Viewing information processing device and viewing information processing method

Abstract

To provide a viewing information processing device capable of appropriately correcting an abnormal attribute configuration when an abnormal attribute configuration is estimated as an attribute configuration of a viewer of a television device from viewing log information of the television device.SOLUTION: A viewing information processing device 1 includes an attribute configuration estimation unit 12 that estimates an attribute configuration of a viewer of a television device 23 from viewing log information output from the television device 23, and an attribute configuration correction unit 13 that corrects the attribute configuration when the estimated attribute configuration is a predetermined abnormal attribute configuration. The attribute configuration correction unit 13 corrects the attribute configuration according to the attribute-specific existence probability specified by the attribute configuration estimation unit 12.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a viewing information processing device and a viewing information processing method having a function of estimating viewer attribute configuration from viewing log information obtained for each television device. [Background technology]

[0002] In recent years, television devices have become widespread that have the capability to transmit viewing data, including viewing log information indicating which channel television broadcasts were viewed and when, to television manufacturers, etc. via an external network such as the Internet. In this specification, a device that can receive and view television broadcasts and has the capability to transmit viewing log information as described above is referred to as a television device.

[0003] As seen in Patent Document 1, for example, the present application proposes a technology for estimating the attribute composition of viewers of each television device (more specifically, one or more viewers who can watch television broadcasts received via the television device) from viewing log information obtained from the television device using a model (mathematical model) that has been pre-trained. Here, the attribute composition of viewers of a television device indicates which of multiple types of attributes, classified according to gender, age, etc., the viewers are made up of. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 6433615 Summary of the Invention [Problem to be solved by the invention]

[0005] As seen in the above-mentioned Patent Document 1, when the attributes of the constituent members of the viewers are estimated from the viewing log information obtained from each television device, the attribute composition of the viewers obtained by the estimation may be an abnormal attribute composition that is likely to be incorrect. For example, if the estimated viewer attributes are only young children, or if the number of types of estimated viewer attributes is zero (in other words, if it is estimated that there are no viewers of the television device), or if the number of types of estimated viewer attributes is too large, the estimated viewer attribute composition may be considered to be incorrect or an abnormal attribute composition that is likely to be incorrect.

[0006] Furthermore, if the viewing log information of a television device from which such an abnormal attribute configuration has been estimated and the attribute configuration of the viewer are used to investigate viewing conditions such as audience ratings by attribute, there is a risk that the reliability of the investigation results will be undermined.

[0007] Here, it is possible to exclude the viewing log information of television devices that are estimated to have abnormal attribute configurations from the targets for use in investigating viewing situations, but in that case, there is a risk that the total number of television devices that can be used may not be sufficient.

[0008] The present invention has been made in consideration of the above background, and aims to provide a viewing information processing device or viewing information processing method that has the function of estimating the attribute configuration of viewers of a television device from the viewing log information of the television device, and that, when an abnormal attribute configuration is estimated, can appropriately correct the abnormal attribute configuration. [Means for solving the problem]

[0009] In order to achieve the above object, the viewing information processing device of the present invention includes a television broadcast receiver and a viewing data output device capable of outputting viewing log information indicating when and which channel or broadcasting station television broadcast was viewed via the receiver, and a viewing log information acquisition unit that acquires viewing log information output from the television device; an attribute configuration estimation unit that estimates an attribute configuration of viewers of the television device from the viewing log information acquired by the viewing log information acquisition unit, the attribute composition estimation unit is configured to, when estimating the attribute composition of viewers of the television device, specify, for each type of attribute, an attribute-specific existence probability, which is the probability that viewers having the attribute exist, and to estimate a predetermined attribute determined based on the attribute-specific existence probability as an attribute of the constituent members of the viewers of the television device; and an attribute configuration correction unit that, when the attribute configuration estimated by the attribute configuration estimation unit is a predetermined abnormal attribute configuration, corrects the attribute configuration of the viewer of the television device from the abnormal attribute configuration in accordance with the attribute-specific presence probability of the viewer of the television device. 、 The attribute composition estimation unit is configured to calculate a total value of the attribute-specific presence probability values, select a predetermined number of people based on the total value in descending order of the attribute-specific presence probability value, and estimate the selected number as an attribute of the constituent members of the viewers of the television device. (First invention).

[0010] According to the first aspect of the present invention, when the attribute configuration estimated by the attribute configuration estimation unit for a viewer of a television device is an abnormal attribute configuration, the attribute configuration of the viewer of the television device is corrected in accordance with the attribute-specific existence probability for each attribute included in the attribute configuration, so that the attribute configuration can be corrected in accordance with the attribute-specific existence probability based on actual viewing log information for the television device. This makes it possible to appropriately correct the attribute configuration of the viewer of the television device from the estimated abnormal attribute configuration.

[0012] In addition, the first invention According to this, the attribute composition of a viewer of a television device can be easily and appropriately corrected based on the sum of the values ​​of the attribute-specific existence probability for each attribute included in the attribute composition estimated by the attribute composition estimation unit for the viewer of the television device. In addition, The attribute composition estimation unit is configured to estimate an attribute whose value of the attribute-specific existence probability is equal to or greater than a predetermined threshold as an attribute of a constituent member of the viewers of the television device. Good too.

[0013] This allows the attribute composition of viewers of a television device to be easily and appropriately corrected based on the value of the attribute-specific existence probability for each attribute included in the attribute composition estimated by the attribute composition estimation unit for the viewers of the television device.

[0014] In the present invention, with respect to any numerical value such as age or probability, "greater than or equal to A" may mean either greater than A, or greater than A or equal to A. Similarly, "equal to or less than A" may mean either smaller than A, or smaller than A or equal to A.

[0015] The viewing information processing device of the present invention includes a television receiver and a viewing data output device capable of outputting viewing log information indicating when and which channel or broadcasting station television broadcast was viewed via the receiver. The television receiver includes a viewing log information acquisition unit that acquires viewing log information output from the television device. an attribute configuration estimation unit that estimates an attribute configuration of viewers of the television device from the viewing log information acquired by the viewing log information acquisition unit, the attribute composition estimation unit is configured to, when estimating the attribute composition of viewers of the television device, specify, for each type of attribute, an attribute-specific existence probability, which is the probability that viewers having the attribute exist, and to estimate a predetermined attribute determined based on the attribute-specific existence probability as an attribute of the constituent members of the viewers of the television device; an attribute configuration correction unit that, when the attribute configuration estimated by the attribute configuration estimation unit is a predetermined abnormal attribute configuration, determines an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; the predetermined abnormal attribute configuration includes a first attribute configuration in which an attribute configuration of a viewer of the television device consists solely of a child attribute, the child attribute being an attribute of a child under a first predetermined age; When the attribute configuration estimated by the attribute configuration estimation unit is the first attribute configuration, the attribute configuration correction unit corrects the attribute configuration of the viewer of the television device to an attribute configuration including the child attribute and attribute A, which is an attribute having the highest value of the attribute-specific existence probability specified by the attribute configuration estimation unit among attributes other than the child attribute that satisfy a condition of being above a second predetermined age. Characterized by (No. 2 invention).

[0016] This allows the attribute configuration estimated as the first attribute configuration to be corrected to include not only child attributes but also attribute A, which is the attribute most likely to represent a television device viewer among attributes other than child attributes that satisfy the condition of being above a second predetermined age, i.e., to have an attribute configuration similar to that of a typical household with children. Therefore, the attribute configuration of television device viewers can be appropriately corrected from the first attribute configuration.

[0017] The above item 2 In the invention, when the attribute configuration estimated by the attribute configuration estimation unit is the first attribute configuration, if there is an attribute of age between the child attribute and the attribute that satisfies the condition of being above the second predetermined age, the value of the attribute-specific existence probability identified by the attribute configuration estimation unit is the same as Pa, which is the value of the attribute-specific existence probability for the attribute A, or a value higher than Pa, the attribute configuration correction unit may be configured to correct the attribute configuration of the viewer of the television device to further include the present attribute (the 3 invention).

[0018] According to this, even if an attribute has an age between the child attribute and an attribute that satisfies the condition of being above the second predetermined age, if the value of the attribute-specific existence probability is high (if there is a high possibility that the person is a viewer of the television device), the attribute can be further included in the attribute configuration of the viewer of the television device.

[0019] The viewing information processing device of the present invention includes a television receiver and a viewing data output device capable of outputting viewing log information indicating when and which channel or broadcasting station television broadcast was viewed via the receiver. The television receiver includes a viewing log information acquisition unit that acquires viewing log information output from the television device. an attribute configuration estimation unit that estimates an attribute configuration of viewers of the television device from the viewing log information acquired by the viewing log information acquisition unit, the attribute composition estimation unit is configured to, when estimating the attribute composition of viewers of the television device, specify, for each type of attribute, an attribute-specific existence probability, which is the probability that viewers having the attribute exist, and to estimate a predetermined attribute determined based on the attribute-specific existence probability as an attribute of the constituent members of the viewers of the television device; an attribute configuration correction unit that, when the attribute configuration estimated by the attribute configuration estimation unit is a predetermined abnormal attribute configuration, determines an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; the predetermined abnormal attribute configuration includes a second attribute configuration in which the number of types of attributes included in the attribute configuration of the viewer of the television device is zero; When the attribute configuration estimated by the attribute configuration estimation unit is the second attribute configuration, the attribute configuration correction unit corrects the attribute configuration of the viewer of the television device to an attribute configuration including attribute B, which is an attribute having the highest value of the attribute-specific existence probability specified by the attribute configuration estimation unit, among attributes that satisfy a condition of being a third predetermined age or older. Characterized by (No. 4 invention).

[0020] In addition, 4 The invention may be, for example, 2 Invention or 3When combined with the present invention, the attribute that satisfies the condition of being equal to or greater than the third predetermined age is an attribute of an age higher than the child attribute of being equal to or less than the first predetermined age. The third predetermined age may be lower than the second predetermined age, the same as the second predetermined age, or higher than the second predetermined age.

[0021] The above item 4 According to the present invention, the attribute configuration estimated as the second attribute configuration can be corrected to include the attribute that is most likely to be associated with a television device viewer among the attributes that satisfy the condition of being at least a third predetermined age, thereby making it possible to appropriately correct the attribute configuration of television device viewers from the second attribute configuration.

[0022] The above item 4 In the invention, an aspect may be adopted in which the attribute satisfying the condition of being equal to or greater than the third predetermined age is an attribute other than a child attribute, which is an attribute of a child equal to or less than a first predetermined age, and the attribute composition correction unit is configured to correct the attribute composition of the viewer of the television device to further include the child attribute when the attribute composition estimated by the attribute composition estimation unit is the second attribute composition, and the value of the attribute-specific existence probability identified by the attribute composition estimation unit for the child attribute is the same as or higher than Pb, which is the value of the attribute-specific existence probability identified for attribute B, and the attribute B is an attribute satisfying the condition of being equal to or greater than a fourth predetermined age that is higher than the third predetermined age (the 5 invention).

[0023] In addition, 5 The invention may be, for example, 2 Invention or 3 When combined with the present invention, the attribute that satisfies the condition of being equal to or greater than the fourth predetermined age is an attribute of an age higher than the child attribute of being equal to or less than the first predetermined age, and the fourth predetermined age may be lower than the second predetermined age, the same as the second predetermined age, or higher than the second predetermined age.

[0024] The above item 5 According to the invention, when the value of the attribute-specific existence probability identified for a child attribute is high (when there is a high possibility that the person is a viewer of a television device), and when attribute B is an attribute that satisfies the condition of being above the fourth predetermined age, the child attribute can be further included in the attribute configuration of the viewer of the television device.

[0025] Above No. 1 to No. 5 In the invention, the predetermined abnormal attribute configuration may include a third attribute configuration in which the number of types of attributes of the viewer of the television device is equal to or greater than a predetermined number. In this case, when the attribute configuration estimated by the attribute configuration estimation unit is the third attribute configuration, the attribute configuration correction unit may adopt an aspect in which, from among the attributes included in the third attribute configuration, the attribute configuration of the viewer of the television device is corrected to an attribute configuration in which one or more attributes, including at least the attribute with the lowest value of the attribute-specific existence probability identified by the attribute configuration estimation unit, are deleted (the third attribute configuration). 6 invention).

[0026] The above item 6 According to the present invention, the attribute configuration estimated as the third attribute configuration can be corrected by deleting one or more attributes from the third attribute configuration, the attributes including at least the attribute that is least likely to be of a television device viewer. Therefore, the attribute configuration of television device viewers can be appropriately corrected from the third attribute configuration.

[0027] In order to achieve the above object, the viewing information processing method of the present invention includes a first step of acquiring viewing log information output from a television device including a television broadcast receiver and a viewing data output device capable of outputting viewing log information indicating when and which channel or broadcasting station television broadcast was viewed via the receiver; a second step of estimating an attribute configuration of viewers of the television device from the viewing log information acquired in the first step, the second step is a step of, when estimating the attribute composition of viewers of the television device, specifying, for each type of attribute, an attribute-specific presence probability, which is the probability that viewers having the attribute exist, and estimating, as an attribute of the constituent members of viewers of the television device, a predetermined attribute determined based on the specified attribute-specific presence probability; a third step of determining, when the attribute configuration estimated in the second step is a predetermined abnormal attribute configuration, an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; The second step is characterized in that it is configured to calculate the sum of the values ​​of the attribute-specific presence probability, select a predetermined number of people based on the sum in order from the highest value of the attribute-specific presence probability, and estimate this as the attribute of the constituent members of the viewers of the television device (seventh invention). The viewing information processing method of the present invention includes a first step of acquiring viewing log information output from a television device including a television broadcast receiver and a viewing data output device capable of outputting viewing log information indicating when and which channel or broadcasting station television broadcast was viewed via the receiver; a second step of estimating an attribute configuration of viewers of the television device from the viewing log information acquired in the first step, the second step is a step of, when estimating the attribute composition of viewers of the television device, specifying, for each type of attribute, an attribute-specific presence probability, which is the probability that viewers having the attribute exist, and estimating, as an attribute of the constituent members of viewers of the television device, a predetermined attribute determined based on the specified attribute-specific presence probability; a third step of determining, when the attribute configuration estimated in the second step is a predetermined abnormal attribute configuration, an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; the predetermined abnormal attribute configuration includes a first attribute configuration in which an attribute configuration of a viewer of the television device consists solely of a child attribute, the child attribute being an attribute of a child under a first predetermined age; The third step is characterized in that, when the attribute configuration estimated in the second step is the first attribute configuration, the attribute configuration of the viewer of the television device is corrected to an attribute configuration that includes the child attribute and attribute A, which is the attribute identified in the second step and has the highest value of the attribute-specific existence probability among attributes other than the child attribute that meet the condition of being above a second predetermined age (8th invention). The viewing information processing method of the present invention includes a first step of acquiring viewing log information output from a television device including a television broadcast receiver and a viewing data output device capable of outputting viewing log information indicating when and which channel or broadcasting station television broadcast was viewed via the receiver; a second step of estimating an attribute configuration of viewers of the television device from the viewing log information acquired in the first step, the second step is a step of, when estimating the attribute composition of viewers of the television device, specifying, for each type of attribute, an attribute-specific presence probability, which is the probability that viewers having the attribute exist, and estimating, as an attribute of the constituent members of viewers of the television device, a predetermined attribute determined based on the specified attribute-specific presence probability; a third step of determining, when the attribute configuration estimated in the second step is a predetermined abnormal attribute configuration, an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; the predetermined abnormal attribute configuration includes a second attribute configuration in which the number of types of attributes included in the attribute configuration of the viewer of the television device is zero; The third step is characterized in that, when the attribute configuration estimated in the second step is the second attribute configuration, the attribute configuration of the viewers of the television device is corrected to an attribute configuration including attribute B, which is the attribute having the highest value of the attribute-specific existence probability identified in the second step, among attributes that satisfy a condition of being a third predetermined age or older. (9th invention).

[0028] The above item 7~ According to the 9th invention, if the attribute configuration estimated in the second step regarding the viewer of the television device is an abnormal attribute configuration, each The first invention , 2nd invention, 4th invention Similarly, since the attribute configuration can be corrected in accordance with the attribute-specific existence probability, the attribute configuration can be appropriately corrected from an abnormal attribute configuration. [Brief explanation of the drawings]

[0029] [Figure 1] 1 is a diagram showing an overall system according to an embodiment of the present invention. [Figure 2] 2 is a block diagram for explaining the processing of an attribute configuration estimation unit of the viewing information processing device shown in FIG. 1. [Figure 3] A flowchart for explaining the processing of the attribute configuration correction unit of the viewing information processing apparatus shown in FIG. 1. [Figure 4] A block diagram for explaining the processing of the viewing information generation unit by attribute of the viewing information processing apparatus shown in FIG. 1.

Embodiments for Carrying Out the Invention

[0030] An embodiment of the present invention will be described below with reference to FIGS. 1 to 4. In the following description of this embodiment, "above", "below", and "less than" are used in their normal meanings. That is, when A is above B, it means A ≥ B; when A is below B, it means A ≤ B; and when A is less than B, it means A < B.

[0031] Referring to FIG. 1, the system described in this embodiment includes a viewing information processing apparatus 1 that executes processing related to the investigation of the viewing status of television broadcasts. The viewing information processing apparatus 1 is constituted by, for example, one or more computers. The computer includes a processor such as a CPU (not shown), a memory (storage device), an interface circuit, a communication device, etc. And the viewing information processing apparatus 1 can acquire viewing data regarding the viewing of television broadcasts in each household by device 20 from a plurality of households by device 20 belonging to the area to be investigated for viewing status, etc. (for example, an area in units of prefectures, or an area combining a plurality of prefectures such as the Kanto region or the Kinki region). The viewing data is data including viewing log information indicating which channel (or which broadcasting station series) of television broadcast was viewed at what time.

[0032] Here, in this embodiment, each "device-specific household 20" refers to a household that includes a television device 23 that includes a television broadcast receiver 21 and a viewing data output device 22 that can output viewing data related to the viewing of the television broadcast, and that includes one or more viewers of the television device 23 (more specifically, one or more viewers who can watch the television broadcast received by the receiver 21 of the television device 23) as its members. In other words, a device-specific household 20 refers to a combination of a television device 23 and a viewer of the television device 23.

[0033] In this case, one device-specific household 20 is associated with each individual television device 23. Therefore, even if a dwelling unit is equipped with multiple television devices 23, one device-specific household 20 is associated with each of the multiple television devices 23. In this case, each device-specific household 20 corresponding to each of the multiple television devices 23 may include the same members as viewers. In other words, one or more members of one device-specific household 20 may be members of another device-specific household 20.

[0034] The television device 23 of each device-specific household 20 may be composed of a television or a television and a recording device connected to it. The viewing data output device 22 of the television device 23 may be composed of a processor such as a microcomputer, memory, an interface circuit, a communication device, etc. (not shown). The viewing data output device 22 can detect the channel of the television broadcast viewed via the television device 23 including it, as well as the date and time when the television broadcast on that channel was viewed (more specifically, the date and time when viewing of the television broadcast on that channel began and ended). From this detected information, viewing log information for the device-specific household 20 (hereinafter referred to as device-specific viewing log information) can be generated. In other words, the device-specific viewing log information is the viewing log information of all members included in the device-specific household 20.

[0035] The viewing data output device 22 can then periodically (or in response to a request from) transmit viewing data including the generated device-specific viewing log information to a server (not shown) of the manufacturer of the television or recording device that constitutes the television device 23 via an external network NW constituted by the Internet, a telephone line network, or the like. In this case, the viewing data transmitted from the viewing data output device 22 includes, in addition to the device-specific viewing log information, location information (e.g., information indicating the first three digits of the postal code) that has been registered in advance in the television or recording device that constitutes the television device 23, and identification information of the television device 23. Note that the identification information of the television device 23 can also be used as identification information of the device-specific household 20 that has the television device 23.

[0036] The viewing information processing device 1 includes, as functions realized by the implemented hardware configuration and program (software configuration), a viewing data acquisition unit 11, an attribute configuration estimation unit 12, an attribute configuration correction unit 13, an attribute-specific viewing information generation unit 14, and a viewing situation estimation unit 15. Hereinafter, the overall processing of the viewing information processing device 1 will be described together with details of each of these functional units.

[0037] The viewing data acquisition unit 11 can communicate with a server (not shown) of the manufacturer of each television device 23 in the device-specific household 20, and by performing this communication, can acquire viewing data of each television device 23 of that manufacturer. The viewing data acquisition unit 11 has a function as a viewing log information acquisition unit in the present invention.

[0038] Note that, when the viewing information processing device 1 can communicate with the viewing data output device 22 of the device-specific household 20, the viewing data acquisition unit 11 may acquire the viewing data of the television device 23 of the device-specific household 20 directly from the viewing data output device 22 of the television device 23. Furthermore, the viewing information processing device 1 may acquire the viewing data of the television device 23 from each manufacturer via an appropriate storage device.

[0039] The viewing information processing device 1 sequentially executes the processing of the attribute composition estimation unit 12, the attribute composition correction unit 13, the attribute-specific viewing information generation unit 14, and the viewing situation estimation unit 15 using viewing data acquired by the viewing data acquisition unit 11 for each device-specific household 20 in the survey area.

[0040] The attribute composition estimation unit 12 is a functional unit that estimates the attribute composition indicating which members of which attributes are included in the device-specific household 20 (in other words, the attribute composition of viewers of the television devices 23 of the device-specific household 20) from device-specific viewing log information for a predetermined period (e.g., one month, several months, one year, etc.) output from the television devices 23 of each device-specific household 20.

[0041] Here, the attributes of the members (viewers of television devices 23) of each device-specific household 20 are classified into multiple types of attributes based on, for example, the age and gender of the members. For example, the attributes are classified into multiple types such as children under y1, men aged y1 or older but younger than y2, women aged y1 or older but younger than y2, men aged y2 or older, and women aged y2 or older. Hereinafter, the number of types of attributes will be designated as N, and each of the N types of attributes will be appropriately represented as At(i) (i = 1, 2, ..., N). Note that the attributes of the members of each device-specific household 20 can be classified not only by age and gender, but also by various other parameters such as occupation and educational background.

[0042] As shown in FIG. 2, the attribute composition estimation unit 12 estimates the attribute composition of members of each device-specific household 20 using a first model that has been previously subjected to machine learning processing. Here, the first model is a model that has been previously subjected to machine learning processing so that the attribute composition of members of any device-specific household 20 belonging to the survey area can be estimated from the device-specific viewing logs for a predetermined period of the device-specific household 20. In the machine learning processing for the first model, viewing log information for each sample household obtained from people meters or the like installed in each of multiple sample households whose attribute composition is known, and the attribute composition for each sample household, are used as learning data. Furthermore, a publicly known algorithm can be used as the algorithm for the machine learning processing.

[0043] In this case, in this embodiment, the first model is configured to be able to determine, for each of N types of attributes At(i) (i = 1, 2, ..., N) from the device-specific viewing log information for each device-specific household 20 for a predetermined period, an attribute-specific presence probability, which is the probability that a member of each attribute At(i) is present in the device-specific household 20. As such a first model, for example, a model similar to the mathematical model for determining household composition in Patent Document 1 may be adopted. However, the first model may be of another form as long as it is able to determine the attribute-specific presence probability (or an index value similar thereto) from the device-specific viewing log information for each device-specific household 20 for a predetermined period.

[0044] Then, the attribute composition estimation unit 12 estimates attributes for which the attribute-specific presence probability identified by the first model is equal to or greater than a predetermined threshold (for example, 0.5 or greater) as attributes of the members of the device-specific household 20. As an example, FIG. 2 illustrates the processing of the attribute composition estimation unit 12 for one device-specific household 20 (in FIG. 2, the device-specific household 20 whose identification information ID is x1). Note that in the block diagram shown in FIG. 2 and FIG. 4 described below, the processing execution unit is indicated by a thick frame, and the data output unit or data is indicated by a thin frame.

[0045] 2, the attribute-specific presence probabilities of members of the device-specific household 20 are identified by the first model as shown in the figure from the device-specific viewing log information for a predetermined period of the device-specific household 20 whose identification information ID is x1. In this example, of N types of attributes At(i) (i=1, 2, ..., N), the attribute-specific presence probabilities of each of the attributes At(1), At(3), and At(N) are greater than or equal to a predetermined threshold (here, for example, 0.5), and the attribute-specific presence probabilities of each of the other attributes At(2), At(4) to At(N-1) are smaller than the threshold.

[0046] In this case, the attribute composition estimation unit 12 estimates that the attributes At(1), At(3), and At(N) whose attribute-specific existence probability is equal to or greater than the threshold value are attributes of the constituent members of the device-specific household 20 (viewers of the television device 23), and estimates that the attributes At(2), At(4) to At(N-1) whose attribute-specific existence probability is smaller than the threshold value are not attributes of the constituent members of the device-specific household 20. In this way, the attribute composition of the constituent members of the device-specific household 20 is estimated.

[0047] In this way, the attribute composition estimation unit 12 estimates the attribute composition of the constituent members of each device-specific household 20 by estimating whether or not constituent members (viewers) of each attribute are present in the device-specific household 20 based on whether or not the attribute-specific presence probability identified by the first model is greater than or equal to a predetermined threshold.

[0048] After executing the processing of the attribute composition estimation unit 12, the viewing information processing device 1 then executes the processing of the attribute composition correction unit 13. This attribute composition correction unit 13 is a functional unit that corrects the estimation result of the attribute composition of the members of the device-specific household 20 when the attribute composition estimated by the attribute composition estimation unit 12 for each device-specific household 20 is a predetermined abnormal attribute composition that is predetermined as an attribute composition that is likely to be incorrect.

[0049] Here, in this embodiment, for example, three types of attribute configurations (first to third attribute configurations) are predefined as predetermined abnormal attribute configurations. The first attribute configuration is an attribute configuration in which the members estimated by the attribute configuration estimation unit 12 for the device-specific household 20 consist only of members with the attribute of children under the age of y1 (or y1 or less) (hereinafter, this attribute will be referred to as the attribute At(1)) among N types of attributes At(i) (i = 1, 2, ..., N). In other words, the first attribute configuration is an attribute configuration in which, among the attribute-specific presence probabilities identified for each of the N types of attributes At(i) (i = 1, 2, ..., N), only the attribute-specific presence probability corresponding to the attribute At(1) of children under the age of y1 (or y1 or less) (hereinafter, simply referred to as the child attribute At(1)) is equal to or greater than a predetermined threshold. The age y1 corresponds to the first predetermined age in the present invention.

[0050] The second attribute configuration is an attribute configuration in which the attribute configuration estimated by the attribute configuration estimation unit 12 for the device-specific household 20 does not include any of the N types of attributes At(i) (i = 1, 2, ..., N) (i.e., the total number of attributes included in the attribute configuration is zero). In other words, the second attribute configuration is an attribute configuration in which all of the attribute-specific existence probabilities identified for each of the N types of attributes At(i) (i = 1, 2, ..., N) are smaller than a predetermined threshold.

[0051] The third attribute configuration is an attribute configuration in which the attribute configuration estimated by the attribute configuration estimation unit 12 for the device-specific household 20 has a predetermined number (for example, 5 or 6) or more types of attributes. In other words, the third attribute configuration is an attribute configuration in which, among the attribute-specific existence probabilities identified for each of N types of attributes At(i) (i = 1, 2, ..., N), the attribute-specific existence probability corresponding to each of the predetermined number or more types of attributes is equal to or greater than a predetermined threshold. In the following description, the predetermined number related to the third attribute configuration will be referred to as a predetermined number nx.

[0052] These first to third attribute configurations are attribute configurations that can be considered not to exist in reality (for example, the first attribute configuration or the second attribute configuration), or attribute configurations that can be considered to exist less frequently than attribute configurations other than the first to third attribute configurations (for example, the third attribute configuration).

[0053] The attribute composition correcting unit 13 receives the attribute composition estimated by the attribute composition estimating unit 12 for each device-specific household 20 and the attribute-specific existence probability identified by the first model of the attribute composition estimating unit 12. Then, the attribute composition correcting unit 13 determines, for each device-specific household 20, whether the estimated attribute composition is an abnormal attribute composition of any of the first to third attribute compositions described above, and corrects the attribute composition if the estimated attribute composition is any of the abnormal attribute composition.

[0054] Specifically, the attribute configuration correction unit 13 corrects the attribute configuration for each device-specific household 20 for which the attribute configuration estimated by the attribute configuration estimation unit 12 is an abnormal attribute configuration by performing processing as shown in the flowchart of Figure 3 for each device-specific household 20.

[0055] In STEP 1, the attribute configuration correction unit 13 determines whether the attribute configuration estimated for each device-specific household 20 is the third attribute configuration (an attribute configuration including a predetermined number nx or more of types of attributes). If the result of this determination is affirmative (if the estimated attribute configuration is the third attribute configuration), the attribute configuration correction unit 13 executes the processing of STEP 2.

[0056] In this STEP 2, the attribute configuration correction unit 13 corrects the attribute configuration of the device-specific household 20 (the device-specific household 20 for which the judgment result of STEP 1 was positive) to delete attributes selected in accordance with the attribute-specific existence probability identified for the device-specific household 20, thereby reducing the total number of attributes included in the attribute configuration of the device-specific household 20 to a total number less than a predetermined number nx.

[0057] Specifically, the attribute configuration correction unit 13 selects one or more types of attributes having lower probability values ​​(probability values ​​(including the lowest probability value) closer to the lowest probability value than the highest probability value) as attributes to be deleted from the attribute configuration of the device-specific household, among the multiple attributes (attributes of a predetermined number nx or more types) included in the attribute configuration estimated for the device-specific household 20. By deleting the selected attributes to be deleted from the attribute configuration of the device-specific household, the attribute configuration is corrected so that the total number of attributes after deletion is less than the predetermined number nx. In this case, of the multiple attributes included in the estimated attribute configuration, attributes with lower attribute-specific existence probability values ​​(probability values) are preferentially deleted.

[0058] The process of reducing the total number of attributes included in the attribute configuration as described above can be performed, for example, as follows. That is, the attribute configuration correction unit 13 selects and deletes attributes (attributes with lower probability values) having relatively low attribute-specific existence probability values ​​(probability values) from among the multiple attributes (attributes of a predetermined number nx or more types) included in the estimated attribute configuration, in order from the lowest probability value, until the total number of attributes after deletion becomes less than the predetermined number nx. In this case, if there are multiple attributes with the lowest attribute-specific existence probability values ​​among the attributes included in the attribute configuration before deletion, these multiple attributes are deleted at each repetition.

[0059] As an example, assume that the predetermined number nx is, for example, "5", the attribute composition estimated by the attribute composition estimation unit 12 for a certain device-specific household 20 is an attribute composition consisting of seven types of attributes, for example, At(1) to At(7), and the values ​​of the attribute-specific existence probability of At(1) to At(7) are 0.63 (:At(1)), 0.53 (:At(2)), 0.53 (:At(3)), 0.70 (:At(4)), 0.80 (:At(5)), 0.57 (:At(6)), and 0.57 (:At(7)).

[0060] In this case, from the attributes At(1) to At(7), the two attributes At(2) and At(3) with the lowest attribute-specific existence probability values ​​are deleted, and then the two attributes At(6) and At(7) with the next lowest attribute-specific existence probability values ​​are deleted. As a result, the attribute configuration of the device-specific household 20 is corrected to an attribute configuration consisting of three types of attributes At(1), At(4), and At(5).

[0061] In this embodiment, the process of STEP 2 (processing to correct the attribute configuration of the device-specific household 20 from the third attribute configuration) is performed as described above. As a result, the attribute configuration of the device-specific household 20 whose estimated attribute configuration is the third attribute configuration is corrected to an attribute configuration in which the number of types of attributes included therein is less than a predetermined number nx.

[0062] If the determination result of STEP 1 is negative (if the estimated attribute configuration is not the third attribute configuration), the attribute configuration correction unit 13 executes the process of STEP 3. The attribute configuration correction unit 13 also executes the process of STEP 3 after executing the process of STEP 2. In STEP 3, the attribute configuration correction unit 13 determines whether the estimated attribute configuration is the first attribute configuration (an attribute configuration including only the child attribute At(1)).

[0063] In this embodiment, the attribute configuration corrected by the processing in STEP 2 may be the first attribute configuration. For example, if the attribute configuration (=third attribute configuration) before correction by the processing in STEP 2 includes the child attribute At(1), and the attribute-specific existence probability values ​​of other attributes in the attribute configuration before correction are lower than the attribute-specific existence probability value of the child attribute At(1) and are the same, the attribute configuration corrected by the processing in STEP 2 will be an attribute configuration that includes only the child attribute At(1), i.e., the first attribute configuration. For this reason, in this embodiment, the attribute configuration correcting unit 13 executes the determination processing in STEP 3 not only when the determination result in STEP 1 is negative, but also after executing the processing in STEP 2.

[0064] If the judgment result of STEP 3 is positive (if the attribute configuration estimated by the attribute configuration estimation unit 12 or the attribute configuration after correction in STEP 2 is the first attribute configuration), the attribute configuration correction unit 13 executes the processing of STEP 4.

[0065] In this STEP 4, the attribute configuration correction unit 13 corrects the attribute configuration of the device-specific household 20 (the device-specific household 20 for which the judgment result of STEP 3 was positive) so that it becomes an attribute configuration that includes, in addition to the child attribute At(1), one or more attributes selected according to the attribute-specific existence probability identified for the device-specific household 20.

[0066] Specifically, the attribute configuration correction unit 13 selects, as an attribute to be added, the attribute with the highest value of attribute-specific presence probability from among the N types of attributes At(i) (i = 1, 2, ..., N) for which the attribute-specific presence probability has been determined for the device-specific household 20 by the attribute configuration estimation unit 12, from among the attributes that satisfy the condition of being a predetermined age or older (adult age), and corrects the attribute configuration of the device-specific household 20 so as to add the selected attribute to be added to the attribute configuration of the device-specific household 20 (an attribute configuration consisting only of the child attribute At(1)). In this case, if there are multiple attributes with the highest value of attribute-specific presence probability, these multiple attributes are added to the attribute configuration of the device-specific household 20. Note that the above-mentioned predetermined age corresponds to the second predetermined age or fourth predetermined age in the present invention.

[0067] For example, assume that the attribute configuration estimated by the attribute configuration estimation unit 12 for a certain device-specific household 20 is the first attribute configuration, the attributes that satisfy the condition of being above a certain age (adult age) are four types of attributes At(4) to At(7), and the attribute-specific presence probability values ​​of At(4) to At(7) are 0.45 (:At(4)), 0.36 (:At(5)), 0.45 (:At(6)), and 0.28 (:At(7)). In this case, among At(4) to At(7), the attributes with the highest attribute-specific presence probability values ​​are two types of attributes, At(4) and At(6), so these attributes At(4) and At(6) are selected as attributes to be added and added to the attribute configuration of the device-specific household 20. As a result, the attribute configuration of the device-specific household 20 is corrected from the first attribute configuration to an attribute configuration including three types of attributes, At(1), At(4), and At(6).

[0068] The same applies to the device-specific household 20 whose attribute configuration after correction in STEP 2 becomes the first attribute configuration. Additionally, in the processing of STEP 4, the attribute configuration after correction may become an attribute configuration (= third attribute configuration) that includes more than the predetermined number nx of types of attributes. Note that in the processing of STEP 4, the attribute configuration of the device-specific household 20 may be corrected so that it can include not only an attribute that satisfies the condition of being above a predetermined age (adult age) (hereinafter referred to as adult attribute), but also an attribute of an age between the adult attribute and the child attribute At(1) (hereinafter referred to as young person attribute).

[0069] Specifically, if the value of the attribute-specific presence probability for a certain young person attribute is equal to or greater than the highest attribute-specific presence probability value Pa among the attribute-specific presence probabilities of each adult attribute (either the same value as Pa or a value higher than Pa), not only the attribute whose attribute-specific presence probability value is Pa, but also the young person attribute having an attribute-specific presence probability value greater than Pa may be added to the attribute configuration of device-specific household 20.

[0070] For example, assume that there are four types of adult attributes, At(4) to At(7), and two types of youth attributes, At(2) and At(3), and the values ​​of the presence probability by attribute of At(2) to At(7) in the device-specific household 20 (the device-specific household 20 whose attribute configuration is estimated to be the first attribute configuration) are 0.49 (: At(2)), 0.30 (: At(3), 0.45 (: At(4)), 0.36 (: At(5)), 0.45 (: At(6)), and 0.28 (: At(7)). In this case, Of the human attributes At(4) to At(7), the attributes At(4) and At(6) with the highest attribute-specific existence probability values, and of the youth attributes At(2) and At(3), the attribute At(2) with a higher attribute-specific existence probability value than the attributes At(4) and At(6) are selected as attributes to be added and added to the attribute configuration of the device-specific household 20. As a result, the attribute configuration of the device-specific household 20 is corrected from the first attribute configuration to an attribute configuration including four types of attributes: At(1), At(2), At(4), and At(6).

[0071] In this embodiment, the process of STEP 4 (processing of correcting the attribute configuration of the device-specific household 20 from the first attribute configuration) is performed as described above. As a result, the attribute configuration of the device-specific household 20 whose attribute configuration estimated by the attribute configuration estimation unit 12 or whose attribute configuration after correction in STEP 2 has become the first attribute configuration is corrected to become an attribute configuration that further includes attributes (adult attributes) other than At(1). Note that when the processing of STEP 4 is executed, the processing of the attribute configuration correction unit 13 for the device-specific household 20 whose attribute configuration has been corrected by that processing is terminated (and thus the attribute configuration of the device-specific household 20 is confirmed).

[0072] If the determination result in STEP 3 is negative (if the attribute configuration estimated by the attribute configuration estimation unit 12 or the attribute configuration after correction in STEP 2 is not the first attribute configuration), the attribute configuration correction unit 13 executes the process of STEP 5. In STEP 5, the attribute configuration correction unit 13 determines whether the estimated attribute configuration is the second attribute configuration (an attribute configuration in which the total number of included attributes is zero).

[0073] Here, in this embodiment, the attribute configuration corrected by the processing in STEP 2 may become the second attribute configuration. For example, if the attribute-specific existence probability values ​​of multiple attributes (attributes with a number of types equal to or greater than the predetermined number nx) included in the attribute configuration (=third attribute configuration) before correction by the processing in STEP 2 are all the same, the attribute configuration corrected by the processing in STEP 2 becomes an attribute configuration in which the total number of attributes included therein is zero, i.e., the second attribute configuration. For this reason, in this embodiment, the attribute configuration correcting unit 13 executes the determination processing in STEP 5 not only when the determination results of both STEPs 1 and 3 are negative, but also when the determination result of STEP 3 becomes negative after the processing in STEP 2 is executed.

[0074] If the judgment result of STEP 5 is positive (if the attribute configuration estimated by the attribute configuration estimation unit 12 or the attribute configuration corrected in STEP 2 is the second attribute configuration), the attribute configuration correction unit 13 executes the processing of STEP 6.

[0075] In this STEP 6, the attribute configuration correction unit 13 corrects the attribute configuration of the device-specific household 20 (the device-specific household 20 for which the judgment result of STEP 5 was positive) so that it becomes an attribute configuration that includes one or more attributes selected according to the attribute-specific existence probability identified for the device-specific household 20.

[0076] Specifically, the attribute composition correction unit 13 selects, as an attribute to be added, an attribute with the highest value of the attribute-specific presence probability from the attributes At(2) to At(N) excluding the child attribute At(1) among the N types of attributes At(i) (i = 1, 2, ..., N) for which the attribute-specific presence probability has been identified for the device-specific household 20 by the attribute composition estimation unit 12, and corrects the attribute composition of the device-specific household 20 so that the attribute composition consisting of the selected attributes to be added becomes the attribute composition of the device-specific household 20. In other words, the attributes At(2) to At(N) excluding the child attribute At(1) are attributes that satisfy the condition of being equal to or greater than a predetermined age y1 (or an age higher than y1) related to the child attribute At(1), and the predetermined age y1 corresponds to the third predetermined age in the present invention.

[0077] In this case, if there are multiple attributes among the attributes At(2) to At(N) excluding the child attribute At(1) that have the highest attribute-specific existence probability, the attribute configuration of the device-specific household 20 is corrected so that it is composed of these multiple attributes.

[0078] For example, assume that the attribute configuration estimated by the attribute configuration estimation unit 12 for a certain device-specific household 20 is the second attribute configuration, and that among the attributes At(2) to At(N), the attribute-specific existence probability values ​​for At(3) and At(4) are both 0.47, and the attribute-specific existence probability values ​​for the other attributes At(2), At(5) to At(N) are all lower than 0.47. In this case, among the attributes At(2) to At(N), the attributes with the highest attribute-specific existence probability values ​​are the two attributes At(3) and At(4), so these attributes At(3) and At(4) are selected as attributes to be added, and the attribute configuration of the device-specific household 20 is corrected to an attribute configuration consisting of these attributes At(3) and At(4) to be added.

[0079] The same applies to the device-specific household 20 whose attribute configuration after correction in STEP 2 becomes the second attribute configuration. Additionally, in the processing of STEP 6, the attribute configuration after correction may become an attribute configuration (= third attribute configuration) that includes more than the predetermined number nx of attributes. Note that in the processing of STEP 6, the attribute configuration of the device-specific household 20 may be corrected so that it can include not only attributes other than the child attribute At(1), but also the child attribute At(1).

[0080] Specifically, if the value of the attribute-specific presence probability for the child attribute At(1) is equal to or greater than the highest attribute-specific presence probability value Pb among the attribute-specific presence probabilities other than the child attribute At(1) (either the same value as Pb or a value higher than Pb), and the attribute with the attribute-specific presence probability value Pb includes an adult attribute, then the child attribute At(1) may be added to the attribute configuration of the device-specific household 20 in addition to the attribute with the attribute-specific presence probability value Pa.

[0081] For example, assume that there are four adult attributes, At(4) to At(7), and two youth attributes, At(2) and At(3), and the attribute-specific presence probability of the child attribute At(1) in the device-specific household 20 (the device-specific household 20 whose attribute configuration is estimated to be the second attribute configuration) is 0.48, and among the attributes At(2) to At(7), the attribute-specific presence probability values ​​of At(3), which is a youth attribute, and At(4), which is an adult attribute, are both 0.47, and the attribute-specific presence probability values ​​of the other attributes At(2), At(5) to At(7) are all lower than 0.47. Among the attributes At(2) to At(7) other than the child attribute At(1), the attributes At(3) and At(4), which have the highest attribute-specific presence probability values, contain the adult attribute At(4), and the attribute-specific presence probability value of the child attribute At(1) is higher than the attribute-specific presence probability values ​​of the attributes At(3) and At(4). Therefore, in addition to the attributes At(3) and At(4), the child attribute At(1) is selected as an attribute to be added, and the attribute configuration of the device-specific household 20 is corrected to an attribute configuration consisting of these attributes At(1), At(3), and At(4) to be added.

[0082] In addition, if the only attribute with the highest attribute-specific existence probability value among the attributes At(2) to At(7) is the young person attribute (for example, At(3)), the child attribute At(1) will not be selected as an attribute to be added, even if the attribute-specific existence probability value of the child attribute At(1) is equal to or greater than the attribute-specific existence probability value of At(3). This prevents the attribute configuration after correction from being composed only of the child attribute At(1) and the young person attribute.

[0083] In this embodiment, the processing of STEP 6 (processing of correcting the attribute configuration of the device-specific household 20 from the second attribute configuration) is performed as described above. As a result, the attribute configuration of the device-specific household 20 whose second attribute configuration is the attribute configuration estimated by the attribute configuration estimation unit 12 or the attribute configuration corrected in STEP 2 is corrected to include one or more attributes.

[0084] In this embodiment, the processing of the attribute configuration correction unit 13 is executed as described above. As a result, in a device-specific household 20 in which the attribute configuration estimated by the attribute configuration estimation unit 12 is the first attribute configuration, the attribute configuration of the device-specific household 20 can be corrected so that, in addition to the child attribute At(1), at least an attribute (adult attribute) that satisfies the condition of being an adult of a predetermined age or older is included. In this case, the attributes added other than the child attribute At(1) are attributes with higher attribute-specific presence probability values ​​than the other attributes, so it is possible to minimize the deviation of the corrected attribute configuration from the actual attribute configuration of the device-specific household 20.

[0085] Furthermore, in a device-specific household 20 in which the attribute configuration estimated by the attribute configuration estimation unit 12 has become the second attribute configuration, the attribute configuration of the device-specific household 20 can be corrected so as to include one or more attributes other than the child attribute At(1). In this case, the attributes included in the corrected attribute configuration are attributes with a higher attribute-specific presence probability value than other attributes, so it is possible to minimize the deviation of the corrected attribute configuration from the actual attribute configuration of the device-specific household 20. Furthermore, because the attributes included in the corrected attribute configuration include at least attributes other than the child attribute At(1), it is possible to prevent the corrected attribute configuration from becoming an attribute configuration (=first attribute configuration) consisting only of the attributes of the child At(1).

[0086] Furthermore, in a device-specific household 20 in which the attribute configuration estimated by the attribute configuration estimation unit 12 is the third attribute configuration, the attribute configuration of the device-specific household 20 can basically be corrected so that the attribute configuration includes fewer types of attributes than the predetermined number nx. In this case, the attributes to be deleted from the attribute configuration before correction are attributes with a lower attribute-specific existence probability value than the other attributes, so it is possible to prevent the corrected attribute configuration from deviating as much as possible from the actual attribute configuration of the device-specific household 20.

[0087] Note that the attribute configuration after correction by the processing of STEP 4 or 6 may become a third attribute configuration including a predetermined number nx or more of types of attributes, but the frequency of occurrence of such a case is generally low. Also, the third attribute configuration is an attribute configuration that is more likely to actually exist than the first attribute configuration or the second attribute configuration. Therefore, in this embodiment, if the attribute configuration after correction by the processing of STEP 4 or 6 becomes the third attribute configuration, that attribute configuration is maintained.

[0088] The viewing information processing device 1 then executes processing by the attribute-specific viewing information generation unit 14. This attribute-specific viewing information generation unit 14 is a functional unit that generates attribute-specific viewing information indicating whether or not a television broadcast that is the subject of a survey of viewing situations (hereinafter referred to as a surveyed broadcast) has been viewed, for each attribute included in the attribute configuration of each device-specific household 20 that has been processed by the attribute configuration correction unit 13 (a device-specific household 20 whose attribute configuration has been determined).

[0089] As shown in Fig. 4, the attribute-specific viewing information generation unit 14 estimates attribute-specific viewing information for each attribute of the constituent factors of each device-specific household 20 from viewing log information for a predetermined period of time for each device-specific household 20 using a second model that has been subjected to machine learning processing in advance.

[0090] Here, in this embodiment, the second model is a model created separately for each of N types of attributes At(i) (i = 1, 2, ..., N). The second model corresponding to each attribute At(i) is a model that has been subjected to machine learning processing in advance so that, when the channel (or broadcasting station affiliate) of the survey target broadcast and date and time data indicating the date and time of the broadcast (month, day of the week, time slot, etc.) are specified, the probability that members (viewers) of the attribute At(i) have viewed the survey target broadcast (hereinafter referred to as attribute-specific viewing probability) can be determined from the device-specific viewing logs for a predetermined period of the device-specific household 20 to which the attribute At(i) belongs.

[0091] 2 shows that the viewing log information of a device-specific household 20 having members with a certain attribute At(n) is used to identify an attribute-specific viewing probability, which is the probability that members with the attribute At(n) watched a survey target broadcast specified by the channel (or broadcast station series) and date and time data. The same applies to second models corresponding to other attributes.

[0092] In the machine learning process for the second model described above, the learning data is the viewing log information for each member of each sample household, obtained from a people meter or the like installed in each of a plurality of sample households whose attribute configurations are known, and the attribute configuration of each sample household. A publicly known algorithm may be used as the algorithm for the machine learning process. Furthermore, the second model may be similar to the mathematical model for determining individual viewing behavior in Patent Document 1, for example. However, the second model may be of another form, as long as it can identify the attribute-specific viewing probability (or a similar index value) for the survey target broadcast for each attribute of the member of the device-specific household 20 from the device-specific viewing log information for the device-specific household 20 for a predetermined period of time.

[0093] Then, the attribute-specific viewing information generation unit 14 determines (estimates) for each attribute of each member of the device-specific household 20 whether or not the member of each attribute watched the survey target broadcast based on the attribute-specific viewing probability identified by the second model and the device-specific viewing log information of the device-specific household 20 (device-specific viewing log information including log information on the broadcast date and time of the survey target broadcast).

[0094] Specifically, the attribute-specific viewing information generation unit 14 determines that the survey target broadcast was viewed by a member of the attribute if the following conditions are met: for each attribute of the members of the device-specific household 20, the value of the attribute-specific viewing probability (probability value) for the survey target broadcast determined by the second model is equal to or greater than a predetermined threshold (for example, 0.5 or greater), and it is confirmed from the viewing probability information of the device-specific household 20 that there was actual viewing on the television broadcast channel (or broadcast station affiliate) at the broadcast date and time of the survey target broadcast; and if the conditions are not met, it determines that the survey target broadcast was not viewed by a member of the attribute.

[0095] For example, Figure 4 illustrates a situation in which it is determined that the broadcast being investigated was viewed by a member of the attribute At(n) when the attribute-specific viewing probability for attribute Ar(n) is equal to or greater than a predetermined threshold and when it is confirmed from device-specific viewing information that actual viewing occurred on the channel (or broadcasting station network) of the specified television broadcast on the date and time indicated by the date and time data of the specified television broadcast.

[0096] In this embodiment, the processing of the attribute-specific viewing information generation unit 14 is executed as described above. As a result, attribute-specific viewing information is generated for each attribute included in the attribute configuration determined for each device-specific household 20 by the attribute configuration correction unit 13, indicating whether or not the survey target broadcast, for which the channel (or broadcast station series) and date and time data are specified, has been viewed.

[0097] The viewing information processing device 1 then executes processing by the viewing situation estimation unit 15. This viewing situation estimation unit 15 is a processing unit that estimates viewing situation data (data equivalent to audience ratings) of the survey target broadcast for each attribute of the overall members of the device-specific households 20 in the survey target area, based on the attribute-specific viewing information obtained by processing by the attribute-specific viewing information generation unit 14 for each device-specific household 20 in the survey target area.

[0098] In this case, in this embodiment, if the total number of constituent members for each attribute At(i) (i = 1, 2, ..., N) in all device-specific households 20 in the survey area is denoted as M(i), and the total number of constituent members who are determined to have watched the survey target broadcast for each attribute At(i) is denoted as m(i), the viewing situation estimation unit 15 calculates the viewing situation data of the survey target broadcast for each attribute At(i), for example, using the following formula (1). Viewing status data for attribute At(i) = m(i) / M(i) ……(1)

[0099] This makes it possible to obtain viewing status data that corresponds to the viewing rate for each attribute in the surveyed area.

[0100] According to the viewing information processing device 1 of the present embodiment described above, when the attribute configuration of each device-specific household 20 estimated by the attribute configuration estimation unit 12 from the device-specific viewing log information of each device-specific household 20 in the survey area is an abnormal attribute configuration of any of the first attribute configuration, the second attribute configuration, and the third abnormal attribute, the attribute configuration is corrected according to the attribute-specific presence probability. This correction makes it possible to ensure that the survey area does not include device-specific households 20 with the first attribute configuration or the second attribute configuration, and that the number of device-specific households 20 with the third attribute configuration is kept sufficiently small.

[0101] Therefore, the attribute composition of each device-specific household in the survey area can be identified in a manner that ensures high reliability. As a result, it is possible to increase the reliability of the attribute-specific viewing information of each device-specific household processed by the attribute-specific viewing information generation unit 14 and the reliability of the viewing situation data processed by the viewing situation estimation unit 15. Ultimately, it is possible to properly survey the viewing situation in the survey area.

[0102] The present invention is not limited to the above-described embodiment, and other embodiments may be adopted. Some other embodiments are exemplified below. In the above embodiment, the attribute composition estimation unit 12 estimates an attribute for which the attribute-specific presence probability specified by the first model is equal to or greater than a predetermined threshold (for example, 0.5 or greater) as an attribute of the members of the device-specific household 20, but the present invention is not limited to this. Specifically, for a predetermined attribute determined based on the attribute-specific presence probability, the attribute composition estimation unit 12 may calculate the sum of the values ​​of the attribute-specific presence probability, select a predetermined number of people based on the sum in descending order of the values ​​of the attribute-specific presence probability (for example, if the sum is 1.8, which exceeds 1, then one person from the highest value; if the sum is 2.5, which exceeds 2, then two people from the highest value), and estimate the selected attribute as an attribute of the members of the device-specific household 20. In this case, when there are multiple people with the same attribute-specific existence probability value, the target person to be selected as a priority may be selected randomly, but priorities may also be set based on information such as "family composition," "TV manufacturer," and "viewing minutes." In addition, a method may be adopted in which the estimated number of people is defined for each attribute (not limited to the total value of the attribute-specific existence probability), and the attribute of the constituent factor is determined in order of the highest existence probability value. In addition, in the above embodiment, three types of attribute configurations, the first attribute configuration, the second attribute configuration, and the third attribute configuration, are used as the abnormal attribute information, but, for example, only the first attribute configuration and the second attribute configuration may be used as the abnormal attribute configuration, and the third attribute configuration may be excluded from the abnormal attribute configuration. Alternatively, for example, whether or not to exclude the third attribute configuration may be selected for each survey target area, or may be selected depending on whether or not the proportion of device-specific households 20 with the third attribute configuration among all device-specific households 20 whose attribute configurations have been estimated by the attribute configuration estimation unit 12 is higher than a predetermined value.

[0103] Furthermore, in the above embodiment, when the estimated attribute configuration is the third attribute configuration, if the attribute configuration includes multiple attributes that have the same attribute-specific existence probability value and that value is lower than the other attributes, all of the multiple attributes are selected as attributes to be deleted. However, in this case, for example, the attributes to be deleted may be selected randomly or according to a predetermined priority order from the multiple attributes that have the same attribute-specific existence probability value, within a range that satisfies the condition that the total number of attributes included in the attribute configuration after correction (after deleting one or more attributes) is less than the predetermined number nx.

[0104] In the above embodiment, when the estimated attribute configuration or the attribute configuration after correction from the third attribute configuration is the first attribute configuration, if the attribute configuration includes multiple attributes that satisfy the condition of being an attribute of adult age and have the same attribute-specific existence probability values ​​and higher values ​​than other attributes, the attribute configuration is corrected so that all of the multiple attributes are added to the attribute configuration. However, in this case, for example, the attribute to be added may be selected randomly or according to a predetermined priority from the multiple attributes with the same attribute-specific existence probability values, within a range that satisfies the condition that the total number of attributes included in the attribute configuration after correction (after addition of one or more attributes) is less than the predetermined number nx. This also applies when a new attribute is added to the attribute configuration when the estimated attribute configuration or the attribute configuration after correction from the third attribute configuration is the second attribute.

[0105] Furthermore, in the above embodiment, the viewing information processing device 1 is provided with the attribute-specific viewing information generation unit 14 and the viewing situation estimation unit 15, but the viewing information processing device of the present invention may not be provided with the attribute-specific viewing information generation unit 14 and the viewing situation estimation unit 15. In that case, the attribute-specific viewing information generation unit 14 and the viewing situation estimation unit 15 may be provided in a device separate from the viewing information processing device. Also, the attribute configuration estimated by the attribute configuration estimation unit 12 or corrected by the attribute configuration correction unit 13 may be used in processing separate from the attribute-specific viewing information generation unit 14 and the viewing situation estimation unit 15. [Explanation of symbols]

[0106] 1...viewing information processing device, 11...viewing data acquisition unit (viewing log information acquisition unit), 12...attribute composition estimation unit, 13...attribute composition correction unit, 21...receiver, 22...viewing data output device, 23...television device.

Claims

1. a viewing log information acquisition unit that acquires viewing log information output from a television device that includes a television broadcast receiver and a viewing data output device that can output viewing log information indicating which channel or broadcast station television broadcast was viewed and when via the receiver; an attribute configuration estimation unit that estimates an attribute configuration of viewers of the television device from the viewing log information acquired by the viewing log information acquisition unit, the attribute composition estimation unit is configured to, when estimating the attribute composition of viewers of the television device, specify, for each type of attribute, an attribute-specific existence probability, which is the probability that viewers having the attribute exist, and to estimate a predetermined attribute determined based on the attribute-specific existence probability as an attribute of the constituent members of the viewers of the television device; an attribute configuration correction unit that, when the attribute configuration estimated by the attribute configuration estimation unit is a predetermined abnormal attribute configuration, determines an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; The attribute composition estimation unit is configured to calculate the sum of the values ​​of the attribute-specific presence probability, select a predetermined number of people based on the sum in descending order of the attribute-specific presence probability value, and estimate the number as an attribute of the constituent members of the viewers of the television device.

2. A viewing log information acquisition unit that acquires viewing log information output from a television device that includes a television broadcast receiver and a viewing data output device that is capable of outputting viewing log information indicating which channel or broadcasting station's television broadcast was viewed and at what time via the receiver; an attribute configuration estimation unit that estimates an attribute configuration of viewers of the television device from the viewing log information acquired by the viewing log information acquisition unit, the attribute composition estimation unit is configured to, when estimating the attribute composition of viewers of the television device, specify, for each type of attribute, an attribute-specific existence probability, which is the probability that viewers having the attribute exist, and to estimate a predetermined attribute determined based on the attribute-specific existence probability as an attribute of the constituent members of the viewers of the television device; an attribute configuration correction unit that, when the attribute configuration estimated by the attribute configuration estimation unit is a predetermined abnormal attribute configuration, determines an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; the predetermined abnormal attribute configuration includes a first attribute configuration in which an attribute configuration of a viewer of the television device consists solely of a child attribute, the child attribute being an attribute of a child under a first predetermined age; A viewing information processing device characterized in that, when the attribute configuration estimated by the attribute configuration estimation unit is the first attribute configuration, the attribute configuration correction unit corrects the attribute configuration of the viewer of the television device to an attribute configuration that includes the child attribute and attribute A, which is the attribute with the highest value of the attribute-specific existence probability identified by the attribute configuration estimation unit among attributes other than the child attribute that satisfy the condition of being above a second predetermined age.

3. 3. The viewing information processing device according to claim 2, a viewer information processing device configured to correct the attribute configuration of the viewer of the television device so that, when the attribute configuration estimated by the attribute configuration estimation unit is the first attribute configuration, if there is an attribute, excluding the child attribute and the attribute that satisfies the condition of being above the second predetermined age, whose attribute-specific existence probability value identified by the attribute configuration estimation unit is the same as or higher than Pa, which is the attribute-specific existence probability value for attribute A, to further include the present attribute.

4. A viewing log information acquisition unit that acquires viewing log information output from a television device that includes a television broadcast receiver and a viewing data output device that can output viewing log information that indicates which channel or broadcasting station's television broadcast was viewed and when via the receiver; an attribute configuration estimation unit that estimates an attribute configuration of viewers of the television device from the viewing log information acquired by the viewing log information acquisition unit, the attribute composition estimation unit is configured to, when estimating the attribute composition of viewers of the television device, specify, for each type of attribute, an attribute-specific existence probability, which is the probability that viewers having the attribute exist, and to estimate a predetermined attribute determined based on the attribute-specific existence probability as an attribute of the constituent members of the viewers of the television device; an attribute configuration correction unit that, when the attribute configuration estimated by the attribute configuration estimation unit is a predetermined abnormal attribute configuration, determines an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; the predetermined abnormal attribute configuration includes a second attribute configuration in which the number of types of attributes included in the attribute configuration of the viewer of the television device is zero; A viewing information processing device characterized in that, when the attribute configuration estimated by the attribute configuration estimation unit is the second attribute configuration, the attribute configuration correction unit corrects the attribute configuration of the viewer of the television device to an attribute configuration that includes attribute B, which is the attribute with the highest value of the attribute-specific existence probability identified by the attribute configuration estimation unit, among the attributes that satisfy the condition of being a third predetermined age or older.

5. 5. The viewing information processing device according to claim 4, the attribute that satisfies the condition of being equal to or greater than the third predetermined age is an attribute other than a child attribute, which is an attribute of a child equal to or less than the first predetermined age; a viewer information processing device configured to correct the attribute composition of the viewer of the television device to further include the child attribute when the attribute composition estimated by the attribute composition estimation unit is the second attribute composition, the value of the attribute-specific presence probability identified by the attribute composition estimation unit for the child attribute is the same as or higher than Pb, which is the value of the attribute-specific presence probability identified for attribute B, and the attribute B is an attribute of a fourth predetermined age or above that is higher than the third predetermined age.

6. 6. The viewing information processing device according to claim 1, the predetermined abnormal attribute configuration includes a third attribute configuration in which the number of types of attributes of viewers of the television device is equal to or greater than a predetermined number; A viewing information processing device characterized in that, when the attribute configuration estimated by the attribute configuration estimation unit is the third attribute configuration, the attribute configuration correction unit corrects the attribute configuration of the viewer of the television device to an attribute configuration in which one or more attributes included in the third attribute configuration, including at least the attribute with the lowest value of the attribute-specific existence probability identified by the attribute configuration estimation unit, are deleted.

7. A first step of acquiring viewing log information output from a television device equipped with a television broadcast receiver and a viewing data output device capable of outputting viewing log information indicating when and which channel or broadcasting station television broadcast was viewed via the receiver; a second step of estimating an attribute configuration of viewers of the television device from the viewing log information acquired in the first step, the second step is a step of, when estimating the attribute composition of viewers of the television device, specifying, for each type of attribute, an attribute-specific presence probability, which is the probability that viewers having the attribute exist, and estimating, as an attribute of the constituent members of viewers of the television device, a predetermined attribute determined based on the specified attribute-specific presence probability; a third step of determining, when the attribute configuration estimated in the second step is a predetermined abnormal attribute configuration, an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; The second step is configured to calculate a total value of the attribute-specific presence probability values, select a predetermined number of people based on the total value in order of the higher attribute-specific presence probability values, and estimate the number of people as an attribute of the constituent members of the viewers of the television device.

8. A first step of acquiring viewing log information output from a television device equipped with a television broadcast receiver and a viewing data output device capable of outputting viewing log information indicating when and which channel or broadcasting station television broadcast was viewed via the receiver; a second step of estimating an attribute configuration of viewers of the television device from the viewing log information acquired in the first step, the second step is a step of, when estimating the attribute composition of viewers of the television device, specifying, for each type of attribute, an attribute-specific presence probability, which is the probability that viewers having the attribute exist, and estimating, as an attribute of the constituent members of viewers of the television device, a predetermined attribute determined based on the specified attribute-specific presence probability; a third step of determining, when the attribute configuration estimated in the second step is a predetermined abnormal attribute configuration, an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; the predetermined abnormal attribute configuration includes a first attribute configuration in which an attribute configuration of a viewer of the television device consists solely of a child attribute, the child attribute being an attribute of a child under a first predetermined age; The third step is a viewing information processing method characterized in that, when the attribute configuration estimated in the second step is the first attribute configuration, the attribute configuration of the viewer of the television device is corrected to an attribute configuration that includes the child attribute and attribute A, which is the attribute with the highest value of the attribute-specific existence probability identified in the second step among attributes other than the child attribute that satisfy the condition of being above a second predetermined age.

9. a first step of acquiring viewing log information output from a television device including a television broadcast receiver and a viewing data output device capable of outputting viewing log information indicating when and which channel or broadcasting station television broadcast was viewed via the receiver; a second step of estimating an attribute configuration of viewers of the television device from the viewing log information acquired in the first step, the second step is a step of, when estimating the attribute composition of viewers of the television device, specifying, for each type of attribute, an attribute-specific presence probability, which is the probability that viewers having the attribute exist, and estimating, as an attribute of the constituent members of viewers of the television device, a predetermined attribute determined based on the specified attribute-specific presence probability; a third step of determining, when the attribute configuration estimated in the second step is a predetermined abnormal attribute configuration, an attribute configuration of viewers of the television device by correcting the abnormal attribute configuration in accordance with an attribute-specific presence probability of viewers of the television device; the predetermined abnormal attribute configuration includes a second attribute configuration in which the number of types of attributes included in the attribute configuration of the viewer of the television device is zero; The third step is a viewing information processing method characterized in that, when the attribute configuration estimated in the second step is the second attribute configuration, the attribute configuration of the viewer of the television device is corrected to an attribute configuration that includes attribute B, which is the attribute with the highest value of the attribute-specific existence probability identified in the second step, among the attributes that satisfy the condition of being a third predetermined age or older.

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