each behavior information and each gene information by performing a correlation analysis between each behavior information and each gene information. First, the analysis unit 132 refers to the gene information storage unit 121 and lists users having the gene for each gene. Specifically, as shown in FIG. 6A, the analysis unit 132 assigns “1” to a user having the gene for each gene included in the gene information, and has the gene for each gene. “0” is given to users who do not. For example, in the example of the gene information storage unit 121 illustrated in FIG. 4, it can be seen from the gene information rd11 that the user U1 has the gene “G1a”. Therefore, the analysis unit 132 assigns “1” to the input field corresponding to the gene “G1a” and the user ID “U1” as illustrated in FIG. Then, the analysis unit 132 generates a gene-user list as shown in FIG.

  In addition, the analysis unit 132 refers to the purchase history storage unit 122 and lists the users who purchased each product during the period Tn (period according to time series). Here, the period T1 is “one month”, and this one month is further “January 1, 2017 to January 31, 2017”. In such a state, as illustrated in FIG. 6B, the analysis unit 132 performs purchases performed between “January 1, 2017 to January 31, 2017” in the acquired purchase information. “1” is assigned to a user who has purchased the product for each product included in the purchase information relating to “0”, and “0” is assigned to a user who has not purchased the product for each product. For example, in the example of the purchase history storage unit 122 shown in FIG. 5, it can be seen from the purchase information pd11 that the user U1 purchased “notebook PC P1” on “January 10, 2017”. Therefore, as shown in FIG. 6B, the analysis unit 132 assigns “1” to the input column corresponding to “notebook personal computer P1” and user ID “U1”. Then, the analysis part 132 produces | generates a goods (notebook personal computer P1) -user list as shown in FIG.6 (b).

  Similarly, the analysis unit 132 includes, in the acquired purchase information, products included in purchase information related to purchases performed between “February 1, 2017 and February 29, 2017” (period T2). A product-user list is generated by assigning “1” to a user who purchases the product every time and assigning “0” to a user who has not purchased the product for each product. That is, the analysis part 132 produces | generates goods (notebook personal computer P1) -user list for every period Tn. In addition, although the notebook personal computer P1 has been described as an example, as illustrated in FIG. 6B, the analysis unit 132 performs a product-user list for each period Tn for each product such as a suit P2 and sake S3. Is generated.

  Hereinafter, an example of a correlation analysis between the purchase behavior “buy the notebook computer P1” and the gene information “G1a” will be described. First, the variable X is the number of users who purchased “notebook personal computer P1” during the period Tn. Further, the variable Y is the number of users who have the gene “G1a” among the number of users who purchased “notebook personal computer P1” during the period Tn. In such a state, the analysis unit 132 counts the variable X and the variable Y for each period Tn corresponding to the time series, as illustrated in FIG. For example, the analysis unit 132 determines the number of users who purchased “notebook PC P1” in “January 1, 2017 to January 31, 2017” (period T1), and the gene “G1a” out of the number of users. Count the number of users who have Similarly, the analysis unit 132 performs counting for each period Tn. Here, it is assumed that the analysis unit 132 has obtained a count result as shown in FIG.

  The analysis unit 132 uses the count result to determine whether a user who performs a purchase action such as “buy a notebook computer P1” has a gene “G1a”, that is, a purchase action “buy a notebook computer P1”. It is analyzed whether a correlation is established with the information “G1a”. Specifically, the analysis unit 132 calculates a correlation coefficient using the count result. The analysis unit 132 then correlates that, for example, if the calculated correlation coefficient is equal to or greater than a predetermined value, a correlation is established between the purchase action “buy the notebook computer P1” and the genetic information “G1a”. Obtain analysis results. On the other hand, if the calculated correlation coefficient is equal to or less than the predetermined value, the analysis unit 132 obtains a correlation analysis result indicating that the purchase behavior “buy the notebook computer P1” and the genetic information “G1a” are not correlated.

  In FIG. 6, the purchase behavior “buy notebook PC P1” and genetic information “G1a” are described as examples. However, the analysis unit 132 corresponds to each product (for example, suit P2, sake S3, etc.). The correlation between the purchase information and gene information corresponding to each gene (for example, G1b, G2a, etc.) is analyzed, and a correlation coefficient is calculated.

(Pattern 2)
Next, pattern 2 will be described with reference to FIG. FIG. 7 is a diagram schematically illustrating an example of an analysis method for analyzing the relationship between behavior information and gene information. In Pattern 2, the analysis unit 132 performs correlation analysis between each behavior information and a combination of a plurality of gene information among the acquired gene information, so that each behavior information and a combination of a plurality of gene information are between Analyzes whether or not a correlation is established. First, the analysis unit 132 refers to the gene information storage unit 121 and lists a user having the gene for each combination of a plurality of genes. For example, when there are “300,000” candidate genes, there are “300,000 × 300,000” combinations of a plurality of genes. Specifically, as shown in FIG. 7A, the analysis unit 132 assigns “1” to a user having a combination of the genes for each combination of a plurality of genes, and for each combination of the plurality of genes. “0” is given to users who do not have the gene combination. For example, in the example of the gene information storage unit 121 illustrated in FIG. 4, it can be seen from the gene information rd11 that the user U1 has a combination of genes “G1a” and “G2a”. Therefore, as shown in FIG. 7A, the analysis unit 132 assigns “1” to the input field corresponding to such a combination. Then, the analysis part 132 produces | generates a gene combination-user list as shown to Fig.7 (a). Here, in order to simplify the explanation, a combination of a plurality of genes is a combination of two genes, but the number of genes to be combined is not limited.

  In addition, the analysis unit 132 refers to the purchase history storage unit 122 and lists the users who purchased each product during the period Tn (period according to time series). Here, the period T1 is “one month”, and this one month is further “January 1, 2017 to January 31, 2017”. In such a state, the analysis unit 132, as shown in FIG. 7 (b), out of the acquired purchase information, the purchase performed between “January 1, 2017 to January 31, 2017”. “1” is assigned to a user who has purchased the product for each product included in the purchase information relating to “0”, and “0” is assigned to a user who has not purchased the product for each product. For example, in the example of the purchase history storage unit 122 shown in FIG. 5, it can be seen from the purchase information pd11 that the user U1 purchased “notebook PC P1” on “January 10, 2017”. Accordingly, as shown in FIG. 7B, the analysis unit 132 assigns “1” to the input column corresponding to “notebook personal computer P1” and user ID “U1”. Then, the analysis part 132 produces | generates a goods (notebook personal computer P1) -user list as shown in FIG.7 (b).

  Similarly, the analysis unit 132 includes, in the acquired purchase information, products included in purchase information related to purchases performed between “February 1, 2017 and February 29, 2017” (period T2). A product-user list is generated by assigning “1” to a user who purchases the product every time and assigning “0” to a user who has not purchased the product for each product. That is, the analysis part 132 produces | generates goods (notebook personal computer P1) -user list for every period Tn. In addition, although the notebook personal computer P1 has been described as an example, as illustrated in FIG. 7B, the analysis unit 132 performs a product-user list for each period Tn for each product, such as a suit P2 and sake S3. Is generated.

  Hereinafter, an example of a correlation analysis between the purchase behavior “buy notebook PC P1” and the gene combination “G1a-G2a” will be described. First, the variable X is the number of users who purchased “notebook personal computer P1” during the period Tn. Further, among the number of users who purchased “notebook personal computer P1” during the period Tn, the number of users who have the gene combination “G1a-G2a” is defined as a variable Y. In such a state, the analysis unit 132 counts the variable X and the variable Y for each period Tn corresponding to the time series, as illustrated in FIG. For example, the analysis unit 132 may include the number of users who purchased “notebook PC P1” in “January 1, 2017 to January 31, 2017” (period T1), and a combination of genes among the number of users “ The number of users having “G1a-G2a” is counted. Similarly, the analysis unit 132 performs counting for each period Tn. Here, it is assumed that the analysis unit 132 has obtained a count result as shown in FIG.

  The analysis unit 132 uses the count result to determine whether the user who performs the purchasing action such as “buy the notebook computer P1” tends to have the gene combination “G1a-G2a”, that is, the purchasing action “notebook computer P1. It is analyzed whether a correlation is established between “buy” and the gene combination “G1a-G2a”. Specifically, the analysis unit 132 calculates a correlation coefficient using the count result. If the calculated correlation coefficient is equal to or greater than a predetermined value, for example, the analysis unit 132 establishes a correlation between the purchase action “buy the notebook computer P1” and the gene combination “G1a-G2a”. A correlation analysis result is obtained. On the other hand, if the calculated correlation coefficient is equal to or less than the predetermined value, the analysis unit 132 indicates that the purchase behavior “buy the notebook computer P1” and the gene combination “G1a-G2a” are not correlated. Get.

  In FIG. 7, the purchase behavior “buy notebook PC P1” and the combination of genes “G1a-G2a” have been described as examples. However, the analysis unit 132 analyzes each product (for example, suit P2, sake P3, etc.). And the correlation information between the purchase information corresponding to the gene information and the gene information corresponding to each gene combination (for example, “G1a-G2b”, “G1b-G2a”, etc.), and the correlation coefficient is calculated.

(Pattern 3)
Next, the pattern 3 will be described with reference to FIG. FIG. 8 is a diagram schematically illustrating an example of an analysis method for analyzing the relationship between behavior information and gene information. In Pattern 3, the analysis unit 132 performs a correlation analysis between a combination of a plurality of behavior information among the acquired behavior information and each gene information, so that the combination between the plurality of behavior information and each gene information is performed. Analyzes whether or not a correlation is established. In Pattern 3, it is assumed that a combination of a plurality of behavior information is a product group belonging to each product category. However, the present invention is not limited to this example, and the combination of the plurality of behavior information may be, for example, all combinations assumed by combining the products.

  First, the analysis unit 132 refers to the gene information storage unit 121 and lists users having the gene for each gene. Specifically, as shown in FIG. 8A, the analysis unit 132 assigns “1” to a user having the gene for each gene included in the gene information, and has the gene for each gene. “0” is given to users who do not. For example, in the example of the gene information storage unit 121 illustrated in FIG. 4, it can be seen from the gene information rd11 that the user U1 has the gene “G1a”. Therefore, the analysis unit 132 assigns “1” to the input field corresponding to the gene “G1a” and the user ID “U1” as illustrated in FIG. Then, the analysis unit 132 generates a gene-user list as shown in FIG.

  In addition, the analysis unit 132 refers to the purchase history storage unit 122 and lists users who have purchased products in each category during the period Tn (period according to time series). Here, the period T1 is “one month”, and this one month is further “January 1, 2017 to January 31, 2017”. In such a state, the analysis unit 132, as shown in FIG. 8 (b), stores the items of merchandise included in the purchase information related to the purchase performed between “January 1, 2017 to January 31, 2017”. Among these, “1” is assigned to a user who has purchased the product for each product belonging to each category, and “0” is assigned to a user who has not purchased the product for each product. For example, as illustrated in FIG. 8B, the analysis unit 132 assigns “1” to the input column corresponding to the category “PC main body” and the user ID “U1”. Then, the analysis part 132 produces | generates a goods category-user list as shown in FIG.8 (b).

  Similarly, the analysis unit 132 selects a product belonging to each category from among the products included in the purchase information related to the purchase performed between “February 1, 2017 and February 29, 2017” (period T2). A product category-user list is generated by assigning “1” to a user who purchases the product every time and assigning “0” to a user who has not purchased the product for each product. . That is, the analysis unit 132 generates a merchandise category-user list for each period Tn. Further, the category “PC main body” has been described as an example. However, as illustrated in FIG. 8B, the analysis unit 132 performs, for each category, for each period Tn, such as the category “male suit” and the category “alcohol”. The product category-user list is generated.

  Hereinafter, an example of a correlation analysis between the purchase behavior “buy a product belonging to the category“ personal computer ”” and the gene information “G1a” will be described. First, let the variable X be the number of users who purchased a product belonging to the category “personal computer” during the period Tn. In addition, the variable Y is the number of users who have the gene “G1a” among the number of users who purchased products belonging to the category “personal computer” during the period Tn. In such a state, the analysis unit 132 counts the variable X and the variable Y for each period Tn corresponding to the time series, as illustrated in FIG. For example, the analysis unit 132 determines whether the number of users who purchased a product belonging to the category “PC main body” in “January 1, 2017 to January 31, 2017” (period T1) and the gene of the number of users The number of users having “G1a” is counted. Similarly, the analysis unit 132 performs counting for each period Tn. Here, it is assumed that the analysis unit 132 has obtained a count result as shown in FIG.

  Then, the analysis unit 132 uses the count result to determine whether a user who performs a purchase action such as “buy a product belonging to the category“ personal computer ”” has a gene “G1a”, that is, the purchase action “category It is analyzed whether or not a correlation is established between “buy a product belonging to the“ personal computer ”” and the gene information “G1a”. Specifically, the analysis unit 132 calculates a correlation coefficient using the count result. Then, if the calculated correlation coefficient is equal to or greater than a predetermined value, for example, the analysis unit 132 has a correlation between the purchase behavior “buy products belonging to the category“ personal computer body ”” and the genetic information “G1a”. Correlation analysis result is obtained. On the other hand, if the calculated correlation coefficient is equal to or less than the predetermined value, the analysis unit 132 correlates that the purchase behavior “buy a product belonging to the category“ personal computer ”” and the genetic information “G1a” are not correlated. Obtain analysis results.

  In FIG. 8, the purchase behavior “buy a product belonging to the category“ PC main body ”” and the genetic information “G1a” are described as examples. However, the analysis unit 132 analyzes each category (for example, male suit, alcoholic beverage, etc.). ) And purchase information corresponding to each gene and gene information corresponding to each gene (for example, G1b, G2a, etc.) are analyzed, and a correlation coefficient is calculated.

(About the specific part 133)
Returning to FIG. 3, the specifying unit 133 has a predetermined relationship with the behavior information of the user among the genetic information of the user acquired by the acquiring unit 131 based on the analysis result obtained from the correlation analysis by the analyzing unit 131. The genetic information having sex (for example, correlation) is specified. In other words, the specifying unit 133 specifies a combination of correlated genetic information and behavior information among the user's genetic information and behavior information. For example, the specifying unit 133 specifies that there is a correlation with the behavior information and the gene information for which the analysis unit 132 has obtained a correlation result with a correlation coefficient equal to or greater than a predetermined value.

(About the providing unit 134)
The providing unit 134 provides information based on the user's behavior information to a target person who has genetic information related to the user's genetic information. For example, the providing unit 134 uses the user purchase information as the user behavior information by the acquisition unit 131 and uses the analysis unit 132 when the relationship between the behavior information and the gene information is analyzed by the analysis unit 132 as described above. The information based on the purchase information is provided to the target person who has the gene information related to the gene information having the relationship with the purchase information among the genetic information of the person.

  Here, it is assumed that the specifying unit 133 specifies that the purchase behavior “buy sake P3” and the gene “G2b” are correlated. In other words, the specifying unit 133 specifies a tendency indicating a correlation such that a user who “buys sake P3” tends to have the gene “G2b”.

  In such an example, if there is a target person who has a gene related to the gene “G2b” (for example, the same or similar), the providing unit 134 can also perform a purchasing action such as “buy sake P3”. Predict that there is sex. For example, the following can be considered as a predictable basis. Specifically, if the alcohol metabolizing enzyme based on the gene “G2b” has a stronger enzyme activity, a person having such a gene is “a constitution resistant to alcohol”, and consequently “likes liquor” It can be predicted that it is a person who can easily buy liquor.

  Therefore, the providing unit 134 predicts that there is a possibility of purchasing behavior such as “buy sake P3” if the subject has the gene “G2b”, and then the gene “G2b” actually has the enzyme activity. If it can be determined that the gene is caused by producing a stronger alcohol-metabolizing enzyme, information may be provided.

  That is, the providing unit 134 is a gene in which genetic information having a predetermined relationship (for example, correlation) with user behavior information is derived from prediction information (for example, constitution or disease) predicted from the behavior information. It is determined whether or not there is. And when providing part 134 determines with it being a gene which originates, you may provide the information based on a user's action information with respect to the subject who has the gene information relevant to this gene information. Note that such determination processing may be performed by a processing unit (for example, a determination unit) other than the providing unit 134. Now, an example of information provision by the providing unit 134 will be described below.

  For example, the providing unit 134 is a user who provides genetic information and is registered as a member of the management company T, so that the purchase action “Sake” The user having the gene “G2b” specified to be correlated with “Buy P3” is extracted from the gene information storage unit 121. Next, the providing unit 134, among the users extracted from the genetic information storage unit 121, a user who has never performed a purchasing action with an account issued with the management company T, or “Sake P3 Users who have not performed purchasing behavior such as “buy”, that is, users whose purchasing behavior is unknown are extracted as target users. Here, it is assumed that the providing unit 134 has extracted the user Ux.

  In such a case, the providing unit 134 may perform purchasing behavior such as “buy sake P3” for the user Ux extracted as the target person, or the user Ux is “sake-resistant constitution”, and consequently. In addition, based on the prediction that the person is liking liquor and is easy to buy liquor, information based on the purchase behavior “buy sake P3” is provided to the user Ux. For example, the providing unit 134 provides advertising content related to sake to the user Ux. Note that the timing of providing the advertisement content may be arbitrary. For example, the providing unit 134 may distribute advertisement content related to sake when receiving a distribution request for a predetermined web page from the user terminal 10 of the user Ux.

  Further, the providing unit 134 may provide the user Ux with recommendation information related to the constitution (for example, strong against alcohol) predicted for the user Ux.

[4. Processing procedure)
Next, the procedure of the providing process executed by the information providing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 9 is a flowchart illustrating the overall flow of the providing process performed by the information providing apparatus 100 according to the embodiment.

  First, the information providing apparatus 100 acquires behavior information indicating a user's behavior on the network and the user's genetic information (step S101). For example, the information providing apparatus 100 acquires genetic information from the inspection institution server 30 that is a server apparatus of a predetermined inspection institution. Moreover, the information provision apparatus 100 acquires action information from the external server 60 which accumulate | stores various action information.

  Next, the information providing apparatus 100 analyzes the relationship between behavior information and gene information (step S102). Specifically, the information providing apparatus 100 analyzes whether or not a predetermined relationship is established between the behavior information and the gene information. For example, the information providing apparatus 100 analyzes whether the relationship based on the tendency between the behavior information and the gene information, that is, the correlation is established as the predetermined relationship.

  Next, the information providing apparatus 100 specifies gene information having a correlation (correlation) with the user's behavior information from the analysis result in step S2 (step S103). . That is, the information providing apparatus 100 identifies which genetic information of the user's genetic information is associated with which behavior information of the user.

  Then, the information providing apparatus 100 provides information based on behavior information having a relationship with the gene information to a target person who has the gene information related to the gene information identified in Step S3 (Step S104).

[5. (Modification)
The information providing apparatus 100 according to the embodiment may be implemented in various different forms other than the above examples. Accordingly, other embodiments will be described below.

[5-1. Information provision based on search behavior)
In the above embodiment, the information providing apparatus 100 acquires purchase information as behavior information, and for a target person who has gene information related to gene information having a predetermined relationship with the purchase information among gene information, The example which provides the information based on this purchase information was shown. However, the information providing apparatus 100 may acquire information related to the search as behavior information and provide information based on the information related to the search.

  Specifically, the acquisition unit 131 acquires search behavior information that is information related to a search performed by a user using a search keyword as user behavior information. The analysis unit 132 also analyzes the relationship between the search behavior information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether or not a correlation is established between the search behavior information and the gene information.

  The specifying unit 133 also obtains gene information having a predetermined relationship (for example, correlation) with the user's search behavior information from the user's genetic information based on the analysis result obtained by the analysis unit 131. Identify. That is, the specifying unit 133 specifies a combination of correlated gene information and search behavior information among the user's gene information and search behavior information. Then, the providing unit 134 provides information based on the search behavior information to a target person who has gene information related to gene information having a predetermined relationship with the search behavior information among the gene information of the user. . Below, an example of the provision process in the case of using search action information as action information is demonstrated. In addition, although the example which uses purchase information as action information was shown in the said embodiment, this modified example uses search action information instead of purchase information. Therefore, description of the common processing will be simplified as appropriate.

  For example, the acquisition unit 131 acquires search behavior information that is information related to a search performed by a user using a search keyword by accessing the external server 60 (for example, a search server). The search behavior information is information indicating a search behavior such as when a user has performed an information search using what search keyword. Therefore, it can be said that the search behavior information is a search history. The acquisition unit 131 stores the acquired search behavior information in the search history storage unit 123 as illustrated in FIG. The search history storage unit 123 is a storage unit included in the storage unit 120.

  FIG. 10 is a diagram illustrating an example of the search history storage unit 123 according to the embodiment. In the example of FIG. 10, the search history storage unit 123 includes items such as “user ID”, “search keyword”, and “search date / time”. “User ID” indicates identification information for identifying the user who performed the search. The gene information stored in the gene information storage unit 121 and the search behavior information stored in the search history storage unit 123 are associated with the same user ID. “Search keyword” indicates a search keyword used (input) by a corresponding user. “Search date and time” indicates the date and time when the search was performed by the corresponding user. That is, the example of FIG. 10 shows an example in which the user U1 performs a search action using the search keyword “travel” on “January 10, 2017”.

  Further, as described in the above embodiment, the analysis unit 132 can analyze whether or not a correlation is established between the search behavior information and the gene information by using three patterns of analysis methods.

  In Pattern 1, the analysis unit 132 analyzes whether or not a correlation is established between each behavior information and each gene information by performing a correlation analysis between each search behavior information and each gene information. For example, the analysis unit 132 generates a gene-user list as described with reference to FIG. Moreover, the analysis part 132 produces | generates the goods-user list for every period Tn for every search action (each search keyword). Such a list corresponds to a product replaced with each search keyword (for example, travel, job change, etc.) in the product-user list for each period Tn shown in FIG.

  Then, the analysis unit 132 analyzes the correlation between the search behavior information information corresponding to each search keyword and the gene information corresponding to each gene, and calculates a correlation coefficient. For example, the analysis unit 132 uses the search keyword “travel” during the period T1 as a variable X, and searches using the search keyword “travel” during the period T1. Among the number of users, these variables are counted with the number of users having the gene “G1a” as a variable Y. Then, the analysis unit 132 determines that the user who searches using the search keyword “travel” has the gene “G1a”, that is, the search action “searches using the search keyword“ travel ”” and the gene information “ The correlation coefficient is calculated by performing a correlation analysis to determine whether or not the correlation is established with “G1a”. Similarly, the analysis unit 132 performs counting for each period Tn.

  In Pattern 2, the analysis unit 132 performs correlation analysis between each search behavior information and a combination of a plurality of pieces of gene information among the acquired gene information, so that each search behavior information and a combination of a plurality of gene information are Analyzes whether a correlation is established between them. For example, the analysis unit 132 generates a gene combination-user list as described with reference to FIG. Moreover, the analysis part 132 produces | generates the goods-user list for every period Tn for every search action (each search keyword). Such a list corresponds to a product replaced with each search keyword (for example, travel, job change, etc.) in the product-user list for each period Tn shown in FIG.

  Then, the analysis unit 132 analyzes the correlation between the search behavior information information corresponding to each search keyword and the gene information corresponding to each combination of genes, and calculates a correlation coefficient. For example, the analysis unit 132 uses the search keyword “travel” during the period T1 as a variable X, and searches using the search keyword “travel” during the period T1. Among the number of users, the number of users having the gene combination “G1a-G2a” is defined as a variable Y, and these variables are counted. Then, the analysis unit 132 has a tendency that the user who searches using the search keyword “travel” has the gene combination “G1a-G2a”, that is, the search action “searches using the search keyword“ travel ””. And a gene combination “G1a-G2a”, a correlation coefficient is calculated by performing a correlation analysis to determine whether a correlation is established. Similarly, the analysis unit 132 performs counting for each period Tn.

  In the pattern 3, the analysis unit 132 performs a correlation analysis between a combination of a plurality of search behavior information in the acquired search behavior information and each gene information, so that the combination of the plurality of search behavior information and each gene information Whether or not a correlation is established. In the pattern 3, it is assumed that a combination of a plurality of search behavior information is a search keyword group belonging to each category of search keywords. An example is a search keyword belonging to the search category “alcohol”. However, the present invention is not limited to this example, and the combination of the plurality of search behavior information may be, for example, all combinations assumed by combining the search keywords.

  For example, the analysis unit 132 generates a gene-user list as described with reference to FIG. Moreover, the analysis part 132 produces | generates the search category-user list for every period Tn for every search category. Such a list corresponds to a product in which the product is replaced with each search category in the product category-user list for each period Tn shown in FIG.

  And the analysis part 132 calculates a correlation coefficient by analyzing the correlation of the search action information corresponding to each search category, and the gene information corresponding to each gene. For example, the analysis unit 132 sets the number of users who have searched for a search keyword belonging to the search category “PC” in the period T1 as a variable X, and uses the search keyword belonging to the search category “PC” in the period T1. Among the number of users who have searched, the number of users having the gene “G1a” is taken as a variable Y, and these variables are counted. Then, the analysis unit 132 determines whether a user who performs a search with a search keyword belonging to the search category “computer” has a gene “G1a”, that is, performs a search with a search keyword belonging to the search action “search category“ computer ””. A correlation coefficient is calculated by performing a correlation analysis to determine whether a correlation is established between “perform” and the gene “G1a”.

  Here, it is assumed that the specifying unit 133 specifies from the correlation analysis result that the search action “search with the search keyword“ beer ”” and the gene “G2b” are correlated. In other words, the specifying unit 133 specifies a tendency indicating a correlation such that a user who “searches with the search keyword“ beer ”tends to have the gene“ G2b ”. In this example, the providing unit 134 provides advertising content related to beer or alcoholic beverages to the user Ux who is a target person having the gene “G2b”, for example.

  Thereby, the information providing apparatus 100 according to the embodiment can predict the search behavior of the target person when, for example, it is unknown what kind of search the target person performs, and is suitable for the target person. Information can be provided. For example, when providing the advertising content, the information providing apparatus 100 can provide the advertising content that is more suitable for the target person, so that the advertising effect can be enhanced.

[5-2. Information provision based on advertisement browsing behavior)
In addition, the information providing apparatus 100 may acquire information related to browsing of advertising content as behavior information and provide information based on information related to browsing of advertising content.

  Specifically, the acquisition unit 131 acquires advertisement browsing information, which is information related to browsing behavior in which the user browsed the advertisement content, as the user behavior information. The analysis unit 132 also analyzes the relationship between the advertisement browsing information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether or not a correlation is established between the advertisement browsing information and the gene information.

  The specifying unit 133 also obtains gene information having a predetermined relationship (for example, correlation) with the advertisement browsing information of the user among the gene information of the user based on the analysis result obtained by the analysis unit 131. Identify. That is, the specifying unit 133 specifies a combination of correlated gene information and search behavior information among the user's gene information and advertisement browsing information. Then, the providing unit 134 provides information based on the advertisement browsing information to a target person who has gene information related to the genetic information having a predetermined relationship with the advertisement browsing information among the genetic information of the user. .

  For example, the acquisition unit 131 accesses the external server 60 (for example, a content server) to acquire advertisement browsing information, which is information related to browsing behavior in which the user has browsed the advertisement content. The advertisement browsing information is information indicating search behavior such as which user browsed which advertisement content when. Therefore, it can be said that the advertisement browsing information is an advertisement browsing history. Note that any case may be defined as a user viewing an advertisement. For example, when the user selects advertising content, the selected advertising content may be defined as viewed. Moreover, you may define that the advertising content delivered to the user was browsed. In this modification, it is determined that the advertisement content selected by the user is viewed by the user.

  The acquisition unit 131 stores the acquired advertisement browsing information in the browsing history storage unit 124 as illustrated in FIG. The browsing history storage unit 124 is a storage unit included in the storage unit 120. FIG. 11 is a diagram illustrating an example of the browsing history storage unit 124 according to the embodiment. In the example of FIG. 11, the browsing history storage unit 124 includes items such as “user ID”, “advertisement content”, and “browsing date / time”.

  “User ID” indicates identification information for identifying a user who has viewed the advertisement content. The gene information stored in the gene information storage unit 121 and the advertisement browsing information stored in the browsing history storage unit 124 are associated with the same user ID. “Advertising content” indicates the advertising content browsed by the corresponding user. “Browsing date and time” indicates the date and time when the advertisement content was browsed by the corresponding user.

  Moreover, the analysis part 132 can analyze whether correlation is established between advertisement browsing information and gene information using the analysis method of 3 patterns, as demonstrated in the said embodiment. In Pattern 1, the analysis unit 132 analyzes whether or not a correlation is established between each advertisement browsing information and each gene information by performing a correlation analysis between each advertisement browsing information and each gene information. In Pattern 2, the analysis unit 132 performs correlation analysis between each advertisement browsing information and a combination of a plurality of pieces of gene information among the acquired gene information, so that each advertisement reading information and a combination of a plurality of gene information are Analyzes whether a correlation is established between them. In Pattern 3, the analysis unit 132 performs a correlation analysis between a combination of a plurality of pieces of advertisement browsing information among the obtained advertisement browsing information and each gene information, and thereby a combination of the plurality of pieces of advertisement browsing information and each gene information. Whether or not a correlation is established.

  Here, for example, it is assumed that the specifying unit 133 specifies from the correlation analysis result that the browsing action “view advertising content related to beer” and the gene “G2b” are correlated. In other words, the specifying unit 133 specifies a tendency indicating a correlation such that a user “browsing advertising content related to beer” tends to have the gene “G2b”. In this example, the providing unit 134 provides advertising content related to beer or alcoholic beverages to the user Ux who is a target person having the gene “G2b”, for example.

  Thereby, the information providing apparatus 100 according to the embodiment can predict the browsing behavior of the target person when, for example, it is unknown what advertisement content the target person browses. Appropriate information can be provided. For example, when providing the advertising content, the information providing apparatus 100 can provide the advertising content that is more suitable for the target person, so that the advertising effect can be enhanced.

[5-3. Information provision based on article browsing behavior)
The advertisement content may be article content. That is, the information providing apparatus 100 may acquire information related to browsing article content as behavior information and provide information based on information reports related to browsing article content.

  Specifically, the acquisition unit 131 acquires article browsing information, which is information related to browsing behavior in which the user has browsed article content, as user behavior information. The article content is, for example, a news article, an economic article, an entertainment-related article, a sports article, a blog, or the like. The analysis unit 132 also analyzes the relationship between the article browsing information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether or not a correlation is established between the article browsing information and the gene information. Although a detailed description of the analysis technique is omitted, patterns 1 to 3 can be used as described above.

  The specifying unit 133 also obtains gene information having a predetermined relationship (for example, correlation) with the user's article browsing information among the user's genetic information based on the analysis result obtained by the analysis unit 131. Identify. That is, the specifying unit 133 specifies a combination of correlated gene information and article browsing information among the user's gene information and article browsing information. Then, the providing unit 134 provides information based on the advertisement browsing information to a target person having genetic information related to gene information having a predetermined relationship with the article browsing information among the genetic information of the user. .

  Here, for example, it is assumed that the browsing action “browsing article content related to beer” and the gene “G2b” are specified to be correlated from the correlation analysis result by the specifying unit 133. In this example, the providing unit 134 provides information based on the browsing action “browsing article content related to beer” to the user Ux who is a target person having the gene “G2b”. For example, the providing unit 134 provides advertising content related to beer or liquor.

  Thereby, the information providing apparatus 100 according to the embodiment can predict the browsing behavior of the target person when, for example, it is unknown what advertisement content the target person browses. Appropriate information can be provided. For example, when providing the advertising content, the information providing apparatus 100 can provide the advertising content that is more suitable for the target person, so that the advertising effect can be enhanced.

[5-4. Information provision based on stock transaction information)
Moreover, the acquisition part 131 may acquire the stock transaction information which is the information regarding the stock transaction which the user performed as a user's action information. Then, the analysis unit 132 analyzes the relationship between the stock transaction information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether or not a correlation is established between the stock transaction information and the gene information.

  The identifying unit 133 also obtains gene information having a predetermined relationship (for example, correlation) with the user's stock transaction information out of the user's gene information based on the analysis result obtained by the analysis unit 131. Identify. That is, the specifying unit 133 specifies a combination of correlated gene information and stock transaction information among the user's gene information and stock transaction information. The providing unit 134 provides information based on the stock transaction information to a target person who has gene information related to the gene information having a predetermined relationship with the stock transaction information among the gene information of the user. .

  For example, the acquisition unit 131 acquires stock transaction information that is information related to stock transactions performed by the user by accessing the external server 60 (for example, a stock transaction management server). The stock trading information is information indicating stock trading behavior such as which user purchased how many stocks of which stock (brand). Further, the acquisition unit 131 stores the acquired stock transaction information as a stock transaction history in a predetermined storage unit (not shown).

  Further, as described in the above embodiment, the analysis unit 132 can analyze whether or not a correlation is established between the stock transaction information and the gene information by using the three patterns of analysis methods. In Pattern 1, the analysis unit 132 analyzes whether or not a correlation is established between each advertisement browsing information and each gene information by performing a correlation analysis between each stock transaction information and each gene information. In Pattern 2, the analysis unit 132 performs correlation analysis between each stock transaction information and a combination of a plurality of pieces of gene information among the acquired gene information, so that each stock transaction information and a combination of a plurality of gene information are Analyzes whether a correlation is established between them. In pattern 3, the analysis unit 132 performs a correlation analysis between a combination of a plurality of stock transaction information in the acquired stock transaction information and each gene information, thereby combining the plurality of stock transaction information and each gene information. Whether or not a correlation is established.

  Here, for example, it is assumed that, from the correlation analysis result, it is specified by the specifying unit 133 that the stock transaction “buy a predetermined number of stocks of a predetermined amount or more per stock” is correlated with the gene “G4a”. . In other words, it is assumed that the specifying unit 133 specifies a tendency indicating a correlation such that a user who “buys a predetermined number of stocks of a predetermined amount or more per share” tends to have the gene “G4a”. In this example, the providing unit 134 provides information based on the stock transaction “buy a predetermined number of stocks of a predetermined amount or more per share” to the user Ux who is a target person having the gene “G4a”. For example, if such stock trading is high risk, the providing unit 134 provides information to call attention or proposes better stock trading.

  In addition, for example, when the information (for example, account information) regarding the asset of the user Ux can be specified, the providing unit 134 purchases a predetermined number of shares equal to or more than a predetermined amount for each user Ux asset. It may be determined whether or not the stock transaction such as “has a risk, and information may be provided based on the determination result.

  Thereby, the information providing apparatus 100 according to the embodiment can predict the stock transaction of the target person when, for example, it is unknown what kind of stock transaction the target person performs, and is suitable for the target person. Provide information on stock trading.

[5-5. About genetic information)
In the said embodiment, the provision part 134 showed the example which provides the information based on the said user's action information with respect to the subject who has the same genetic information as a user's genetic information. However, the providing unit 134 provides information based on the user's behavior information to a target person having genetic information similar to the user's genetic information as genetic information related to the user's genetic information. Also good.

  Here, regarding gene information similar to the gene information of the user, the similarity may refer to the similarity of the structure, such as a gene similar to the structure of the user's gene. In addition, when there are multiple genes that cause common diseases, and the user's gene is one of these, similarity refers to any other of the multiple genes. It may be.

[6. Hardware configuration)
Further, the information providing apparatus 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in FIG. 12, for example. FIG. 12 is a hardware configuration diagram illustrating an example of a computer 1000 that implements the functions of the information providing apparatus 100. The computer 1000 includes a CPU 1100, RAM 1200, ROM 1300, HDD 1400, communication interface (I / F) 1500, input / output interface (I / F) 1600, and media interface (I / F) 1700.

  The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 and controls each unit. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, a program depending on the hardware of the computer 1000, and the like.

  The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. The communication interface 1500 receives data from other devices via the communication network 50 and sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the communication network 50.

  The CPU 1100 controls an output device such as a display and a printer and an input device such as a keyboard and a mouse via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. In addition, the CPU 1100 outputs the generated data to the output device via the input / output interface 1600.

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

  For example, when the computer 1000 functions as the information providing apparatus 100, the CPU 1100 of the computer 1000 realizes the function of the control unit 130 by executing a program loaded on the RAM 1200. The HDD 1400 stores data in the storage unit 120. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them. However, as another example, these programs may be acquired from other devices via the communication network 50.

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

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured.

  Moreover, each embodiment mentioned above can be combined suitably in the range which does not contradict a process content.

[8. effect〕
The information providing apparatus 100 according to the embodiment includes an acquisition unit 131 and a providing unit 134. The acquisition unit 131 acquires behavior information indicating the behavior of the user on the network and the genetic information of the user. The providing unit 134 provides information based on the user's behavior information to a target person who has genetic information related to the user's genetic information.

  As described above, the information processing apparatus 100 according to the embodiment can provide more appropriate information to the target person by using the behavior information and gene information of the user.

  The providing unit 134 provides information based on the behavior information to a target person having genetic information related to the genetic information having a predetermined relationship with the behavior information of the user among the genetic information of the user. To do.

  Thereby, the information processing apparatus 100 according to the embodiment provides, for example, more suitable information to the target person because the target person whose behavior is unknown can be predicted with high accuracy. be able to.

  Moreover, the acquisition part 131 acquires the search action information which is the information regarding the search which the user performed using the search keyword as a user's action information. Then, the providing unit 134 provides information based on the search behavior information to a target person who has gene information related to gene information having a predetermined relationship with the search behavior information among the gene information of the user. .

  Thereby, the information providing apparatus 100 according to the embodiment can predict the search behavior of the target person when, for example, it is unknown what kind of search the target person performs, and is suitable for the target person. Information can be provided. For example, when providing the advertising content, the information providing apparatus 100 can provide the advertising content that is more suitable for the target person, so that the advertising effect can be enhanced.

  Moreover, the acquisition part 131 acquires the purchase information which is the information regarding the purchase which the user performed as a user's action information. The providing unit 134 provides information based on the purchase information to a target person who has gene information related to gene information having a predetermined relationship with the purchase information among the gene information of the user.

  Thereby, the information providing apparatus 100 according to the embodiment can predict the purchase behavior of the target person when, for example, what kind of purchase is performed by the target person, and is therefore suitable for the target person. Information can be provided. For example, when providing the advertising content, the information providing apparatus 100 can provide the advertising content that is more suitable for the target person, so that the advertising effect can be enhanced.

  Moreover, the acquisition part 131 acquires the advertisement browsing information which is the information regarding the browsing action which the user browsed advertisement content as a user's action information. Then, the providing unit 134 provides information based on the advertisement browsing information to a target person who has gene information related to the genetic information having a predetermined relationship with the advertisement browsing information among the genetic information of the user. .

  Thereby, the information providing apparatus 100 according to the embodiment can predict the browsing behavior of the target person when, for example, it is unknown what advertisement content the target person browses. Appropriate information can be provided. For example, when providing the advertising content, the information providing apparatus 100 can provide the advertising content that is more suitable for the target person, so that the advertising effect can be enhanced.

  Moreover, the acquisition part 131 acquires the article browsing information which is the information regarding the browsing action which the user browsed the article content as a user's action information. The providing unit 134 provides information based on the article browsing information to a target person who has gene information related to gene information having a predetermined relationship with the article browsing information among the gene information of the user. .

  Thereby, the information providing apparatus 100 according to the embodiment can predict the browsing behavior of the target person when, for example, it is unknown what advertisement content the target person browses. Appropriate information can be provided. For example, when providing the advertising content, the information providing apparatus 100 can provide the advertising content that is more suitable for the target person, so that the advertising effect can be enhanced.

  Moreover, the acquisition part 131 acquires the stock transaction information which is the information regarding the stock transaction which the user performed as a user's action information. The providing unit 134 provides information based on the stock transaction information to a target person who has gene information related to the gene information having a predetermined relationship with the stock transaction information among the gene information of the user. .

  Thereby, the information providing apparatus 100 according to the embodiment can predict the stock transaction of the target person when, for example, it is unknown what kind of stock transaction the target person performs, and is suitable for the target person. Provide information on stock trading.

  Further, the providing unit 134 has, as the predetermined relationship, a target having gene information related to gene information having a relationship based on a tendency between the gene information and the user's behavior information among the gene information of the user. Information based on the user's behavior information is provided to the user.

  Thereby, the information processing apparatus 100 according to the embodiment can provide more suitable information to the target person.

  The providing unit 134 also provides information based on the user's behavior information to a target person having genetic information that is the same as or similar to the genetic information of the user as genetic information related to the genetic information of the user. I will provide a.

  Thereby, the information processing apparatus 100 according to the embodiment can provide more appropriate information to each target person.

  As described above, some of the embodiments of the present application have been described in detail with reference to the drawings. However, these are merely examples, and various modifications, including the aspects described in the disclosure section of the invention, based on the knowledge of those skilled in the art, It is possible to implement the present invention in other forms with improvements.

  In addition, the “section (module, unit)” described above can be read as “means” or “circuit”. For example, the acquisition unit can be read as acquisition means or an acquisition circuit.

DESCRIPTION OF SYMBOLS 1 Information provision system 10 User terminal 30 Inspection organization server 60 External server 100 Information provision apparatus 121 Gene information storage part 131 Acquisition part 132 Analysis part 133 Identification part 134 Provision part

Claims (11)

An acquisition unit for acquiring behavior information indicating behavior on a user's network and genetic information of the user;
An information providing apparatus, comprising: a providing unit that provides information based on the user's behavior information to a target person having genetic information related to the user's genetic information. The providing unit provides information based on the behavior information to a target person having genetic information related to genetic information having a predetermined relationship with the behavior information of the user among the genetic information of the user. The information providing apparatus according to claim 1, wherein: The acquisition unit acquires search behavior information that is information related to a search performed by the user using a search keyword as the user behavior information,
The providing unit provides information based on the search behavior information to a target person having gene information related to gene information having a predetermined relationship with the search behavior information among the genetic information of the user. The information providing apparatus according to claim 2. The acquisition unit acquires purchase information, which is information related to purchase performed by the user, as the user behavior information,
The providing unit provides information based on the purchase information to a target person having gene information related to gene information having a predetermined relationship with the purchase information among the gene information of the user. The information providing apparatus according to claim 2 or 3, characterized in that The acquisition unit acquires, as the user behavior information, advertisement browsing information that is information related to browsing behavior in which the user browsed the advertising content,
The providing unit provides information based on the advertisement browsing information to a target person who has gene information related to gene information having a predetermined relationship with the advertisement browsing information among the user's genetic information. The information providing apparatus according to any one of claims 2 to 4, wherein the information providing apparatus includes: The acquisition unit acquires, as the user behavior information, article browsing information that is information related to browsing behavior in which the user browsed article content;
The providing unit provides information based on the article browsing information to a target person who has gene information related to gene information having a predetermined relationship with the article browsing information among the user's genetic information. The information providing apparatus according to any one of claims 2 to 5, wherein the information providing apparatus includes: The acquisition unit acquires stock transaction information, which is information related to stock transactions performed by the user, as the user behavior information,
The providing unit provides information based on the stock transaction information to a target person having genetic information related to the gene information having a predetermined relationship with the stock transaction information among the gene information of the user. The information providing apparatus according to any one of claims 2 to 6, wherein the information providing apparatus includes: The providing unit has, as the predetermined relationship, an object having genetic information related to genetic information having a relationship based on a tendency between the genetic information and the user's behavior information among the genetic information of the user The information providing apparatus according to any one of claims 2 to 7, wherein information based on the behavior information of the user is provided to the user. The providing unit provides information based on the user's behavior information to a target person having genetic information that is the same as or similar to the genetic information of the user as genetic information related to the genetic information of the user The information providing device according to claim 1, wherein the information providing device is provided. An information providing method executed by the information providing apparatus,
An acquisition step of acquiring behavior information indicating behavior on the network of the user and genetic information of the user;
A providing step of providing information based on the user's behavior information to a target person having genetic information related to the user's genetic information. An acquisition procedure for acquiring behavior information indicating behavior on the user's network and the genetic information of the user;
An information providing program for causing a target person having genetic information related to the genetic information of the user to execute a providing procedure for providing information based on the behavior information of the user.

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