JP2011242996A - Output device, output method, and output program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To simplify operation that is necessary for obtaining desired information for a user.SOLUTION: An output device includes a preference attribute storage part for storing preference attributes for respective users that are attributes of user's preference. When identification information to identify a user is accepted, the output device reads out the preference attribute of the user identified with the identification information from the preference attribute storage part, and calculates a similarity with the preference attribute associated with other users stored in the preference attribute storage part for each of the other users. Then, the output device compares transmission information transmitted by another user having a high similarity calculated with transmission information of another user having a low similarity calculated to preferentially output the former transmission information.

Description

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

  There is a word-of-mouth system in which a plurality of users transmit information about contents, products, services, and the like, and a plurality of users receive information transmitted by other users. Information transmitted by the user is also referred to as “word of mouth information” or “transmitted information”. Here, when the user selects one of the categories of information prepared in advance or when the user inputs an arbitrary keyword, the word-of-mouth information that suits the user's preference from among a large amount of word-of-mouth information There is a narrowing down method. There is also a distribution device that distributes word-of-mouth information according to the current location of the user.

JP 2008-176570 A

  However, the above-described narrowing method has a problem that the user selects a category every time and takes time. Moreover, in the narrowing-down method described above, there is a problem that it takes time and effort because the user inputs a keyword every time. Moreover, it is not easy to select an appropriate combination of categories and keywords, and there is a problem that it is difficult for a user to acquire information that suits his / her preference with the above-described narrowing method. In addition, the distribution device only distributes the word-of-mouth information according to the position information.

  The disclosed technology has been made in view of the above, and an object thereof is to provide an output device, an output method, and an output program capable of simplifying an operation required for a user to acquire desired information. .

  In one aspect of the disclosed technology, a preference attribute storage unit that stores a preference attribute that is a user preference attribute for each user is provided. When the output device receives the identification information for identifying the user, the output device reads the preference attribute of the user identified by the identification information from the preference attribute storage unit, and associates the preference with the user other than the user. A similarity calculation unit that calculates the similarity with the preference attribute stored in the attribute storage unit for each different user is provided. Further, the output device preferentially outputs the transmission information transmitted by another user whose high similarity is calculated by the similarity calculation unit compared with the transmission information of another user whose low similarity is calculated. An output unit is provided.

  According to one aspect of the disclosed technology, there is an effect that the operation required for the user to acquire desired information can be simplified.

FIG. 1 is a block diagram illustrating an example of the configuration of the output device according to the first embodiment. FIG. 2 is a diagram illustrating an example of preference attributes stored in the preference attribute table in the first embodiment. FIG. 3 is a diagram illustrating similarity calculation processing by the attribute similarity calculation unit according to the second embodiment. FIG. 4 is a diagram illustrating an example of output processing by the word-of-mouth information output control unit according to the first embodiment. FIG. 5 is a flowchart illustrating an example of a flow of processing performed by the output device according to the second embodiment. FIG. 6 is a block diagram illustrating an example of the configuration of the output device according to the second embodiment. FIG. 7 is a diagram illustrating an example of information stored in the browsing log table according to the second embodiment. FIG. 8 is a flowchart illustrating an example of a processing flow by the preference attribute update unit according to the second embodiment.

  Hereinafter, embodiments of the disclosed output device, output method, and output program will be described in detail with reference to the drawings. Note that the invention disclosed by this embodiment is not limited. Each embodiment can be appropriately combined within a range in which processing contents do not contradict each other.

  The output device 100 according to the first embodiment will be described. The output device 100 stores a preference attribute that is a user preference attribute, as will be described in detail below. Then, when the output device 100 narrows down information that matches the user's preference, the output device 100 compares the transmission information transmitted by another user with a similar preference attribute with the transmission information of another user with a similar preference attribute. Output with priority. That is, the transmission information of other users having a preference similar to their own preference is considered useful, and the output device 100 outputs the transmission information of other users with similar preference attributes. As a result, the operation required for the user to obtain desired information can be simplified.

[Configuration of Output Device According to Embodiment 1]
1 shows an exemplary configuration of an output device 100 according to a first embodiment. FIG. 1 is a block diagram illustrating an example of the configuration of the output device according to the first embodiment. In the example illustrated in FIG. 1, the output device 100 includes an input / output unit 101, a storage unit 200, and a control unit 300.

  The input / output unit 101 is connected to the control unit 300. The input / output unit 101 receives information and instructions from the user, and inputs the received information to the control unit 300. The input / output unit 101 receives information from the control unit 300 and outputs the received information. The input / output unit 101 includes, for example, a keyboard, a mouse, and a microphone, and includes a monitor, a speaker, and the like. That is, for example, the input / output unit 101 receives information from the user via a keyboard, mouse, microphone, or the like, and outputs the information received from the control unit 300 from a monitor, a speaker, or the like.

  The details of the information received by the input / output unit 101 and the details of the information output by the input / output unit 101 will not be described here, and will be described together with the description of each related unit.

  The storage unit 200 is connected to the control unit 300. The storage unit 200 stores data used for various processes performed by the control unit 300. The storage unit 200 is, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. In the example illustrated in FIG. 1, the storage unit 200 includes a preference attribute table 201 and a word-of-mouth information table 202.

  The preference attribute table 201 stores a preference attribute that is a user preference attribute for each user. For example, the preference attribute table 201 stores, for each preference attribute item, an attribute value indicating a degree that the user likes or dislikes. The preference attribute table 201 stores, as preference attributes, for example, a user's preference for food and a user's preference for clothing miscellaneous goods. Information stored in the preference attribute table 201 is, for example, a value input for each preference attribute by the user himself / herself. The preference attribute table 201 is also referred to as a “preference attribute storage unit”.

  FIG. 2 is a diagram illustrating an example of preference attributes stored in the preference attribute table in the first embodiment. In the example illustrated in FIG. 2, a case where the preference attribute table 201 stores a user's preference for food as a preference attribute is illustrated. More specifically, in the example shown in FIG. 2, a case where “spiciness”, “sweetness”, “miso”, and “soy sauce” are stored as preference attributes is shown. In the example illustrated in FIG. 2, the preference attribute table 201 stores the preference attributes for “user 1”, “user 2”, “user 3”, and “user 4”. However, the present invention is not limited to this, and the preference attribute table 201 may store preference attributes for other users or may store other preference attributes.

  Below, it demonstrates using the case where the value which a preference attribute table 201 memorize | stores for every preference attribute shows that a user is large, and it shows that a user dislikes, so that it is small. However, the present invention is not limited to this, and it may indicate that the user is disliked as it is large, and that the user likes it as it is small.

  In the example illustrated in FIG. 2, the preference attribute table 201 stores hotness “6” sweetness “6” miso “2” soy sauce “4” for “user 1”. In other words, the preference attribute table 201 indicates that the user 1 likes “spicy” is “6”, the degree that likes sweetness is “6”, the degree that likes miso is “2”, and likes soy sauce. It memorizes that the degree is “4”. In addition, the preference attribute table 201 stores an attribute value for each item of the preference attribute in the same manner for other users.

  The word-of-mouth information table 202 stores the transmission information transmitted by the user in association with the user who is the transmission source. The transmission information stored in the word-of-mouth information table 202 is stored in the word-of-mouth information table 202 every time the user transmits information, for example. In this embodiment, for convenience of explanation, a case where the storage unit 200 includes the word-of-mouth information table 202 will be described as an example, but the present invention is not limited to this. For example, the storage unit 200 may not have the word-of-mouth information table 202, and a word-of-mouth information storage device corresponding to the word-of-mouth information table 202 may be provided outside the output device 100. In this case, for example, the output device 100 and the word-of-mouth information storage device may be connected via a network, and the output device 100 may acquire outgoing information from the word-of-mouth information storage device connected via the network.

  The control unit 300 is connected to the input / output unit 101 and the storage unit 200. The control unit 300 has an internal memory that stores a program that defines various processing procedures and the like, and controls various processes. The control unit 300 is an electronic circuit such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a central processing unit (CPU), or a micro processing unit (MPU). In the example illustrated in FIG. 1, the control unit 300 includes an attribute similarity calculation unit 301 and a word-of-mouth information output control unit 302.

  The attribute similarity calculation unit 301 receives identification information for identifying a user via the input / output unit 101. For example, the attribute similarity calculation unit 301 acquires identification information for identifying “user 4”. In this case, “user 4” is a user who wants to narrow down transmission information that suits his / her preference from a large amount of transmission information. Hereinafter, a case where the attribute similarity calculation unit 301 receives identification information for identifying “user 4” will be described as an example. However, the present invention is not limited to this, and the attribute similarity calculation unit 301 may accept arbitrary identification information. The attribute similarity calculation unit 301 is also referred to as a “similarity calculation unit”.

  The attribute similarity calculation unit 301 acquires the preference attribute of the user identified by the identification information from the preference attribute table 201, and classifies the similarity with the preference attribute stored in the preference attribute table 201 in association with another user. Calculate for each user.

  As shown in FIG. 2, description will be made using a case where the preference attribute table 201 stores preference attributes for “user 1”, “user 2”, “user 3”, and “user 4”. FIG. 3 is a diagram illustrating similarity calculation processing by the attribute similarity calculation unit according to the second embodiment. Reference numerals 401 to 404 in FIG. 3 indicate attributes of “user 1” to “user 4”, respectively. Upon receiving the identification information for identifying “user 4”, the attribute similarity calculation unit 301 acquires the preference attribute of “user 4” from the preference attribute table 201. Then, as indicated by 411 in FIG. 3, the attribute similarity calculation unit 301 calculates the similarity between the preference attribute of “user 4” and the preference attribute of “user 1”. Further, as indicated by 412 in FIG. 3, the attribute similarity calculation unit 301 calculates the similarity between the preference attribute of “user 4” and the preference attribute of “user 2”. Also, as indicated by reference numeral 413 in FIG. 3, the attribute similarity calculation unit 301 calculates the similarity between the preference attribute of “user 4” and the preference attribute of “user 3”.

  An example of a similarity calculation method by the attribute similarity calculation unit 301 will be described. For example, the attribute similarity calculation unit 301 calculates the similarity using the Euclidean distance. To explain with a more detailed example, the attribute similarity calculation unit 301 normalizes the Euclidean distance for each attribute value of the preference attribute to a range of “0” to “1”, and obtains a value obtained by normalization. The number obtained by subtracting “1” from “1” is the similarity. However, the present invention is not limited to the case where the similarity is calculated using the Euclidean distance, and the attribute similarity calculation unit 301 may calculate the similarity using any method.

  For example, a case where the similarity between “Mr. X” and “Mr. Y” is calculated will be described as an example. Here, the case where the attribute value of “Mr. X” is (Expression 1) and the attribute value of “Mr. Y” is (Expression 2) will be described.

  Of the attribute values shown in (Equation 1) and (Equation 2), “x1” to “xn” are assumed to be attribute values for the same preference attributes as “y1” to “yn”, respectively. . In this case, the similarity calculated by the attribute similarity calculation unit 301 is represented by (Equation 3).

  “S (X, Y)” in (Expression 3) indicates the degree of similarity between “Mr. X” and “Mr. Y”. “N” indicates a constant for normalization. As shown in (Expression 3), the similarity between “Mr. X” and “Mr. Y” is calculated by calculating the square value of the difference between attribute values for each preference attribute, and calculating the sum of the calculated square values. The value obtained by multiplying the square root by “N” and multiplying by “N” is a value obtained by subtracting from “1”.

  Here, by using (Equation 3) and calculating the similarity between “User 4” and “User 1” to “User 3”, (Equation 4) to (Equation 6) are obtained. In (Expression 4) to (Expression 6), the case where “1 / 10√4” is used as “N” is shown.

  In the example shown in (Expression 4) to (Expression 6), the attribute similarity calculation unit 301 calculates that the similarity between “User 4” and “User 1” is “67%”, The similarity between “4” and “User 2” is calculated as “48%”, and the similarity between “User 4” and “User 1” is calculated as “81%”.

  The word-of-mouth information output control unit 302 compares the transmission information transmitted by another user whose high similarity is calculated by the attribute similarity calculation unit 301 with the transmission information of another user whose low similarity is calculated. And output. In other words, the word-of-mouth information output control unit 302 sends the transmission information of “user 3” whose similarity is calculated as “81%” to “user 2” whose similarity is calculated as “48%”. Output in preference to outgoing information. The word-of-mouth information output control unit 302 is also referred to as an “output unit”.

  For example, the word-of-mouth information output control unit 302 compares the similarity calculated by the attribute similarity calculation unit 301 with a threshold, and selects a user with a similarity determined to be equal to or greater than the threshold. Then, the word-of-mouth information output control unit 302 acquires the transmission information associated with the selected user from the word-of-mouth information table 202, and outputs the acquired transmission information via the input / output unit 101.

  This will be further described with reference to FIG. 4 using a case where the threshold is “60%”. FIG. 4 is a diagram illustrating an example of output processing by the word-of-mouth information output control unit according to the first embodiment. In FIG. 4, reference numerals 421 to 423 denote “user 1” to “user 3”, respectively. Reference numeral 431 indicates transmission information transmitted by “user 1”, reference numeral 432 indicates transmission information transmitted by “user 2”, and reference numeral 433 indicates transmission information transmitted by “user 3”.

  As illustrated in (1) of FIG. 4, the word-of-mouth information output control unit 302 compares the similarity calculated by the attribute similarity calculation unit 301 with the threshold “60%”, and the similarity is equal to or greater than the threshold “60%”. The user whose degree is calculated is selected. In the example shown in (1) of FIG. 4, the word-of-mouth information output control unit 302 calculates “user 3” whose similarity is calculated as “81%” and “67%” as the similarity. “User 1” is selected. In other words, the word-of-mouth information output control unit 302 does not select “user 2” whose similarity is calculated to be “48%”. Then, as shown in (2) of FIG. 4, the word-of-mouth information output control unit 302 acquires the transmission information of the selected user from the word-of-mouth information table 202 and outputs it. In the example shown in (2) of FIG. 4, the word-of-mouth information output control unit 302 outputs the transmission information 431 and the transmission information 433 transmitted by “user 1” and “user 3”. On the other hand, as shown in (3) of FIG. 4, the word-of-mouth information output control unit 302 does not output the transmission information of the user who has not been selected. In the example shown in (3) of FIG. 4, the word-of-mouth information output control unit 302 does not output the transmission information 432 transmitted by “user 2”.

  The output device 100 may be realized by using an information processing device such as a known personal computer, server, mobile phone, PHS (Personal Handyphone System) terminal, mobile communication terminal, or PDA (Personal Digital Assistant). . For example, by installing the functions of the preference attribute table 201, the word-of-mouth information table 202, the attribute similarity calculation unit 301, and the word-of-mouth information output control unit 302 shown in FIG. It may be realized.

[Processing by Output Device According to Embodiment 1]
An example of the flow of processing by the output device 100 according to the second embodiment will be described with reference to FIG. FIG. 5 is a flowchart illustrating an example of a flow of processing performed by the output device according to the second embodiment.

  As illustrated in FIG. 5, when the attribute similarity calculation unit 301 receives the identification information (Yes in Step S101), the attribute similarity calculation unit 301 acquires the user preference attribute identified by the identification information from the preference attribute table 201 (Step S102). For example, when receiving the identification information for identifying “user 4”, the attribute similarity calculation unit 301 acquires the preference attribute of “user 4” from the preference attribute table 201.

  Then, the attribute similarity calculation unit 301 calculates the similarity with another user's preference attribute (step S103). For example, the attribute similarity calculation unit 301 calculates the similarity between the preference attribute of “user 4” and the preference attributes of “user 1” to “user 3”, respectively.

  Then, the similarity calculated by the attribute similarity calculation unit 301 is compared with a threshold (step S104), and a user having a similarity determined to be equal to or greater than the threshold is selected (step S105). For example, the word-of-mouth information output control unit 302 compares the similarity calculated by the attribute similarity calculation unit 301 with the threshold “60%”, and “user 1” for which the similarity equal to or higher than the threshold “60%” is calculated. Select “User 3”.

  Then, the word-of-mouth information output control unit 302 acquires transmission information associated with the selected user from the word-of-mouth information table 202 (step S106), and outputs the acquired transmission information via the input / output unit 101 (step S107). ). For example, the word-of-mouth information output control unit 302 acquires the transmission information transmitted by “user 1” or “user 3” from the word-of-mouth information table 202 and outputs it.

  In addition, said process procedure is not limited to said order, You may change suitably in the range which does not contradict a process content. For example, in the example illustrated in FIG. 5, the case where the output device 100 executes a series of processes when the identification information is received is illustrated as an example, but the present invention is not limited thereto. For example, the output device 100 may previously select another user with a similar preference attribute for each user.

[Effect of Example 1]
As described above, according to the first embodiment, the output device 100 stores the preference attribute for each user. Further, when receiving the identification information, the output device 100 reads the preference attribute of the user identified by the identification information from the preference attribute storage unit, and sets the similarity with the preference attribute of the user different from the user for each different user. calculate. Then, the output device 100 preferentially outputs the transmission information transmitted by another user whose high similarity is calculated with the transmission information of another user whose low similarity is calculated. As a result, the operation required for the user to obtain desired information can be simplified.

  For example, unlike the method in which the user selects any one of the categories every time, the output device 100 can output the transmission information without the user selecting a category, and the user's operation can be simplified. Further, for example, unlike a method in which a user inputs a keyword every time, the output device 100 can output outgoing information without the user inputting a keyword, and the user's operation can be simplified. Further, for example, according to the output device 100, as a result of outputting the transmission information of other users with similar preference attributes, the transmission information that is likely to match the user's preference is output without giving the user trouble. Is possible. In other words, for example, unlike the method of uniformly displaying regardless of whether or not the transmission information can be sympathized, it is possible to easily reach the desired transmission information by a filter of information of a person similar to the user. .

  In the second embodiment, an output device 500 that updates attribute values in the preference attribute table 201 will be described. That is, the output device 500 updates the preference attribute of the user, focusing on the fact that the transmission information that the user actually browses is likely to be the transmission information of another user similar to his / her preference. To do. Similarly, the output device 500 updates the user's preference attribute, focusing on the fact that another user who has selected the transmission information that he / she sent is likely to be similar to his / her preference. . Hereinafter, description of the same points as those of the output device 100 will be omitted, or description thereof will be omitted.

[Configuration of Output Device According to Second Embodiment]
10 shows an exemplary configuration of an output device 500 according to a second embodiment. FIG. 6 is a block diagram illustrating an example of the configuration of the output device according to the second embodiment. In FIG. 6, the same reference numerals as those in FIG.

  The storage unit 510 includes a preference attribute table 511 and a word-of-mouth information table 202. The storage unit 510 further includes a browsing log table 512 in addition to the table included in the storage unit 200 in the first embodiment. A preference attribute table 511 corresponds to the preference attribute table 201 in the first embodiment. In the preference attribute table 511, attribute values are updated by a preference attribute update unit 522 described later.

  The browsing log table 512 stores selected user information for identifying a user who has selected transmission information and transmission user information for identifying a user who has transmitted transmission information in association with each other. In other words, the browsing log table 512 stores transmission user information that identifies a user who has transmitted the transmission information selected by the user in association with the user. In addition, the browsing log table 512 stores selected user information that identifies a user who selects transmission information transmitted by the user in association with the user.

  Here, selecting the transmission information indicates, for example, that the user browses the transmission information or that the user selects arbitrary transmission information from the list of transmission information displayed on the screen. The browsing log table 512 is accumulated as a log each time transmission information is selected by the user, for example. The browsing log table 512 is also referred to as a “sending user storage unit” or a “selected user storage unit”.

  FIG. 7 is a diagram illustrating an example of information stored in the browsing log table according to the second embodiment. In the example illustrated in FIG. 7, the browsing log table 512 stores the calling user information “user 1” in association with the selected user information “user 4”. That is, the browsing log table 512 stores that “user 4” has selected transmission information transmitted by “user 1”. In other words, it stores that the transmission information transmitted by “user 1” is selected by “user 4”.

  The control unit 520 further includes a browsing log storage unit 521 and a preference attribute update unit 522 in addition to the processing unit included in the control unit 300 of the first embodiment. Each time the transmission information is selected by the user, the browsing log storage unit 521 stores the selected user information and the transmission user information in the browsing log storage unit 521 in association with each other.

  The preference attribute update unit 522 updates the information stored in the preference attribute table 511 based on the information stored in the browsing log storage unit 521. The preference attribute update unit 522 is also referred to as a “selected user update unit” or a “sending user update unit”. For example, the preference attribute update unit 522 updates the preference attribute table 511 at a predetermined update timing. The predetermined update timing indicates an interval set in advance by the designer of the output device 500, for example. A detailed example of the flow of processing by the preference attribute update unit 522 will be described later with reference to FIG.

  Specifically, the preference attribute update unit 522 associates the preference attribute stored for each user in the preference attribute table 511 with the user and is identified by the user information stored in the browsing log storage unit 521. Update based on preference attributes. That is, the preference attribute update unit 522 updates the preference attribute of the user to be updated based on the user preference attribute identified by the transmission user information associated with the user to be updated. In other words, the preference attribute update unit 522 updates the preference attribute of the user who has selected the transmission information based on the preference attribute of the user who is the transmission source of the transmission information selected by the user.

  For example, the information stored in the browsing log storage unit 521 illustrated in FIG. 7 will be described as an example. The preference attribute update unit 522 transmits the transmission information viewed by the “user 4” on the preference attribute of the “user 4”. It is updated based on a preference attribute such as “user 1” as a user. More specifically, the preference attribute update unit 522 acquires the user who has transmitted the transmission information viewed by the “user 4”, and calculates the average value of the acquired user attribute values for each preference attribute item. Then, the preference attribute update unit 522 compares the average value calculated for each preference attribute item with the attribute value of “user 4”. Then, when the average attribute value is larger than the attribute value of “user 1”, the preference attribute update unit 522 updates the attribute value of “user 1” to a value larger than the current value. In addition, when the calculated average value is smaller than the attribute value of “user 1”, the preference attribute update unit 522 updates the attribute value of “user 1” to a value smaller than the current value.

  In addition, for example, the preference attribute update unit 522 has a higher weighting as the number of times associated with “user 4” in the browsing log storage unit 521 is larger among the users who have transmitted the transmission information browsed by “user 4”. Then, the preference attribute of “user 4” is updated. To explain with a more detailed example, the average value is calculated using a value obtained by multiplying the attribute value of the user by the number of times of association. “User 4” is associated with “User 1” three times, “User 4” is associated with “User 2” once, and the attribute value of “User 1” is “3”. A case where the attribute value of “user 2” is “1” will be described. In this case, the preference attribute update unit 522 reads “((user 1 attribute value) × (number of times user 1 is associated) + (user 2 attribute value) × (number of times user 2 is associated))”. / (Number of times user 1 is associated + number of times user 2 is associated) ”=“ (3 × 3 + 1 × 1) /4=2.5 ”. However, the present invention is not limited to this, and the preference attribute update unit 522 may perform weighting using any method.

  Specifically, the preference attribute update unit 522 associates the preference attribute stored for each user in the preference attribute table 511 with the user to be updated and is selected user information stored in the browsing log storage unit 521. It updates based on the user preference attribute identified by. That is, the preference attribute update unit 522 updates the preference attribute of the user to be updated based on the user preference attribute identified by the selected user information associated with the user to be updated. In other words, the preference attribute updating unit 522 updates the preference attribute of the user who has transmitted the transmission information based on the preference attribute of the user who has selected the transmission information transmitted by the user.

  For example, the information stored in the browsing log storage unit 521 illustrated in FIG. 7 will be described as an example. The preference attribute update unit 522 browses the transmission information transmitted by “user 1” for the preference attribute of “user 1”. It is updated based on a preference attribute such as “user 4” who is a user. More detailed processing is the same as when updating based on the preference attribute of the user who is the transmission source of the transmission information selected by the user, and a description thereof will be omitted. A detailed example of the flow of processing by the preference attribute update unit 522 will be described later with reference to FIG.

[Processing by Preference Attribute Update Unit in Example 2]
An example of processing performed by the preference attribute update unit 522 according to the second embodiment will be described with reference to FIG. FIG. 8 is a flowchart illustrating an example of a processing flow by the preference attribute update unit according to the second embodiment. Below, the case where the preference attribute update part 522 updates based on the user's preference attribute used as the transmission origin of the transmission information which the user selected, and the user's preference attribute which selected the transmission information which the user transmitted is an example. explain. However, the present invention is not limited to this, and any one of the preference attribute of the user who is the transmission source of the transmission information selected by the user and the preference attribute of the user who selected the transmission information transmitted by the user One may be used.

  As shown in FIG. 8, the preference attribute update unit 522 selects one user to be updated at a predetermined update timing (Yes at Step S201) (Step S202). For example, “user 4” is selected. And the preference attribute update part 522 acquires the transmission user information matched with the user who becomes update object with reference to the browsing log table 512 (step S203). For example, the preference attribute update unit 522 acquires the transmission user information “user 1” associated with “user 4”.

  And the preference attribute update part 522 acquires the selection user information matched with the user used as update object with reference to the browsing log table 512 (step S204). For example, the preference attribute update unit 522 acquires the selected user information “user 2” associated with “user 4”.

  Then, the preference attribute update unit 522 acquires the acquired user preference attribute by referring to the preference attribute table 511 (step S205). For example, the preference attribute update unit 522 acquires the preference attribute of “user 2”, and acquires the preference attribute of “user 1”.

  Then, the preference attribute update unit 522 updates the preference attribute of the user to be updated based on the acquired preference attribute (step S206). For example, the preference attribute update unit 522 calculates the average value of the acquired attribute values of the user 1 and the user 2 for each preference attribute item, the average value calculated for each preference attribute item, and the attribute value of “user 4” And compare. When the average attribute value is larger than the attribute value of “user 4”, the preference attribute update unit 522 updates the attribute value of “user 4” to a value larger than the current value. In addition, when the calculated average value is smaller than the attribute value of “user 4”, the preference attribute update unit 522 updates the attribute value of “user 4” to a value smaller than the current value.

  In addition, said process procedure is not limited to said order, You may change suitably in the range which does not contradict a process content. For example, the order of steps S203 and S204 described above may be switched, and either one of steps S203 and S204 may not be executed.

[Effect of Example 2]
As described above, according to the second embodiment, the output device 500 includes the browsing log table 512. Further, the output device 500 updates the preference attribute stored for each user based on the user preference attribute identified by the calling user information stored in the browsing log table 512 in association with the user. As a result, the preference attribute can be appropriately updated based on the log of the transmission information actually selected by the user, and the transmission information that matches the user's preference attribute at the time of outputting the transmission information can be output.

  Further, according to the second embodiment, the output device 500 associates the preference attribute stored for each user with the user preference attribute identified by the selected user information stored in the browsing log table 512 in association with the user. Update. As a result, the preference attribute can be appropriately updated based on the log of the user who selected the transmission information transmitted by the user, and the transmission information that matches the user's preference attribute at the time when the transmission information is output can be output.

  For example, the output device 500 updates the preference attribute using the browsing log table 512 and uses it. As a result, it is possible to output the transmission information according to the user's preference even if the user's preference changes, unlike the method of preliminarily registering the filtering conditions and narrowing the transmission information using a fixed condition. is there.

  Although the embodiments of the present invention have been described so far, the present invention may be implemented in other embodiments besides the above-described embodiments. Therefore, other embodiments will be described below.

[Similarity calculation processing]
For example, in the above-described embodiment, the case where the output device calculates the similarity for all the users whose preference attributes are stored in the preference attribute table 201 has been described, but the present invention is not limited to this. For example, the output device may calculate the similarity only for a part of users whose preference attributes are stored in the preference attribute table 201.

[Output processing]
Further, for example, in the above-described embodiment, the case where the transmission information of the user whose similarity equal to or higher than the threshold is calculated has been described, but the present invention is not limited to this. For example, the word-of-mouth information output control unit 302 outputs transmission information in descending order of similarity without using a threshold value. That is, for example, the word-of-mouth information output control unit 302 outputs the transmission information of “user 3” whose similarity is calculated as “81%”, and thereafter, the similarity is calculated as “67%”. Alternatively, the transmission information of “user 1” may be output, and subsequently, the transmission information of “user 2” calculated to have a similarity of “48%” may be output. Further, for example, the word-of-mouth information output control unit 302 may output the transmission information as a list in which the transmission information and the similarity are associated with each other.

[System configuration]
Also, among the processes described in this embodiment, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed. All or a part can be automatically performed by a known method. In addition, the processing procedures, control procedures, specific names, and information including various data and parameters shown in the above-mentioned documents and drawings (FIGS. 1 to 8 etc.) are arbitrarily changed unless otherwise specified. can do.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or a part of the distribution / integration is functionally or physically distributed in arbitrary units according to various loads and usage conditions. Can be integrated and configured. For example, in the example illustrated in FIG. 1, the output device 100 has the word-of-mouth information table 202 and the transmission information is acquired from the word-of-mouth information table 202. However, the present invention is not limited to this. . For example, the word-of-mouth information table 202 may be an external device of the output device 100. In this case, the output device 100 may be connected to the word-of-mouth information table 202 via a network.

[Others]
Each processing function performed by the output device 100 is realized by a CPU and a program that is analyzed and executed by the CPU. Alternatively, it can be realized as hardware by wired logic. In other words, each processing function performed in the output device 100 may be realized by executing a prepared program on a computer such as a personal computer or a workstation.

  In addition, the output method described in the above-described embodiments may be executed by specifically realizing information processing by the output program using a computer. The computer has, for example, a CPU, a system memory, a disk drive interface, a serial port interface, a video adapter, and a network interface. Each part of the computer is connected by a system bus. The system memory has a ROM and a RAM. The ROM stores a boot program such as BIOS (Basic Input Output System). The hard disk interface is connected to the HDD. The disk drive interface is connected to the disk drive. For example, a removable storage medium such as a magnetic disk or an optical disk is inserted into the disk drive. The serial port interface is connected to, for example, a mouse or a keyboard. The video adapter is connected to a display, for example.

  The HDD stores, for example, an OS (Operating System), application programs, program modules, program data, and the like. That is, the output program according to the disclosed technology is stored in, for example, the HDD as a program module in which a command to be executed by a computer is described. Referring to FIG. 1 as an example, a procedure for executing processing similar to that of the attribute similarity calculation unit 301 and a procedure for executing processing similar to that of the word-of-mouth information output control unit 302 are stored in the HDD.

  In addition, data used for processing by the output program, such as data stored in the preference attribute table 201 and data stored in the word-of-mouth information table 202 described in the above-described embodiment, may be, for example, HDD as program data. Is remembered. Then, the CPU appropriately reads the program module and program data stored in the HDD into the RAM and executes the above-described procedure.

  The program module and program data related to the output program are not limited to being stored in the HDD. For example, the program module and program data may be stored in a removable storage medium and read by the CPU via a disk drive or the like. Further, for example, the program module and the program data are stored in another computer connected via a network (such as a LAN (Local Area Network) or a WAN (Wide Area Network)) and read by the CPU via the network interface. May be.

100 output device 101 input / output unit 200 storage unit 201 preference attribute table 202 review information table 300 control unit 301 attribute similarity calculation unit 302 review information output control unit 500 output device 510 storage unit 511 preference attribute table 512 browsing log table 520 control unit 521 Browsing log storage unit 522 Preference attribute update unit

Claims (9)

A preference attribute storage unit that stores a preference attribute that is a user preference attribute for each user;
When the identification information for identifying the user is received, the preference attribute of the user identified by the identification information is read from the preference attribute storage unit and stored in the preference attribute storage unit in association with a user different from the user. A similarity calculation unit for calculating the similarity with the preference attribute for each different user;
An output unit that preferentially outputs transmission information transmitted by another user whose high similarity is calculated by the similarity calculation unit compared with transmission information of another user whose low similarity is calculated An output device characterized by that. An outgoing user storage unit that stores outgoing user information that identifies the user who sent the outgoing information selected by the user in association with the user;
Selection to update the preference attribute stored for each user in the preference attribute storage unit based on the user preference attribute identified by the outgoing user information stored in the outgoing user storage unit in association with the user The output device according to claim 1, further comprising: a user update unit. A selected user storage unit that stores selected user information that identifies the user who selected the transmission information transmitted by the user in association with the user;
The transmission which updates the preference attribute memorize | stored for every said user in the said preference attribute memory | storage part based on the user's preference attribute identified by the said selected user information memorize | stored in the said selected user memory | storage part in association with the said user The output device according to claim 1, further comprising: a user update unit. Computer
When the identification information for identifying the user is received, the preference attribute of the user identified by the identification information is read by referring to the preference attribute storage unit that stores the preference attribute that is the preference attribute of the user for each user. A similarity calculation step for calculating, for each different user, the similarity with the preference attribute stored in the preference attribute storage unit in association with a user different from the user;
An output step of preferentially outputting the transmission information transmitted by another user whose high similarity is calculated in the similarity calculation step compared with the transmission information of another user whose low similarity is calculated An output method characterized by: The computer functions as an outgoing user storage unit that stores outgoing user information that identifies a user who has sent the outgoing information selected by the user in association with the user,
Selection to update the preference attribute stored for each user in the preference attribute storage unit based on the user preference attribute identified by the outgoing user information stored in the outgoing user storage unit in association with the user The output method according to claim 4, further comprising executing a user update step. The computer functions as a selected user storage unit that stores selected user information for identifying a user who selects the transmission information transmitted by the user in association with the user,
The transmission which updates the preference attribute memorize | stored for every said user in the said preference attribute memory | storage part based on the user's preference attribute identified by the said selected user information memorize | stored in the said selected user memory | storage part in association with the said user 6. The output method according to claim 4, further comprising a user update step. On the computer,
When the identification information for identifying the user is received, the preference attribute of the user identified by the identification information is read by referring to a preference attribute storage unit that stores a preference attribute that is a preference attribute of the user for each user. A similarity calculation procedure for calculating the similarity with the preference attribute stored in the preference attribute storage unit in association with a user different from the user, for each different user;
An output procedure for preferentially outputting the transmission information transmitted by another user whose high similarity is calculated by the similarity calculation procedure compared with the transmission information of another user whose low similarity is calculated An output program characterized by causing The computer is associated with the user and functions as a transmission user storage unit that stores transmission user information for identifying a user who has transmitted the transmission information selected by the user,
Selection to update the preference attribute stored for each user in the preference attribute storage unit based on the user preference attribute identified by the outgoing user information stored in the outgoing user storage unit in association with the user 8. The output program according to claim 7, further comprising executing a user update procedure. The computer is associated with the user and functions as a selected user storage unit that stores selected user information for identifying a user who has selected the transmission information transmitted by the user,
The transmission which updates the preference attribute memorize | stored for every said user in the said preference attribute memory | storage part based on the user's preference attribute identified by the said selected user information memorize | stored in the said selected user memory | storage part in association with the said user 9. The output program according to claim 7, further comprising executing a user update procedure.

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