WO2013088682A1 - Dispositif, procédé et programme de correction de conditions de recommandation - Google Patents

Dispositif, procédé et programme de correction de conditions de recommandation Download PDF

Info

Publication number
WO2013088682A1
WO2013088682A1 PCT/JP2012/007828 JP2012007828W WO2013088682A1 WO 2013088682 A1 WO2013088682 A1 WO 2013088682A1 JP 2012007828 W JP2012007828 W JP 2012007828W WO 2013088682 A1 WO2013088682 A1 WO 2013088682A1
Authority
WO
WIPO (PCT)
Prior art keywords
recommendation
condition
history
success
user
Prior art date
Application number
PCT/JP2012/007828
Other languages
English (en)
Japanese (ja)
Inventor
健太郎 山崎
敏功 落合
佑嗣 小林
Original Assignee
日本電気株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 日本電気株式会社 filed Critical 日本電気株式会社
Publication of WO2013088682A1 publication Critical patent/WO2013088682A1/fr

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G06Q10/105—Human resources
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06398—Performance of employee with respect to a job function

Definitions

  • Patent Document 1 discloses an apparatus for optimizing an advertisement according to an advertisement result while performing an advertisement. When the sales amount has not reached the target, this device expands the target audience of the advertisement.
  • Patent Document 2 discloses a business analysis table creation system for recognizing the effect of advertising media. This business analysis table displays questionnaire survey responses in a matrix table. This business analysis table includes the number of people who answered that the target product was advertised with a flyer but wanted to purchase the product. Patent Literature 3 discloses a recommendation effect measuring device for an online shopping server.
  • An object of the present invention is to provide a recommended condition correcting device, a recommended condition correcting method, and a recommended condition correcting program that solve the above-mentioned problems.
  • the recommendation condition correction device includes a condition storage unit that stores a recommendation condition that specifies a range of one or more values of the attribute that is user information including a plurality of attributes, When the context satisfies the recommendation condition, each attribute value of the target user and the target user correspond to each target user who is a user who has output recommendation information for encouraging a predetermined action.
  • a recommendation history storage means for storing a recommendation history including success / failure information indicating whether or not a predetermined action has been taken;
  • a success history storage means for storing the value of each attribute of the context of the successful user and a recommendation history storage means for each successful user who is a user who has taken the predetermined action other than the target user.
  • the value indicating that the attribute of the context is the value corresponding to each value of the attribute included in the context of all of the recommendation histories being performed indicates that the predetermined action has been taken in the recommendation history
  • a first contribution ratio indicating a ratio of recommendation history is calculated, and a ratio of the success history in which the value of the attribute in the context matches the recommendation condition in the success history for each attribute in the recommendation condition
  • a recommendation condition correction means for correcting the recommendation condition based on the first contribution ratio and the second contribution ratio.
  • a recommendation history including success / failure information indicating whether or not a predetermined action has been taken in the recommendation history storage means;
  • the value of each attribute of the context of the successful user is stored in a success history storage unit, and stored in the recommendation history storage unit.
  • the value indicating that the attribute of the context is the value corresponding to each value of the attribute included in the context of all of the recommendation histories being performed indicates that the predetermined action has been taken in the recommendation history
  • a first contribution ratio indicating a ratio of recommendation history is calculated, and a ratio of the success history in which the value of the attribute in the context matches the recommendation condition in the success history for each attribute in the recommendation condition
  • a second contribution ratio indicating the second contribution ratio is calculated, and the recommendation condition is corrected based on the first contribution ratio and the second contribution ratio.
  • a recommendation condition correction program includes a condition storage process for storing a recommendation condition that specifies a range of one or more values of a context that is user information, including a plurality of attributes, as condition storage means. , When the context satisfies the recommendation condition, each attribute value of the target user and the target user correspond to each target user who is a user who has output recommendation information for encouraging a predetermined action.
  • the device can improve the “number of successful recommendations” while suppressing a decrease in the “recommendation success rate”.
  • the recommended condition correction device 10 of the present embodiment includes a registration unit 60, a condition storage unit 40, a recommended condition correction unit 20, a recommendation history storage unit 50, and a success history, each including a logic circuit, a storage device, and the like.
  • a storage unit 30 is included.
  • the recommended condition correction apparatus 10 may be a computer that operates under program control.
  • the registration unit 60, the condition storage unit 40, the recommended condition correction unit 20, the recommendation history storage unit 50, and the success history storage unit 30 are programs stored in the storage device by the processing device included in the computer. It may be realized by reading and executing.
  • the recommendation history storage unit 50, the condition storage unit 40, and the success history storage unit 30 may include a disk device included in the computer.
  • the registration unit 60 receives the scenario 12 from the administrator terminal 11 and registers the condition information 41 in the condition storage unit 40.
  • FIG. 2 shows an example of the scenario 12.
  • the scenario 12 includes a scenario ID, recommendation conditions, and recommendation information.
  • the scenario ID is information for distinguishing the scenario 12.
  • the recommendation condition is information including a recommendation condition ID and a conditional expression.
  • the recommendation condition ID is information for distinguishing the recommendation condition.
  • the conditional expression expresses a condition for selecting a user to be recommended using part or all of the user context 13.
  • the context 13 is information indicating the state of the user, and includes a plurality of attribute information.
  • the attribute information includes a pair of attribute name and attribute value.
  • the attribute name indicates the property of the attribute, and is, for example, a user ID, a position, and an age.
  • the attribute value indicates the value of the attribute, for example, Ichiro Tanaka, XX station, 30 years old.
  • FIG. 3 shows an example of the context 13.
  • This is a context 13 including the attribute information.
  • This context 13 indicates that “User 1 who is a man in his fifties is currently at the station, has 1000 steps, and is in good health”.
  • the conditional expression represents the condition of the context 13 to be satisfied by the user to be recommended by one or more attribute information, that is, one or more attribute name and attribute value pairs.
  • the attribute value may be a range of values.
  • Recommendation information is information related to recommendation.
  • the recommendation information may be a recommendation information ID indicating recommendation content, an address of the recommendation execution device 17 that performs the recommendation, an advertisement that is presented to a user that matches the conditional expression of the recommendation condition, and a program that is executed.
  • FIG. 2 shows a scenario 12 when the recommendation information is a recommendation information ID.
  • the condition information 41 is information including a condition ID, a scenario ID, a conditional expression, and association information.
  • FIG. 4 shows an example of the condition information 41.
  • the registration unit 60 creates the condition information 41 from the scenario 12.
  • the registration unit 60 acquires a recommendation condition ID, a scenario ID, a conditional expression, and recommendation information from the scenario 12, and sets the information as the condition ID, the scenario ID, the conditional expression, and the association information of the condition information 41.
  • the condition storage unit 40 stores one or more condition information 41.
  • FIG. 5 shows an example of a plurality of condition information 41 stored in the condition storage unit 40.
  • FIG. 5 shows an example in which the condition storage unit 40 stores two condition information 41 having a condition ID of recommendation condition 1 and recommendation condition 2.
  • the recommendation history storage unit 50 includes the context 13 at the time of recommendation of the user recommended by the recommendation execution device 17 and whether the user has taken the expected behavior described later (success) or not yet (unsuccessful).
  • One or more recommendation histories 51 including recommendation success / failure information indicating “” are stored.
  • FIG. 6 shows an example of a plurality of recommendation histories 51 stored in the recommendation history storage unit 50.
  • FIG. 6 shows a recommendation history 51 for the recommendation condition 1.
  • the example of FIG. 6 shows that the recommendation execution device 17 made the recommendation four times, and the effect expected only once was obtained.
  • the recommendation execution device 17 receives the user context 13 from the user terminal 15, refers to the condition storage unit 40 included in the recommendation condition correction device 10, transmits recommendation information to the user terminal 15, and recommends The history 51 is written into the recommendation history storage unit 50.
  • the recommendation condition correction apparatus 10 may acquire the recommendation history 51 collectively from the recommendation execution apparatus 17 or the like by other means, for example, a data migration tool or the like.
  • the expected behavior is an effect or reaction expected from the user when the system operator who registered the scenario 12 in the recommendation condition correction system 90 receives a recommendation from the scenario 12. For example, when an advertisement is sent to a user of a specific age group and gender and a purchase of a product is recommended, the expected behavior is that the user purchases the product or the user stops at a store that sells the product. is there.
  • the recommendation execution device 17 may have sent an advertisement for recommending a product to a woman in her 20s, but a woman in her 30s who did not send an advertisement bought the product.
  • the success history 31 is transmitted from the sales terminal of the store to the recommended condition correction device 10, for example.
  • the success history 31 may be collectively transferred from the sales log of the sales terminal of the store by other means such as a data migration tool.
  • the recommendation condition correction apparatus 10 can also acquire the recommendation success / failure information of the recommendation history 51 in the same manner.
  • the recommendation condition correction unit 20 When the recommendation condition correction unit 20 receives the recommendation condition correction request 14 from the administrator terminal 11, the recommendation condition correction unit 20 corrects the conditional expression of the recommendation condition of the recommendation condition ID specified in the recommendation condition correction request 14.
  • the recommendation condition correction unit 20 acquires the success history 31 and the recommendation history 51 from the success history storage unit 30 and the recommendation history storage unit 50, acquires the conditional expression from the condition storage unit 40, and corrects it.
  • the recommendation condition modification request 14 includes a recommendation condition ID, an attribute information deletion threshold value, and an attribute information addition threshold value.
  • FIG. 8 shows an example of the recommended condition correction request 14.
  • the attribute information addition threshold is a lower limit value for adding attribute information when the first success contribution rate of each attribute information calculated from the recommendation history 51 is calculated.
  • the recommendation condition correction unit 20 adds attribute information whose first success contribution rate is above the attribute information addition threshold.
  • the attribute information deletion threshold is a lower limit value that does not delete the attribute information when the second success contribution rate of each attribute information calculated from the success history 31 is calculated.
  • the recommendation condition correction unit 20 deletes attribute information whose second success contribution rate is equal to or less than the attribute information deletion threshold.
  • the recommendation condition modification unit 20 When receiving the recommendation condition modification request 14, the recommendation condition modification unit 20 creates an acquisition request for the condition information 41, an acquisition request for the success history 31, and an acquisition request for the recommendation history 51.
  • the acquisition request for the condition information 41, the acquisition request for the success history 31, and the acquisition request for the recommendation history 51 include a condition ID.
  • the recommended condition correction unit 20 transmits an acquisition request for the condition information 41 to the condition storage unit 40, and acquires the condition information 41 as a response. Also, the recommendation condition correction unit 20 transmits an acquisition request for the success history 31 and an acquisition request for the recommendation history 51 to the success history storage unit 30 and the recommendation history storage unit 50, and the success history 31 and the recommendation history 51 that are responses thereto. Receive.
  • the first success contribution rate is used for adding attribute information.
  • the recommendation condition correction unit 20 extracts all different attribute information, that is, attribute name / attribute value pairs as a list from all the recommendation histories 51 stored in the recommendation history storage unit 50. For each piece of attribute information in the list, the recommendation condition correcting unit 20 out of the recommendation history 51 including the attribute information in the context 13, the number of recommended histories 51 (success number) with the success / failure recommendation is “success”. Is obtained (the number of unsuccessful attempts). Then, the recommendation condition correction unit 20 calculates the number of successes / (number of successes + number of unsuccessful) for each attribute information in the list and sets it as the first success contribution rate.
  • FIG. 9 shows the first success contribution rate calculated from the four recommendation histories 51 shown in FIG.
  • the second success contribution rate is used for deleting attribute information.
  • the recommendation condition correction unit 20 acquires a conditional expression corresponding to the recommendation condition ID included in the recommendation condition correction request 14 from the condition storage unit 40, and includes the attribute information in the context 13 for each attribute information included in the conditional expression.
  • the number of success histories 31 (number of matches) is obtained.
  • the recommendation condition correction unit 20 calculates the number of matches / total number of success histories 31 for each attribute information, and sets it as the second success contribution rate.
  • FIG. 10 shows the second success contribution rate calculated from the ten success histories 31 shown in FIG.
  • the administrator terminal 11 is an information processing apparatus including an input device such as a keyboard and a mouse, an output device such as a liquid crystal display, a processing device that operates under program control, and a storage device including a memory.
  • the administrator terminal 11 creates a scenario 12 and transmits it to the recommended condition correction device 10. Further, the administrator terminal 11 creates a recommended condition correction request 14 and transmits it to the recommended condition correction apparatus 10.
  • the recommendation execution device 17 is an information processing device including an input device such as a keyboard and a mouse, an output device such as a liquid crystal display, a processing device operated by program control, and a storage device including a memory.
  • the recommendation execution device 17 receives the information including the recommendation condition and the recommendation content, and transmits the recommendation information to the user.
  • the operation of the system according to the present embodiment can be divided into a scenario registration flow for registering the scenario 12 and a recommendation condition correction flow for correcting the recommendation conditions.
  • FIG. 11 is a scenario registration flowchart showing the operation of the system according to the first embodiment.
  • the registration unit 60 receives the scenario 12 and proceeds to S-102S.
  • the registration unit 60 acquires a scenario ID, a recommendation condition ID, a conditional expression, and recommendation information from the scenario 12, and sets the condition information 41 using the respective information as a scenario ID, a condition ID, a conditional expression, and association information. Create and go to S-103S.
  • the registration unit 60 transmits the condition information 41 to the condition storage unit 40, and the condition storage unit 40 stores the condition information 41 and ends the scenario registration flow.
  • the linking information is stored in the linking information storage unit.
  • 12A and 12B are recommended condition correction flowcharts showing the operation of the system according to the first embodiment.
  • the recommended condition correction unit 20 receives the recommended condition correction request 14 from the administrator terminal 11, and proceeds to S-1020.
  • the recommendation condition correction request 14 includes a recommendation condition ID, an attribute information deletion threshold value, and an attribute information addition threshold value.
  • the recommended condition modification unit 20 creates a condition acquisition request and proceeds to S-1030.
  • the condition acquisition request includes a recommended condition ID.
  • the recommended condition correction unit 20 transmits a condition acquisition request to the condition storage unit 40.
  • the condition storage unit 40 receives the condition acquisition request, the condition storage unit 40 returns condition information 41 having a condition ID that matches the recommended condition ID included in the condition acquisition request to the recommended condition correction unit 20. If there is no condition information 41 having a matching condition ID, the condition storage unit 40 returns “no match”.
  • the recommended condition correction unit 20 receives the condition information 41 or “no match” from the condition storage unit 40, and proceeds to S-1040.
  • the recommended condition correction unit 20 proceeds to S-1050 if the condition information 41 is received from the condition storage unit 40 in S-1030, and ends the process if “no match” is received.
  • the recommendation condition correction unit 20 creates an acquisition request for the success history 31, and proceeds to S-1060.
  • the acquisition request for the success history 31 includes a recommendation condition ID.
  • the recommendation condition correction unit 20 transmits a success history 31 acquisition request to the success history storage unit 30.
  • the success history storage unit 30 receives the acquisition request for the success history 31, the success history storage unit 30 returns a success history 31 having a condition ID that matches the recommendation condition ID included in the acquisition request for the success history 31 to the recommendation condition correction unit 20. If there is no success history 31 having a matching condition ID, the success history storage unit 30 returns “no match”.
  • the recommendation condition correction unit 20 receives the success history 31 or “no match” from the success history storage unit 30, and proceeds to S-1070.
  • the recommendation condition correction unit 20 creates an acquisition request for the recommendation history 51, and proceeds to S-1080.
  • the acquisition request for the recommendation history 51 includes a recommendation condition ID.
  • the recommendation condition correction unit 20 transmits an acquisition request for the recommendation history 51 to the recommendation history storage unit 50.
  • the recommendation history storage unit 50 Upon receiving the recommendation history 51 acquisition request, the recommendation history storage unit 50 returns a recommendation history 51 having a condition ID that matches the recommendation condition ID included in the recommendation history 51 acquisition request to the recommendation condition correction unit 20. If there is no recommendation history 51 having a matching condition ID, the recommendation history storage unit 50 returns “no match”.
  • the recommendation condition correction unit 20 receives the recommendation history 51 or “no match” from the recommendation history storage unit 50, and proceeds to S-1090.
  • the recommendation condition correction unit 20 proceeds to S-1100 if the success history 31 is received from the success history storage unit 30 in S-1060, and proceeds to S-1110 if “no match” is received.
  • the recommendation condition correction unit 20 performs deletion attribute information determination, and proceeds to S-1110. Detailed operation of attribute information deletion will be described later with reference to FIG.
  • the recommendation condition correction unit 20 proceeds to S-1120 if the recommendation history 51 is received from the recommendation history storage unit 50 in S-1080, and proceeds to S-1130 if “no match” is received.
  • the recommendation condition correction unit 20 performs additional attribute information determination, and proceeds to S-1130.
  • the detailed operation for adding attribute information will be described later with reference to FIG.
  • the recommended condition correction unit 20 deletes the attribute information determined as the deletion attribute information, adds the attribute information determined as the additional attribute information, and ends the process.
  • FIG. 13 is a flowchart of the process for determining the deletion attribute information of the recommendation condition.
  • the recommended condition correction unit 20 extracts a conditional expression from the condition information 41, and proceeds to S-102D.
  • the recommendation condition correction unit 20 sets 0 to the counter i, and proceeds to S-103D.
  • the recommended condition correction unit 20 calculates the second success contribution rate of the i-th attribute information of the conditional expression from the success history 31, and proceeds to S104.
  • the recommendation condition correction unit 20 counts the number of success histories 31 including the i-th attribute information in the context 13 in the success history 31 for all the success histories 31 stored in the success history storage unit 30.
  • the second success contribution rate is obtained by calculating the number of counts / success history 31.
  • the recommended condition modification unit 20 proceeds to S-106D if the calculation of the second success contribution rate has been completed for the attribute information of all the conditional expressions, and proceeds to S-105D if it has not been completed.
  • the recommended condition correction unit 20 adds 1 to the counter i and proceeds to S-103D.
  • the recommendation condition correction unit 20 determines that the attribute information that is below the attribute information deletion threshold among the second success contribution ratio calculated in S-103D is the deletion attribute information, and ends the process.
  • FIG. 14 is a processing flowchart for determining additional attribute information of recommendation conditions.
  • the recommended condition correction unit 20 sets 0 to the counter i, and proceeds to S-102A.
  • the recommendation condition correction unit 20 acquires the i-th recommendation history 51 from the recommendation history 51 acquired from the recommendation history storage unit 50, and proceeds to S-103A.
  • the recommended condition correction unit 20 sets 0 to the counter j, and proceeds to S-104A.
  • the recommendation condition correction unit 20 proceeds to S-105A if the success / failure information of the i-th recommendation history 51 acquired in S-102A is “success”, and proceeds to S-108A if “unsuccessful”. .
  • the recommendation condition correction unit 20 acquires the j-th attribute information of the i-th recommendation history 51, adds 1 to the success number of the attribute information, and proceeds to S-106A.
  • the recommendation condition correcting unit 20 proceeds to S-111A if the processing of S-105A is completed for all the attribute information of the i-th recommendation history 51, and proceeds to S-107A if not completed.
  • the recommended condition correcting unit 20 adds 1 to the counter j and proceeds to S-105A.
  • the recommendation condition correction unit 20 acquires the j-th attribute information of the i-th recommendation history 51, adds 1 to the unsuccessful number of attribute information, and proceeds to S-109A.
  • the recommendation condition correcting unit 20 proceeds to S-111A if the processing of S-108A is completed for all the attribute information of the i-th recommendation history 51, and proceeds to S-110A if not completed.
  • the recommended condition correction unit 20 adds 1 to the counter j and proceeds to S-108A.
  • the recommendation condition correction unit 20 proceeds to A-113A if the processing has been completed for all the recommendation histories 51, and proceeds to S-112A if it has not been completed.
  • the recommended condition correction unit 20 adds 1 to the counter i and proceeds to S-102A.
  • the recommendation condition correction unit 20 calculates the first success contribution rate for each attribute information, and proceeds to S114A.
  • the recommendation condition correcting unit 20 calculates the first success contribution rate by calculating the number of successes / (the number of successes + the number of unsuccessful) for each attribute.
  • the recommendation condition correcting unit 20 determines that the attribute information having the first success contribution rate exceeding the attribute information addition threshold among the attribute information is the additional attribute information, and ends the process.
  • the recommendation condition correction apparatus 10 can perform deletion attribute information determination without using the recommendation history 51 while assuming feedback correction of the recommendation condition based on the recommendation history 51.
  • the recommendation condition correction system 90 increases the number of recommendations to improve the “number of successful recommendations”, while reducing the “recommendation success rate” until the recommendation history 51 is accumulated and fed back. Can be suppressed.
  • the reason is that the recommendation condition correction apparatus 10 performs the deletion attribute information determination using the success history 31 accumulated in the success history storage unit 30.
  • the recommended condition correcting apparatus 10 is based on the assumption that there can be a plurality of recommended conditions.
  • the recommended condition correction apparatus 10 may be implemented on the assumption that there is one recommended condition. In this case, for example, the recommendation history 51 and the success history 31 do not need to include the condition ID, and the recommendation condition correction unit 20 or the like does not need to perform processing for checking the condition ID.
  • the recommendation condition correction apparatus 10 may perform deletion attribute information determination in consideration of the recommendation success rate calculated from the recommendation history 51.
  • the recommendation success rate is a ratio of the number of recommendation histories 51 whose recommendation success / failure information indicates “success” in the recommendation histories 51 stored in the recommendation history storage unit 50.
  • the recommendation condition correction unit 20 may calculate a recommendation success rate, and may perform deletion attribute information determination similar to that of the first embodiment only when this value is equal to or less than a predetermined threshold.
  • This mechanism allows the recommendation condition correcting device 10 to avoid the risk of correcting the recommendation condition and lowering the recommendation success rate when the recommendation success rate is sufficiently high.
  • the recommendation condition correction apparatus 10 may add that the second contribution ratio of the attribute information to be added is a predetermined value or more to the attribute addition condition in the additional attribute information determination. With this mechanism, the recommendation condition correction apparatus 10 can carefully add attribute information.
  • FIG. 15 is a block diagram of the recommended condition correction system 90 according to the second embodiment of this invention.
  • a recommendation condition correction system 90 illustrated in FIG. 15 includes a recommendation condition correction device 10, an administrator terminal 11, a user terminal 15, a recommendation execution device 17, and a success history input terminal 16.
  • the recommended condition correction apparatus 10 of the present embodiment includes a registration unit 60, a condition storage unit 40, a search unit 70, a recommendation history storage unit 50, and a success history registration unit, which are configured with logic circuits, storage devices, and the like. 80, a success history storage unit 30, and a recommendation condition correction unit 20.
  • the recommended condition correction apparatus 10 may be a computer that operates under program control.
  • the registration unit 60, the condition storage unit 40, the search unit 70, the recommendation history storage unit 50, the success history registration unit 80, the success history storage unit 30, and the recommendation condition correction unit 20 are provided in the computer.
  • the central processing unit may be realized by reading and executing a program stored in the storage device.
  • the recommendation history storage unit 50, the condition storage unit 40, and the success history storage unit 30 may include a disk device included in the computer.
  • the registration unit 60, condition storage unit 40, recommendation history storage unit 50, success history storage unit 30, and recommendation condition correction unit 20 in the second embodiment of the present invention are the same as those in the first embodiment.
  • the search unit 70 and the success history registration unit 80 which are differences from the first embodiment, will be described.
  • the search unit 70 receives the user context 13 from the user terminal 15, acquires the condition information 41 that matches the context 13 from the condition storage unit 40, creates a recommendation history 51, and uses the condition information 41 as a recommendation execution device. 17 to send.
  • the search unit 70 creates a recommendation history 51 from the context 13 and the condition information 41 and stores it in the recommendation history storage unit 50.
  • the search unit 70 sets the condition ID obtained from the condition information 41 and the context 13 received from the user terminal 15 to the condition ID and context 13 of the recommendation history 51 to be created.
  • the search unit 70 sets “unsuccessful” information in the recommendation success / failure information of the recommendation history 51. For example, when the context 13 shown in FIG. 3 and the condition information 41 shown in FIG. 4 are obtained, the search unit 70 generates the recommendation history 51 shown in FIG.
  • the search unit 70 transmits the condition information 41 to the recommendation execution device 17.
  • the recommendation execution device 17 executes recommendation for the user terminal 15.
  • the success history registration unit 80 receives the success history 31 from the success history input terminal 16 and determines whether the recommendation history 51 corresponding to the success history 31 exists in the recommendation history storage unit 50.
  • the success history 31 includes a recommendation condition ID and an expected action context 13 and is received when the user takes an action expected by the system operator.
  • FIG. 17 shows an example of the success history 31.
  • the success history 31 shown in FIG. 17 is the success history 31 of the user 1 for the scenario 12 having the recommendation condition indicated by the condition ID of the recommendation condition 1.
  • the success history registration unit 80 When the recommendation history storage unit 50 stores the recommendation history 51 shown in FIG. 6 and the success history registration unit 80 receives the success history 31 shown in FIG. 17, the recommendation history 51 that matches the condition ID and the user ID. Is found. When the recommendation history 51 corresponding to the success history 31 is found, the success history registration unit 80 updates the recommendation success / failure information of the recommendation history 51 of the recommendation history storage unit 50 corresponding to the success history 31 to “success”.
  • the success history registration unit 80 includes the success history 31.
  • the success history registration unit 80 stores the success history 31 in the success history storage unit 30.
  • the user terminal 15 is an information processing apparatus including an input device such as a button, a GPS (Global Positioning System) sensor, an acceleration sensor, and a microphone, an output device such as a liquid crystal display, a processing device, and a storage device such as a memory. is there.
  • an input device such as a button, a GPS (Global Positioning System) sensor, an acceleration sensor, and a microphone
  • an output device such as a liquid crystal display
  • a processing device such as a memory.
  • the user terminal 15 transmits the context 13 to the recommended condition correction device 10 every time there is a change in the value of the input device or at regular intervals.
  • the context 13 is a position acquired by the sensor, a health state input from the input device, or a gender value stored in the storage device.
  • a part of the context 13 such as gender may be stored in the search unit 70 or the like as user profile information in association with the user ID or the like.
  • the search unit 70 adds the stored attribute information to the attribute information received from the user terminal 15 to complete the context 13.
  • the success history input terminal 16 is an information processing device including an input device such as a keyboard and a mouse, an output device such as a liquid crystal display, a processing device operated by program control, and a storage device including a memory. 31 is created and transmitted to the recommended condition correction apparatus 10.
  • the success history input terminal 16 is, for example, a POS terminal (Point of Sales) installed in a store that sells products recommended by the recommendation information.
  • the success history input terminal 16 can receive the context 13 from the user terminal 15 possessed by the user who visited the store, for example, by proximity communication.
  • the success history input terminal 16 stores, for example, correspondence information between sold product codes and recommendation condition IDs, and may create the success history 31 when inputting the sales of products.
  • the operation of the system according to the present embodiment includes a scenario registration flow for registering a scenario 12, a context processing flow performed every time a user context 13 is received, a success history processing flow performed every time a success history 31 is received, and a recommendation It can be divided into a recommended condition correction flow for correcting conditions.
  • the scenario registration flow and recommended condition correction flow are the same as those in the first embodiment.
  • the user context processing flow and the success history processing flow will be described.
  • FIG. 18 is a context processing flowchart showing the operation of the system according to the second embodiment.
  • the search unit 70 receives the context 13 from the user terminal 15, and proceeds to S-202U.
  • the search unit 70 searches the condition storage unit 40 for the condition information 41 that matches the context 13 received in S-201U, and proceeds to S-203U.
  • the condition information 41 that matches the context 13 means the condition information 41 that satisfies the conditional expression that the context 13 includes.
  • the search unit 70 creates a recommendation history 51 from the context 13 and the condition information 41, and proceeds to S-205U.
  • the search unit 70 sets the condition ID obtained from the condition information 41 and the context 13 received from the user terminal 15 to the condition ID and context 13 of the recommendation history 51 to be created.
  • the search unit 70 sets “unsuccessful” information in the recommendation success / failure information of the recommendation history 51.
  • the search unit 70 stores the recommendation history 51 generated in S-204U in the recommendation history storage unit 50, and proceeds to S-206U.
  • the search unit 70 transmits the condition information 41 to the recommendation execution device 17 and ends the process.
  • FIG. 19 is a success history process flowchart showing the operation of the system according to the second embodiment.
  • the success history registration unit 80 receives the success history 31 from the success history input terminal 16, and proceeds to S-202s.
  • the success history registration unit 80 creates a search request for the recommendation history 51 from the success history 31, and proceeds to S-203s.
  • the search request for the recommendation history 51 includes a recommendation condition ID and a user ID included in the success history 31.
  • the success history registration unit 80 searches the recommendation history storage unit 50 for the recommendation history 51 including the same recommendation condition ID and user ID as the recommendation history 51 search request, and proceeds to S-204s.
  • the success history registration unit 80 proceeds to S-205s if there is a matching recommendation history 51 as a result of S-203s, otherwise proceeds to -206s.
  • the success history registration unit 80 updates the recommendation success / failure information of the recommendation history 51 of the recommendation history storage unit 50 including the same recommendation condition ID and user ID as the received success history 31 to “success”, and ends the processing. To do.
  • the success history registration unit 8060 stores the received success history 31 in the success history storage unit 30 and ends the process.
  • the recommendation condition correction apparatus 10 can automatically store the recommendation history 51 and the success history 31 by the apparatus itself. As a result, the degree of freedom in modifying the recommendation conditions is improved, and the burden of creating and maintaining the manager's recommendation history 51 and success history 31 is reduced.
  • the recommendation condition correction apparatus 10 receives the scenario 12 from the administrator terminal 11, the context 13 from the user terminal 15, and the success history 31 from the success history input terminal 16, creates a recommendation history 51, and recommends the recommendation history 51. This is because the success history 31 is accumulated.
  • FIG. 20 is a block diagram of a recommendation condition correction system 90 according to the third embodiment of this invention.
  • a recommendation condition correction system 90 illustrated in FIG. 20 includes a recommendation condition correction apparatus 10, an administrator terminal 11, a user terminal 15, a recommendation condition correction apparatus 10, and a recommendation execution apparatus 17.
  • the recommended condition correction apparatus 10 of the present embodiment includes a registration unit 60, a condition storage unit 40, a search unit 70, a recommendation history storage unit 50, and a success history registration unit, which are configured with logic circuits, storage devices, and the like. 80, a success history storage unit 30, and a recommendation condition correction unit 20.
  • the recommended condition correction apparatus 10 may be a computer that operates under program control.
  • the registration unit 60, the condition storage unit 40, the search unit 70, the recommendation history storage unit 50, the success history registration unit 80, the success history storage unit 30, and the recommendation condition correction unit 20 are provided in the computer.
  • the central processing unit may be realized by reading and executing a program stored in the storage device.
  • the recommendation history storage unit 50, the condition storage unit 40, and the success history storage unit 30 may include a disk device included in the computer.
  • condition storage unit 40, the search unit 70, the recommendation history storage unit 50, the success history registration unit 80, the success history storage unit 30, and the recommendation condition correction unit 20 in the third embodiment of the present invention are the same as those in the second embodiment. It is the same.
  • registration unit 60, the search unit 70, and the success history registration unit 80, which are differences from the second embodiment, will be described.
  • the registration unit 60 receives the scenario 12 and registers the condition information 41 in the condition storage unit 40.
  • FIG. 21 shows an example of the scenario 12.
  • the scenario 12 includes a scenario ID, recommendation conditions, recommendation information, and expected conditions.
  • Scenario ID, recommendation condition, and recommendation information are the same information as in the first embodiment.
  • Expected condition is information including expected condition ID and conditional expression.
  • the expected condition ID is information for distinguishing the expected condition.
  • the conditional expression expresses a state expected of the user as a result of the recommendation using a part or all of the context 13.
  • the recommended condition correcting apparatus 10 determines that the user whose context 13 matches the expected condition has taken the expected behavior.
  • the condition information 41 is information including a scenario ID, a condition ID, a conditional expression, and a condition type.
  • the condition information 41 exists corresponding to the recommended condition.
  • the condition information 41 is created corresponding to both the recommended condition and the expected condition.
  • the condition type indicates whether the condition information 41 corresponds to a recommended condition or an expected condition.
  • the recommendation condition ID of the scenario 12 is stored as the association information.
  • FIG. 22 shows an example of the condition information 41.
  • the condition storage unit 40 stores one or more condition information 41.
  • FIG. 22 shows an example of a plurality of condition information 41 stored in the condition storage unit 40.
  • FIG. 22 shows an example in which the condition storage unit 40 stores four condition information 41 including recommendation condition 1, recommendation condition 2, expectation condition 1, and expectation condition 2.
  • the search unit 70 receives the context 13 from the user terminal 15 and acquires the condition information 41 that matches the context 13 from the condition storage unit 40.
  • the search unit 70 creates the recommendation history 51 and transmits the condition information 41 to the recommendation execution device 17.
  • the search unit 70 transmits the context 13 and the condition information 41 to the success history registration unit 80.
  • the success history registration unit 80 receives the condition information 41 and the context 13 and generates the success history 31 from the condition information 41 and the context 13.
  • the success history registration unit 80 generates the success history 31 from the association information (recommended condition ID) extracted from the condition information 41 and the context 13.
  • the success history registration unit 80 extracts the recommendation condition 1 of the association information (recommended condition ID) from the condition information 41 and matches it with the context 13. 26 creates the success history 31 shown in FIG.
  • the operation of the system according to the present embodiment can be divided into a scenario registration flow for registering a scenario 12, a user context processing flow performed every time a user context 13 is received, and a recommended condition correction flow for correcting a recommendation condition. .
  • the scenario registration flow and recommendation condition correction flow are the same as those in the first implementation system.
  • the user context processing flow will be described.
  • FIG. 27 is a context processing flowchart showing the operation of the system according to the third embodiment.
  • the search unit 70 receives the user context 13 and proceeds to S-302U.
  • the search unit 70 searches the condition storage unit 40 for the condition information 41 that matches the context 13 received in S-301U, and proceeds to S-303U.
  • the search unit 70 proceeds to S-304U if the condition type of the matching condition information 41 is the recommended condition as a result of the search in S-302U, and proceeds to S-307U otherwise.
  • the search unit 70 creates a recommendation history 51 from the context 13 and the condition information 41, and proceeds to S-305U.
  • the search unit 70 sets the condition ID obtained from the condition information 41 and the context 13 received from the user terminal 15 to the condition ID and context 13 of the recommendation history 51 to be created.
  • the search unit 70 sets “unsuccessful” information in the recommendation success / failure information of the recommendation history 51.
  • the search unit 70 stores the recommendation history 51 generated in S-304U in the recommendation history storage unit 50, and proceeds to S-306U.
  • the search unit 70 transmits the condition information 41 to the recommendation execution device 17 and ends the process.
  • the search unit 70 transmits the context 13 and the condition information 41 to the success history registration unit 80, and the S-308U If there is no matching condition information 41, the process is terminated.
  • the success history registration unit 80 In S-308U, the success history registration unit 80 generates a success history 31 from the received context 13 and condition information 41, and proceeds to S-309s.
  • the success history registration unit 80 generates the success history 31 from the association information extracted from the condition information 41 and the context 13.
  • the success history registration unit 80 creates a recommendation history search request from the success history 31, and proceeds to S-310s.
  • the recommendation history search request includes a recommendation condition ID and a user ID included in the success history 31.
  • the success history registration unit 80 searches the recommendation history storage unit 50 for the condition information 41 including the same recommendation condition ID and user ID as the recommendation history search request, and proceeds to S-311U.
  • the success history registration unit 80 proceeds to S-312U if there is matching condition information 41 as a result of S-310U, and proceeds to S-313U if not.
  • the success history registration unit 80 updates the recommendation success / failure information of the recommendation history 51 of the recommendation history storage unit 50 including the same recommendation condition ID and user ID as the success history 31 to “success”, and ends the process.
  • the success history registration unit 80 stores the success history 31 in the success history storage unit 30 and ends the process.
  • the recommendation condition correcting apparatus 10 of the third implementation can automatically store the recommendation history 51 and the success history 31 by the apparatus itself. As a result, the degree of freedom in modifying the recommendation conditions is improved, and the burden of creating / maintaining the recommendation history 51 and the success history 31 of the manager or the like is reduced. Furthermore, it is not necessary to input the success history 31 from the success history input terminal 16, and the burden of creating and maintaining the recommendation history 51 and the success history 31 for the manager and the like is further reduced.
  • the reason is that the recommendation condition correction apparatus 10 receives the scenario 12 from the administrator terminal 11 and the context 13 from the user terminal 15, creates the recommendation history 51, and accumulates the recommendation history 51 and the success history 31. It is.
  • FIG. 28 is a block diagram of the recommended condition correcting apparatus 10 according to the fourth embodiment of this invention.
  • the recommended condition correction apparatus 10 of the present embodiment includes a condition storage unit 40, a recommendation history storage unit 50, a success history storage unit 30, and a recommendation condition correction unit 20.
  • the condition storage unit 40 stores a recommendation condition that specifies a range of values of one or more attributes of the context 13 that is user information including a plurality of attributes.
  • the recommendation history storage unit 50 responds to each target user who is a user who has output recommendation information for encouraging a predetermined action by satisfying the recommendation condition of the context 13, and the value of each attribute of the target user context 13 and A recommendation history 51 including success / failure information indicating whether or not the target user has taken a predetermined action is stored.
  • the success history storage unit 30 stores the value of each attribute of the context 13 of the successful user in response to each successful user who is a user who has taken a predetermined action other than the target user.
  • the recommendation condition modification unit 20 corresponds to each value of each attribute included in the context 13 of all the recommendation histories 51 stored in the recommendation history storage unit 50, and the recommendation history 51 of the recommendation history 51 in which the attribute of the context 13 is the value. Of these, a first contribution ratio indicating the ratio of the recommendation history 51 indicating that a predetermined action has been taken is calculated. Further, the recommendation condition correction unit 20 calculates a second contribution ratio indicating the ratio of the success history 31 in which the value of the attribute of the context 13 matches the recommendation condition in the success history 31 for each attribute in the recommendation condition. Then, the recommendation condition is corrected based on the first contribution rate and the second contribution rate.
  • the recommendation condition correction apparatus 10 performs the deletion attribute information determination using the success history 31 accumulated in the success history storage unit 30.
  • the present invention can be applied to a recommended condition correction system 90 represented by an advertisement distribution system, a control system, a notification system, an expert system, a navigation system, and the like.

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • Operations Research (AREA)
  • Marketing (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Development Economics (AREA)
  • Educational Administration (AREA)
  • Data Mining & Analysis (AREA)
  • Game Theory and Decision Science (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

L'invention concerne un dispositif qui permet la correction efficace d'une condition de recommandation. Le dispositif stocke des conditions de recommandation spécifiant une plage de valeurs d'attributs de contextes d'utilisateur, et, pour chaque utilisateur pour qui des informations de recommandation ont été produites, enregistre un historique de recommandation incluant une valeur de chaque attribut du contexte de l'utilisateur et des informations de réussite/échec indiquant si oui ou non l'utilisateur a pris une action prédéterminée, et, pour chaque utilisateur associé à une réussite, enregistre la valeur de chaque attribut du contexte de l'utilisateur. Le dispositif calcule en outre, pour chaque valeur de chaque attribut inclus dans les contextes de toutes les entrées d'historique de recommandation, un rapport des entrées d'historique de recommandation indiquant qu'une action prédéterminée a été prise parmi les entrées d'historique de recommandation pour lesquelles l'attribut du contexte est cette valeur, et, pour chaque attribut dans la condition de recommandation, le rapport des entrées de réussite dans l'historique pour lesquelles la valeur de l'attribut du contexte correspond à la condition de recommandation parmi les entrées de réussite dans l'historique. Le dispositif corrige les conditions de recommandation en fonction des deux rapports.
PCT/JP2012/007828 2011-12-15 2012-12-06 Dispositif, procédé et programme de correction de conditions de recommandation WO2013088682A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2011-274793 2011-12-15
JP2011274793 2011-12-15

Publications (1)

Publication Number Publication Date
WO2013088682A1 true WO2013088682A1 (fr) 2013-06-20

Family

ID=48612159

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2012/007828 WO2013088682A1 (fr) 2011-12-15 2012-12-06 Dispositif, procédé et programme de correction de conditions de recommandation

Country Status (2)

Country Link
JP (1) JPWO2013088682A1 (fr)
WO (1) WO2013088682A1 (fr)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2015087963A (ja) * 2013-10-30 2015-05-07 富士ゼロックス株式会社 文書推薦プログラム及び装置
JP2016146107A (ja) * 2015-02-09 2016-08-12 株式会社Ｎｔｔドコモ 推薦情報配信システム及び推薦情報配信方法
JP2019016220A (ja) * 2017-07-07 2019-01-31 富士ゼロックス株式会社 情報処理装置及びプログラム
US11783215B2 (en) 2019-07-29 2023-10-10 Fujitsu Limited Information processing apparatus and recommendation control method
US11972327B2 (en) 2017-08-25 2024-04-30 Samsung Electronics Co., Ltd. Method for automating actions for an electronic device

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002082641A (ja) * 2000-06-08 2002-03-22 Nippon Telegr & Teleph Corp <Ntt> 情報配送方法、情報配送装置、広告提供方法、広告提供装置およびコンピュータプログラム
JP2003216608A (ja) * 2002-01-23 2003-07-31 Sony Corp 情報収集／分析方法及びシステム
JP2010073170A (ja) * 2008-09-22 2010-04-02 Yahoo Japan Corp 推薦商品選択装置、推薦商品選択プログラムおよび商品検索装置

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002082641A (ja) * 2000-06-08 2002-03-22 Nippon Telegr & Teleph Corp <Ntt> 情報配送方法、情報配送装置、広告提供方法、広告提供装置およびコンピュータプログラム
JP2003216608A (ja) * 2002-01-23 2003-07-31 Sony Corp 情報収集／分析方法及びシステム
JP2010073170A (ja) * 2008-09-22 2010-04-02 Yahoo Japan Corp 推薦商品選択装置、推薦商品選択プログラムおよび商品検索装置

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
KENTARO YAMAZAKI ET AL.: "Kodo Suisen System ni Okeru Scenario ni Motozuita Feedback Joho Shushu Archtecture", SYMPOSIUM ON MULTIMEDIA, DISTRIBUTED, COOPERATIVE AND MOBILE SYSTEMS (DICOM02011) RONBUNSHU, IPSJ SYMPOSIUM SERIES, vol. 2011, no. 1, 29 June 2011 (2011-06-29), pages 1461 - 1466 *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2015087963A (ja) * 2013-10-30 2015-05-07 富士ゼロックス株式会社 文書推薦プログラム及び装置
JP2016146107A (ja) * 2015-02-09 2016-08-12 株式会社Ｎｔｔドコモ 推薦情報配信システム及び推薦情報配信方法
JP2019016220A (ja) * 2017-07-07 2019-01-31 富士ゼロックス株式会社 情報処理装置及びプログラム
JP7031151B2 (ja) 2017-07-07 2022-03-08 富士フイルムビジネスイノベーション株式会社 情報処理装置及びプログラム
US11972327B2 (en) 2017-08-25 2024-04-30 Samsung Electronics Co., Ltd. Method for automating actions for an electronic device
US11783215B2 (en) 2019-07-29 2023-10-10 Fujitsu Limited Information processing apparatus and recommendation control method

Also Published As

Publication number Publication date
JPWO2013088682A1 (ja) 2015-04-27

Similar Documents

Publication Publication Date Title
JP4886749B2 (ja) 推薦商品選択装置、推薦商品選択プログラムおよび商品検索装置
US10162868B1 (en) Data mining system for assessing pairwise item similarity
JP5271686B2 (ja) 情報処理装置、情報処理方法、およびプログラム
US20150066940A1 (en) Providing relevant online content
US20140108139A1 (en) Marketing Segment Rule Definition for Real-time and Back-end Processing
US9619548B2 (en) Dimension widening aggregate data
US9489638B2 (en) Method and apparatus for propagating user preference information in a communications network
US20160042403A1 (en) Extraction device, extraction method, and non-transitory computer readable storage medium
US10621618B2 (en) System and method to connect a user of a product to contacts of the user who are promoters
WO2013088682A1 (fr) Dispositif, procédé et programme de correction de conditions de recommandation
CN104756143A (zh) 获得事件评论
US10223726B2 (en) Information provisioning device, method, and medium for evaluating and estimating gift candidates
US10552863B1 (en) Machine learning approach for causal effect estimation
US10909571B2 (en) Visitor identification based on feature selection
US20150134475A1 (en) Information processing apparatus, information processing method, information processing program, and recording medium storing thereon information processing program
US11854051B2 (en) Systems and methods for generating efficient iterative recommendation structures
US10803471B2 (en) Audience size estimation and complex segment logic
US20150248720A1 (en) Recommendation engine
US20210133203A1 (en) System and method for converting user data from disparate sources to bitmap data
JP2010262484A (ja) ユーザ管理方法及び情報処理システム
JP2008027358A (ja) レコメンド装置、レコメンド方法、及びプログラム
US10692127B1 (en) Inferring user demographics from user behavior using Bayesian inference
US11734706B2 (en) Systems and methods for providing user offers based on efficient iterative recommendation structures
JP2020154841A (ja) 決定装置、決定方法及び決定プログラム
JP7249316B2 (ja) 情報処理装置、情報処理方法、及び情報処理プログラム

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 12858087

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2013549107

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 12858087

Country of ref document: EP

Kind code of ref document: A1