WO2015016094A1 - 情報処理装置、情報処理方法、及び、プログラム - Google Patents
情報処理装置、情報処理方法、及び、プログラム Download PDFInfo
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- WO2015016094A1 WO2015016094A1 PCT/JP2014/069275 JP2014069275W WO2015016094A1 WO 2015016094 A1 WO2015016094 A1 WO 2015016094A1 JP 2014069275 W JP2014069275 W JP 2014069275W WO 2015016094 A1 WO2015016094 A1 WO 2015016094A1
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Definitions
- the present technology relates to an information processing device, an information processing method, and a program, and particularly relates to an information processing device, an information processing method, and a program suitable for use in recommending a seat or an area assigned to a user in an event. .
- some conventional events such as concerts, theaters, and movies can be purchased by the user by selecting a preferred seat from among vacant seats.
- the present technology improves the user's satisfaction with the seats or areas assigned to the user at the event.
- An information processing apparatus includes a recommendation unit that matches a feature of a seat or area assigned to a user in an event with the feature of the user and selects a combination of the recommended seat or area and the user.
- a combination of a recommended seat or area and a user is selected based on a distance between a seat vector that is a vector representing a seat or area feature and a user vector that is a vector representing a user feature. Can be made.
- each seat or area is presented separately based on the distance between the seat vector of each seat or area and the user vector of the user. It is possible to further provide a presentation control unit for controlling.
- the recommendation unit has a second seat vector that has a seat vector smaller than the first seat or area for a user to whom a first seat or area is assigned. Can recommend a seat or area.
- a seat vector generation unit that generates the seat vector of each seat or area based on metadata about each seat or area, and a user vector generation unit that generates the user vector of each user based on metadata about each user And can be further provided.
- the image simulates the appearance of the event area that is the area where the event is held in the event venue from the seat or area recommended to the user, and the surroundings of the seat or area recommended to the user Can be.
- the feature of the seat or area includes the feature of the user that is preferentially assigned to the seat or area, and the recommendation unit is based on the feature of the user and the feature of the user that is preferentially assigned to each seat or area.
- the user can select a recommended seat or area and a combination of users.
- the recommendation unit recommends facilities and seats used by the target user before the event or after the event. Can be further performed.
- the feature of the seat or area is a feature related to how the event area is an area where the event is held in the event venue from the seat or area, and a feature related to how sound is heard in the seat or area. , Including at least one of a feature relating to a spectator around the seat or area, a feature relating to the environment of the seat or area, and a feature of a user assigned with priority to the seat or area. At least one of the user's attributes, the user's physical characteristics, the user's preferences, and the user's view of the event.
- the event audience is classified into a plurality of types based on at least one of audience attributes, audience physical characteristics, audience preference characteristics, and audience event viewing characteristics. It is possible to further provide a presentation control unit that performs control so as to distinguish and present the audience distribution for each type.
- a sales strategy setting unit that can set a sales strategy indicating whether or not to make a recommendation to the user for each seat or area of the event is further provided, and the recommendation unit is set to make a recommendation to the user It is possible to recommend a seat or area.
- the sales strategy setting unit may be able to set a different sales strategy when a cancellation occurs, when the seat is vacant even after a predetermined time limit, and when it is not.
- the recommendation unit further sets a fee for the event and a privilege for the participant of the event, and recommends a seat or area to be recommended, the fee, and the privilege based on the user's preference for the event.
- the content of the combination can be adjusted.
- the recommendation unit recommends a virtual seat or area that determines how the event area in the video is to be viewed. Can be made.
- the information processing method includes a recommendation step of matching a feature of a seat or area assigned to a user in an event with a feature of the user and selecting a combination of the recommended seat or area and the user.
- the program according to one aspect of the present technology matches a feature of a seat or area assigned to a user in an event with the feature of the user, and performs processing including a recommendation step of selecting a combination of the recommended seat or area and the user on the computer. Let it run.
- a feature of a seat or area assigned to a user in an event is matched with a feature of the user, and a recommended seat or area and user combination are selected.
- FIG. 1 is a block diagram illustrating an embodiment of an information processing system to which the present technology is applied. It is a figure for demonstrating a virtual seat. It is a block diagram which shows the structural example of the function of a recommendation system. It is a flowchart for demonstrating a seat vector production
- Embodiment 2 modes for carrying out the present technology (hereinafter referred to as embodiments) will be described. The description will be given in the following order. 1. Embodiment 2. FIG. Modified example
- FIG. 1 is a block diagram illustrating an embodiment of an information processing system 11 to which the present technology is applied.
- the information processing system 11 is a system for recommending events and seats, selling event tickets, and the like.
- the information processing system 11 also recommends an action plan before or after the event.
- the event to be handled by the information processing system 11 is, for example, an entertainment event in which a performer or an organizer exists.
- the type of event to be targeted is not particularly limited as long as it is an event in which a user is assigned a seat or an area so that the user can view the event or participate in the event.
- special venues where seats and areas are temporarily set up such as live events (eg concerts, plays, sports games, etc.), movies, lectures, etc., and outdoor festivals, festivals, fireworks, etc. Events that take place in
- participatory events such as town cons (men and women encounter parties held around the town) are also targeted.
- the seat or area assigned to the user is a seat or area for the user himself / herself to participate in the event in addition to viewing the event.
- events that allow remote participation such as live viewing and live video distribution are also targeted.
- events in a virtual space such as virtual live using computer graphics (hereinafter referred to as virtual events) are targeted.
- the event fee may be charged or free.
- the venue where the event is held is not particularly limited as long as a seat or an area is allocated to the user.
- a hall, an arena, a theater, a movie theater, a stadium, a stadium, a live house, a restaurant, a special outdoor venue, and the like are assumed.
- an area where an event is held in the event venue (for example, an area where a concert or a game is held in the hall, an area where images are projected, an area where fireworks are launched, etc.) is referred to as an event area.
- an event area For example, a stage, a screen, a ground of a ball game field, a field, a court, a track of a stadium, a link, and the like are assumed.
- the information processing system 11 includes a recommendation system 21, an information presentation unit 22, an information presentation unit 23, a ticket sales system 24, an event information database (DB) 25, a customer seat sales situation database (DB) 26, a user profile database (DB) 27, A purchase history information database (DB) 28, an organizer profile database (DB) 29, and an action plan database (DB) 30 are included.
- the recommendation system 21 uses the information stored in each DB to recommend an event to the user and an action plan before and after the event. As will be described later, the recommendation system 21 can not only recommend events but also recommend event seats.
- the recommendation of the seat of the event is performed in units of seats or areas.
- the recommendation of the seat of the event is performed in units of seats or areas.
- recommendation is performed in units of areas.
- each venue is treated as one area, and each area (venue) unit. A recommendation will be made.
- a virtual seat or area (hereinafter referred to as a virtual seat) is recommended. It becomes.
- the virtual seat is realized by, for example, artificially changing the appearance of an area (event area) in which an event in a video delivered to the user's environment is performed in the same manner as an actual seat.
- an image in which the performer 41 is close to the stage and looks large is delivered to a user of a virtual seat with a high fee or grade.
- the virtual seat user with the lower price or grade as shown in the middle or lower figure, a video that makes the performer 41 appear smaller from the stage is distributed. Thereby, a virtual seat is realized.
- the seat includes the concept of an area unless the seat and the area need to be particularly distinguished, and the seat or area is simply referred to as a seat.
- the recommendation system 21 sequentially updates the information in the audience sales situation DB 26, the user profile DB 27, the purchase history information DB 28, the organizer profile DB 29, and the action plan DB 30 according to the situation such as the recommendation process. Further, the recommendation system 21 transmits / receives information necessary for processing to / from the ticket sales system 24.
- the information presentation unit 22 presents various information transmitted from the recommendation system 21 and the ticket sales system 24 to the user. For example, the information presentation unit 22 presents information related to events and seats recommended for the user. The information presentation unit 22 transmits information input by the user to the recommendation system 21 and the ticket sales system 24.
- the information presentation unit 22 is configured by a terminal used by a user (for example, a computer, a mobile phone, a smartphone, a tablet terminal, or the like) or an application program that operates on a terminal used by the user.
- the information presentation unit 22 may be incorporated in the ticket sales system 24 and configured by a terminal (for example, a multimedia terminal) placed at a store such as a ticket sales store or a convenience store, or an application program operating on the terminal. Is possible.
- the information presentation unit 23 presents various information transmitted from the recommendation system 21 to an event organizer or the like.
- the information presentation unit 23 presents information related to event ticket sales status, sales strategy, analysis data of past ticket sales results, and the like.
- the information presentation unit 23 transmits information input by the organizer or the like to the recommendation system 21.
- the information presentation unit 23 is configured by a terminal (for example, a computer, a mobile phone, a smartphone, a tablet terminal, or the like) used by an organizer or the like, or an application program that operates on a terminal used by the organizer or the like.
- a terminal for example, a computer, a mobile phone, a smartphone, a tablet terminal, or the like
- an application program that operates on a terminal used by the organizer or the like.
- organizers and the like include, for example, traders involved in the event (for example, owners, ticket sellers, event venue owners, etc.) and owners of facilities used in action plans before and after the event.
- the ticket sales system 24 is a system for managing event ticket sales and reservations using information stored in each DB.
- the ticket sales system 24 displays a ticket sales screen or website on a terminal placed at a store such as a ticket sales store or a convenience store, an information presentation unit 22 of each user, and the like. Provide service. Further, the ticket sales system 24 sequentially updates the information in the customer seat sales status DB 26, the user profile DB 27, and the purchase history information DB 28 in accordance with the ticket sales status and the like.
- ticket sales by the ticket sales system 24 include, for example, a case where an event seat right is given without issuing a ticket such as a paper medium or an electronic ticket.
- a user who is given the right to seat an event is permitted to enter or sit in the venue, for example, by identity authentication.
- the event information DB 25 holds event information related to events handled by the information processing system 11.
- the event information includes, for example, all or some of the following information.
- the event information includes an event ID for identifying each event, the date and time of the event, the venue, the contents of the event, the performers, the fee, and the like.
- the event information includes, for example, information on the progress and performance of each event such as a timetable, the appearance order of performers, scheduled appearance time, set list, lighting and movement of the set.
- the event information includes, for example, venue information regarding the venue of each event.
- the venue information mainly includes information that affects the environment of the audience seat and the appearance of the event area from the audience seat.
- the venue information includes the venue type, size, seat arrangement, seat type (S seat, A seat, standing seat, non-smoking seat, smoking seat, etc.), seat interval, seat specifications (eg, shape, Information such as size, material, etc.) and the surrounding environment of the seat (for example, the entrance / exit, passage, position of air conditioning equipment, etc.).
- the venue information includes, for example, information on the facilities and settings of each event venue, such as event areas, sets, musical instruments, lecture stands, chairpersons, lighting, audio equipment, equipment positions and specifications.
- the venue information includes, for example, information when the venue setting changes in time series.
- the venue information includes a seat vector representing the characteristics of each seat.
- the event information includes, for example, information about the virtual seat such as the relationship between the virtual seat and the appearance of the event area in the video to be distributed.
- the event information is information that affects the appearance of the performer from the audience, such as the physical characteristics of the performer of the event (for example, height, body shape, etc.), the characteristics of movement and performance, the costume of the performer, etc. including.
- performers include persons and animals that are the targets of the event.
- performers include sports players and circus animals.
- event information is created and held for each event.
- venue information is created and held for each venue.
- the guest seat sales status DB 26 holds customer seat sales status information indicating the sales status or reservation status of each event.
- the passenger seat sales status information includes, for example, an event ID, vacant seat information indicating the position of a vacant seat, a user ID for identifying a user who has purchased or reserved a seat, and the like.
- the user profile DB 27 holds a user profile that is information about each user who uses the service provided by the information processing system 11.
- the user profile includes, for example, all or some of the following information.
- the user profile includes general attributes of the user such as user ID, gender, age, nationality, address, occupation, hometown, educational background, and the like.
- the user profile includes, for example, the user's physical characteristics.
- the user profile includes physical features of the user that affect the appearance of the event area of the user himself and the surrounding users, such as height, sitting height, body shape, visual acuity, whether or not a wheelchair is used, and the like.
- the user profile includes, for example, preference information related to user preferences.
- preference information includes user events such as favorite artists, favorite group members, favorite teams, favorite players, favorite event types, favorite genres, favorite or favorite instruments, favorite stage sets, etc. Including preference information).
- preference information includes preference information for the user's venue and seat such as a favorite venue, a favorite seat position, an angle for viewing a favorite event area, a favorite seat type, a favorite seat specification, and the like.
- the user profile includes, for example, viewing feature information indicating the viewing feature of the user's event.
- View feature information includes, for example, making noise, singing, dancing, intense movement, laughing, crying, clapping hands, watching quietly, sitting and watching, standing, sleeping, cheering, raising a strange voice, skipping a goat , Tweet, talk with the surroundings, cosplay, use cheering goods, poor pants, drink alcohol, often take a seat, join late, return on the way, etc.
- the viewing characteristic information may include not only the user's actual characteristics but also the user's wishes such as wanting to make a noise, singing, or dancing. Further, in consideration of the fact that the user's view of the event is different for each event type and performer, each user's view characteristic information may be separately provided for each event type and performer.
- viewing feature information can be created based on questionnaire responses from each user, or can be created based on video, image, and sound analysis results near the seats of each user during the event. It is.
- viewing feature information can be created based on questionnaire responses from each user, or can be created based on video, image, and sound analysis results near the seats of each user during the event. It is.
- information on the user's viewpoint characteristics may be extracted and reflected in the viewpoint characteristic information. Is possible.
- the user profile includes a user vector that represents the user's characteristics.
- the purchase history information DB 28 holds purchase history information related to the purchase history of each user's past event tickets.
- the purchase history information includes, for example, all or some of the following information.
- the purchase history information includes information such as the user ID, the number of purchases, the venue of the purchased event, the seat type and the seat position, the type of event (eg, movie, theater, concert, sports, etc.), the performer of the event, etc. Including. Further, the purchase history information is information indicating purchase patterns of each user such as repeatedly purchasing tickets of the same type of event (for example, concerts of the same artist, etc.), purchasing tickets of a wide range of genres, and rarely purchasing tickets. including. Further, the purchase history information includes a history of reservations for the recommended action plan before or after the event.
- the purchase history information includes a history of reservations for the recommended action plan before or after the event.
- ticket purchases not only ticket purchases but also a history such as each user viewing information related to an event or adding a bookmark or the like for considering ticket purchases may be included in the purchase history information. Moreover, you may make it update the user profile of each user of user profile DB27 based on purchase history information.
- the organizer profile DB 29 stores an organizer profile that is information provided by the organizer for each event.
- the organizer profile includes, for example, all or some of the following information.
- the organizer profile indicates an organizer ID for identifying the organizer, an event ID, sales policy information indicating the sales policy of the organizer for each event, and schedules and events of performers of each event. Contains information.
- the sales policy information includes, for example, a sales target (for example, sold out or what percentage or more is sold) and sales strategy information.
- Sales strategy information includes, for example, information such as the presence / absence of promotion for each event, the method of promotion, the timing of promotion, the presence / absence and discount rate of ticket fees, the presence / absence of benefits to event participants, and the contents of benefits.
- the contents of the privilege include, for example, a handshake ticket, a signing ticket, a gift of related goods, a dressing room visit, a right to download premium content using AR (Augmented Reality), and the like.
- a camera or a display may be provided at a specific seat so that communication can be performed with performers and audiences at other seats (for example, talking or singing together).
- a camera or a display may be provided at a specific seat so that communication can be performed with performers and audiences at other seats (for example, talking or singing together).
- the sales strategy information includes, for example, seating policy information indicating a policy for allocating spectators to the audience seats.
- the seating policy information includes, for example, information indicating which seat or area from which the audience is preferentially filled, and information indicating the type of audience preferentially arranged in each seat or each area.
- the audience type can be classified based on at least one of an attribute, a physical feature, a feature related to preference, and a feature related to viewing the event, for example. More specifically, for example, the type of audience is classified according to the fans of each member of the group to appear, core fans and light fans, sex, age group, and the like.
- a sales strategy can be set and implemented for each event seat.
- the action plan DB 30 holds information used for recommending an action plan before or after an event.
- the action plan DB 30 holds a facility database (DB) regarding facilities used in the action plan.
- the action plan DB 30 holds an action desired ranking in which actions that the user desires to perform before and after the event are ranked.
- FIG. 3 is a block diagram illustrating a configuration example of functions of the recommendation system 21.
- the recommendation system 21 is configured to include a seat vector generation unit 51, a user vector generation unit 52, a recommendation unit 53, a sales strategy setting unit 54, an information analysis unit 55, and a presentation control unit 56.
- the seat vector generation unit 51 generates a seat vector representing the characteristics of each seat of each event based on the information in the event information DB 25, the audience sales situation DB 26, the user profile DB 27, and the organizer profile DB 29.
- the seat vector generation unit 51 stores information indicating the generated seat vector in the event information DB 25.
- the user vector generation unit 52 generates a user vector representing the characteristics of each user based on information in the user profile DB 27 and the purchase history information DB 28.
- the user vector generation unit 52 stores information indicating the generated user vector in the user profile DB 27.
- the recommendation unit 53 selects a combination of a recommended event and a user, and a combination of a recommended event seat and a user based on information in each DB. In other words, the recommendation unit 53 selects an event to be recommended to a user or a seat of an event based on information in each DB, or selects a user who recommends an event or an event seat. Further, the recommendation unit 53 selects an action plan before and after an event to be recommended to the user based on information in each DB. Furthermore, the recommendation part 53 sets the charge of an event, and a privilege based on the information of user profile DB27 and organizer profile DB29.
- the sales strategy setting unit 54 generates and updates sales strategy information based on a command from the organizer or the like input via the information presenting unit 23, and stores it in the organizer profile DB 29.
- the information analysis unit 55 includes information from the user input through the information presentation unit 22, information from the organizer and the like input through the information presentation unit 23, information from the ticket sales system 24, and each DB Based on this information, various types of information analysis such as user behavior and preferences, event ticket sales status, and the like are performed. For example, the information analysis unit 55 aggregates the behaviors desired by the user before and after the event based on information input by the user, and stores the desired behavior ranking indicating the aggregation results in the behavior plan DB 30. Further, the information analysis unit 55 aggregates the event ticket and the sales situation of the passenger seat based on the information in the customer seat sales situation DB 26 and the purchase history information DB 28. Furthermore, the information analysis part 55 supplies an analysis result to the ticket sales system 24 as needed, or memorize
- the presentation control unit 56 controls the presentation of various information by the information presentation unit 22 and the information presentation unit 23.
- the presentation control unit 56 controls the presentation by the information presentation unit 22 of the event recommended to the user, the event seat, the action plan before the event, and the action plan for each event.
- the presentation control unit 56 controls the presentation of the event ticket and the sales situation of the audience seat by the information presentation unit 23.
- Event and seat recommendation process Next, event and seat recommendation processing executed by the information processing system 11 will be described with reference to FIGS.
- an event to be processed is referred to as a target event
- a user to be processed is referred to as a target user.
- This process is performed, for example, regularly or when information related to the target event in the event information DB 25, the audience seat sales status DB 26 or the organizer profile DB 29 is changed, or when a seat is recommended to the user. To be executed.
- step S1 the seat vector generation unit 51 collects information related to the audience of the target event from the event information DB 25, the audience sales situation DB 26, the user profile DB 27, and the organizer profile DB 29. At this time, as long as it is information related to the audience seat of the target event, all directly or indirectly related information may be collected, or the range of information to be collected may be limited.
- the seat vector generation unit 51 extracts the metadata of each seat from the collected information. Specifically, the seat vector generation unit 51 extracts information on each seat from the collected information for each seat of the venue of the target event, and divides the extracted information into appropriate units, thereby Extract metadata. At this time, the seat vector generation unit 51 may process the collected information as necessary to generate metadata for each vacant seat. For example, metadata relating to musical instruments and the like that can be seen from each seat may be generated from information relating to stage settings and seat positions.
- step S3 the seat vector generation unit 51 generates a seat vector for each seat based on the metadata. That is, the seat vector generation unit 51 generates a seat vector representing the feature of each seat by vectorizing the metadata of each seat by a predetermined method.
- the features of the seat represented by the seat vector include, for example, a feature related to the appearance of the event area from the seat, a feature related to how the sound is heard in the seat, a feature related to the audience around the seat, a feature related to the environment of the seat, and It includes at least one of the user features preferentially assigned to the seat.
- the features related to how the event area looks from the seat include, for example, the positional relationship between the seat and the event area, the presence and location of obstacles between the seat and the event area, the musical instruments that can be seen from the seat, and the members of the performers that can be seen from the seat Including features such as the position and size of the set, etc., visible from the seat.
- Features related to how to hear sound at the seat include, for example, specifications of the audio equipment in the venue, the positional relationship between the seat and the audio equipment, the presence or absence of an obstacle between the seat and the audio equipment, and the position.
- the characteristics related to the audience around the seat are, for example, the characteristics extracted from the user profile of the audience around the seat. For example, the attributes of the surrounding audience, the physical characteristics, the taste characteristics, the characteristics of the event view, etc. Including.
- the features related to the seat environment are, for example, features representing the comfort of the seat, and include features such as the type of the venue, seat spacing, seat specifications, and the environment surrounding the seat.
- the feature of the user that is preferentially assigned to the seat is, for example, information extracted from the seating policy information of the organizer profile DB 29 described above, and includes the type of audience that is preferentially placed on the seat.
- each metadata may be vectorized by giving a weight according to the importance.
- the organizer profile It is conceivable to set a large weight for metadata extracted from information in the DB 29. If only the intention of the organizer or the like is to be reflected, it is conceivable to set the weight of metadata other than the metadata extracted from the information in the organizer profile DB 29 to 0.
- the seat vector generation unit 51 stores information indicating the seat vector of each seat of the generated target event in the event information DB 25.
- This process is executed, for example, regularly, when information about the target user in the user profile DB 27 or the purchase history information DB 28 is changed, or when a seat is recommended for the target user. .
- step S21 the user vector generation unit 52 collects information on the target user from the user profile DB 27 and the purchase history information DB 28. At this time, as long as it is information related to the target user, all directly or indirectly related information may be collected, or the range of information to be collected may be limited.
- step S22 the user vector generation unit 52 extracts the metadata of the target user from the collected information. Specifically, the user vector generation unit 52 extracts the metadata of the target user by dividing the collected information into appropriate units or discarding unnecessary information. At this time, the user vector generation unit 52 may process the collected information as necessary to generate metadata of the target user.
- step S23 the user vector generation unit 52 generates a user vector of the target user based on the metadata. That is, the user vector generation unit 52 generates a user vector representing the characteristics of the target user by vectorizing the target user's metadata by the same method as the process of step S3 in FIG. At this time, each metadata may be vectorized by giving a weight according to the importance.
- the feature of the target user represented by the user vector is, for example, at least one of the attribute of the target user, the physical feature of the target user, the feature related to the preference of the target user, and the feature related to how the target user views the event. Including.
- generation part 52 memorize
- Event recommendation process push type event recommendation processing executed by the information processing system 11 will be described with reference to the flowchart of FIG. This process is executed, for example, when a push-type promotion for the target event is performed.
- the recommendation unit 53 narrows down users based on conditions presented by the organizer or the like as necessary. Specifically, the recommendation unit 53 narrows down candidate users who are candidates for recommending the target event, as necessary, based on information in the organizer profile DB 29. Thereby, for example, candidate users are narrowed down to fans of a specific artist, users of a specific age group, users of a specific gender, and the like.
- candidate users may be narrowed down for each seat or area in the venue. That is, different candidate users may be extracted for each seat or area.
- candidate users may be narrowed down for each venue. Thereby, for example, it becomes possible to collect fans of a specific member of a group appearing in an event in a specific area or a specific venue in the venue.
- the recommendation unit 53 performs matching between the feature of each seat of the target event and the feature of the user, and selects a target user who recommends each seat. Specifically, the recommendation unit 53 reads the seat vector of each vacant seat of the target event from the event information DB 25. Note that when a seat to be recommended is determined by the organizer or the like, the recommendation unit 53 reads only the seat vector of the seat set as the recommendation target from the vacant seats of the target event. The recommendation unit 53 reads the user vector of each candidate user from the user profile DB 27.
- the recommendation unit 53 calculates the distance between the vectors (that is, the similarity between the corresponding feature vector) for all combinations of the read seat vector and the user vector.
- the distance between the vectors for example, a cosine distance, an Euclidean distance, or the like is used.
- the recommendation part 53 extracts the candidate user from which the distance between vectors became below a predetermined threshold value for every seat, for example, and selects it as the object user who recommends each seat.
- the recommendation unit 53 selects a candidate user that falls within a predetermined upper rank as a target user who recommends each seat. Thereby, the user who has the characteristic suitable for the characteristic of each seat is selected as an object user. The same user may be selected as a target user for a plurality of seats.
- a user who has already purchased a ticket for the target event can be selected as the target user. That is, for example, when a seat is canceled, when a good seat remains, when an upgrade of a seat is recommended, a seat to be exchanged for a purchased seat may be recommended to the target user. Good.
- step S103 the recommendation unit 53 sets a ticket fee and a privilege as necessary. That is, the recommendation unit 53 sets a ticket fee and a privilege to be presented to the target user based on information in the user profile DB 27 and the organizer profile DB 29.
- the content of the combination of the recommended seat, the ticket fee, and the privilege may be adjusted.
- a method for adjusting the content of the combination of recommended seats, ticket fees, and benefits will be described later with reference to FIGS.
- step S104 the information processing system 11 recommends the target event together with the recommended seat to the target user.
- the presentation control unit 56 generates recommended event information for recommending a target event to each target user.
- the recommended event information includes recommended seat information related to recommended seats recommended for the target user.
- This recommended seat information includes, for example, information on how the event area is seen from the recommended seat, how to hear sound in the recommended seat, the audience around the recommended seat, the environment of the recommended seat, and the like.
- the presentation control part 56 transmits the produced
- the information presentation unit 22 presents the received recommended event information to the target user.
- any method can be adopted as a method for presenting recommended event information.
- an e-mail including recommended event information may be transmitted to the target user.
- the recommended event information may be posted on the target user page of the website for members.
- recommended event information may be presented using social media such as SNS (Social Networking Service).
- the recommended event information may be presented using an application program that operates on the event information.
- the event information may be immediately notified to the target user by a method such as automatically starting an application program upon receiving event information or automatically displaying a pop-up display of the program. Is possible.
- not only information on the recommended target event but also information on the recommended seat is presented to the target user. Furthermore, it is possible to visually present not only the position of the recommended seat, but also, for example, how the event area is viewed from the recommended seat and the surroundings.
- an entire screen including a bird's-eye view of the entire venue is displayed.
- This entire screen shows the positional relationship between the event area (in this example, the stage) and the audience seats, and the positions of instruments, sets, etc. on the event area. Also, the position of the recommended seat in the venue is shown.
- a detailed screen including an image simulating the field of view from the selected recommended seat is displayed. For example, when seat A is selected from the entire screen of FIG. 7, a detailed screen including an image simulating the field of view from seat A schematically shown in FIG. 8 is displayed, and when seat B is selected, FIG. A detailed screen including an image simulating the field of view from the seat B schematically shown in FIG.
- images that simulate the appearance of the event area (stage in this example) from each seat and the surroundings of each seat are displayed.
- performers' models, musical instruments, sets, and the like simulating height and body shape are displayed on the stage according to the actual arrangement.
- a model of the surrounding audience that simulates height (sitting height), body shape, movement (eg standing, seeing, moving violently, etc.) is displayed according to the actual seat of each audience. .
- seat A is closer to the center than seat B and is closer to the center, but in front of seat A there are many tall, standing and noisy audiences. Therefore, it is highly possible that the field of view is obstructed or that you cannot sit down and enjoy the event slowly. On the other hand, there is a high possibility that they can get excited, stand up and make noise with the surrounding audience.
- seat B is farther from the stage than seat A and off the center, but in front of seat B there are few tall, standing or noisy audiences. Therefore, there is a high possibility that you can sit down and enjoy the event without being blocked. On the other hand, there is a high possibility that they cannot swell, stand up or make noise with the surrounding audience.
- the atmosphere around the recommended seat (for example, the degree of excitement and quietness) may be represented by a color or an image.
- a privilege set by the organizer or the like for the recommended seat may be presented as the reason for recommendation. For example, “To the customers in this area, performers often throw their eyes from the stage (otherly, wave their hands, kiss them, etc.)”, “The performers are facing customers in this area. You can also present a reason for the recommendation, such as “throwing presents (for example, what you are wearing)” or “the area where the performers walk in the middle of the event and can shake hands if they are lucky” Good. In the case of an event where there are a large number of performers, for example, the seat recommendation may be made for the performers that the target user likes, and the reasons for the recommendation may be presented.
- a recommendation reason such as “The state of this area is scheduled to be broadcast at least five times on the day of the live broadcast of the TV station” may be presented.
- “Customers in this area can enjoy a touching experience on the day. Good.
- the whole venue was in the galaxy, the seats in the target area rose, and both the beautiful production and the artist who sang with special costumes singing You may make it perform the production which can be seen from the sky.
- the arrangement of the occupant seats and the positions of the vacant seats may be presented, and the vacant seats may be distinguished and presented by color coding based on the distance between the user vector of the target user and the seat vector of each seat. .
- the target user can easily find a seat that suits his / her compatibility from the empty seats.
- step S105 the ticket sales system 24 determines whether or not the target user has purchased a ticket for the target event. If it is determined that the target user has purchased a ticket for the target event, the process proceeds to step S106.
- step S106 the ticket sales system 24 updates the customer seat sales status DB 26 and the purchase history information DB 28.
- step S105 if it is determined in step S105 that the target user has not purchased the ticket for the target event, the process in step S106 is skipped, and the event recommendation process ends.
- a seat with high satisfaction that suits each user's preference. For example, for a user who likes piano, a seat where the pianist's finger can be seen is recommended, or for a user who likes to make noise, a seat with a lot of good spectators around is recommended. For a user who wants to do so, it is possible to recommend a seat with many spectators around.
- each user can visually confirm how the event area is viewed from the recommended seat and the surroundings, and can select a seat with higher satisfaction. Thereby, the user's satisfaction with the event seat is improved, and as a result, the user's satisfaction with the entire event is also improved.
- the user can visually confirm that, select a seat after being convinced, and purchase a ticket. Therefore, for example, it is possible to prevent the user from being disappointed by sitting in a different seat from the image expected at the time of purchase.
- the user seat is divided into several areas that are circled, and the types of users to be preferentially arranged for each area are set, and set for each type of user. It is also possible to recommend seats in the selected area.
- each area may be changed during the event. That is, for example, the seats of the users in the area A and the users in the area B may be exchanged during the event.
- the fans of each performer can be moved to an easy-to-view seat on the stage.
- users of a type that raises the audience seats may be preferentially arranged in the areas indicated by hatching in each area in FIG. 10 (hereinafter referred to as representative areas).
- representative areas users of a type that raises the audience seats
- the types of users to be excited are distributed, and as a result, the entire area is excited without the area to be excited becoming a specific area.
- a user representing a type of user preferentially arranged in that area may be preferentially arranged.
- a user having a user vector whose distance from the average value of seat vectors in a certain area is equal to or smaller than a predetermined threshold may be preferentially arranged in the representative area of the area.
- a user having a user vector whose distance from an average value of user vectors of a type of user preferentially arranged in a certain area is equal to or less than a predetermined threshold is preferentially arranged in the representative area of the area. May be.
- the type of user it is possible to change the type of user to be preferentially arranged for each area at a predetermined timing (for example, periodically). Thereby, the types of users arranged in one area can be distributed.
- the type of audience to be preferentially arranged for each venue may be changed.
- the fans of each member of the performers can be collected in different venues, and videos preferentially showing the target members can be distributed to each venue.
- the type of audience that is preferentially arranged each time may be changed. For example, when a concert of a certain group is continuously performed, when members to be featured are different at each time, it is possible to preferentially enter the fans of each member at each time.
- Event recommendation process Pull type
- This process is started, for example, when the target user inputs an event recommendation command to the recommendation system 21 via the information presentation unit 22.
- the recommendation unit 53 selects a target event to be recommended to the target user. For example, when a condition is given by the target user, the recommendation unit 53 selects an event that satisfies the condition as the target event. For example, when the condition is not given from the target user, the recommendation unit 53 extracts an event that matches the target user's preference using a predetermined method and selects the event as the target event.
- the number of target events recommended for the target user is not limited to one, and may be plural.
- the number of target events recommended to the target user is one will be described.
- the recommendation unit 53 performs matching between the characteristics of each seat of the target event and the characteristics of the target user, and selects the recommended seat. Specifically, the recommendation unit 53 reads the seat vector of each vacant seat of the target event from the event information DB 25. Note that when a seat to be recommended is determined by the organizer or the like, the recommendation unit 53 reads only the seat vector of the seat set as the recommendation target from the vacant seats of the target event. The recommendation unit 53 reads the user vector of the target user from the user profile DB 27. Further, the recommendation unit 53 calculates the distance between the vectors for all combinations of the read seat vector and the user vector.
- the recommendation part 53 selects the vacant seat where the distance between vectors became below a predetermined threshold value as a recommended seat recommended to the target user, for example.
- the recommendation unit 53 selects, for example, a vacant seat that falls within a predetermined predetermined rank as a recommended seat when vacant seats are arranged in ascending order of the distance between vectors. As a result, a seat having characteristics that match the characteristics of the target user is selected as the recommended seat.
- steps S153 to S156 the same processing as steps S103 to S106 in FIG. 6 is executed, and the target event and the recommended seat are recommended to the target user.
- FIG. 13 to FIG. 16 are combinations of seats, ticket charges, and privileges according to the user's A and B's preference for events (including the preference for event performers) in the case shown in FIG.
- the example of the method of adjusting the content of is shown.
- FIGS. 13 to 16 four axes having the same contents are shown.
- the leftmost axis indicates the user's preference for the event.
- the preference level is classified into four clusters according to the strength of preference, and the preference level increases as it goes down (that is, the core fan), and the preference level decreases as it goes up.
- the second axis from the left indicates the seat level.
- the seat level is classified into four clusters according to a predetermined standard.
- the seat level decreases as it goes down, and the seat level increases as it goes up.
- FIGS. 13 to 16 in order to make the explanation easy to understand, the order of the front and rear of the seats is shown in alphabetical order, and the seats are simply the better seats that go forward and the worse the seats that go back.
- the third axis from the left shows the ticket price.
- the ticket fee is classified into four clusters according to the level of the fee. The ticket fee increases as it goes down, and the ticket fee decreases as it goes up.
- the rightmost axis indicates the presence / absence and level of benefits.
- the benefits are classified into four clusters according to their contents, and there are no benefits at the bottom, and the content of the benefits improves as it goes up.
- the axis from the second axis from the left to the right end is more advantageous to the user as it goes up.
- the contents of the combination of the recommended seat, the ticket fee, and the privilege are adjusted so as to be balanced from the viewpoint of loss and profit.
- the contents of the benefits of both are set to the same level, and the seat and the ticket fee are set in a trade-off relationship. That is, instead of recommending a seat better than user B to user A, the ticket fee of user A is set higher than user B. Alternatively, instead of setting the ticket price of the user A higher than that of the user B, a better seat than the user B is recommended to the user A. Thus, by giving a better seat to a user who pays a higher fee, an unfair feeling between them can be suppressed.
- the seat levels recommended for both are set to the same level, and the ticket fee and the privilege are set in a trade-off relationship. That is, instead of setting a ticket fee cheaper than user B for user A, a privilege is granted only to user B, or a privilege better than user A is granted to user B. Alternatively, a privilege is given only to the user B, or a ticket fee of the user B is set higher than that of the user A instead of giving a privilege better than the user A to the user B. Thus, by giving a better privilege to a user who pays a higher fee, an unfair feeling between the two can be suppressed.
- the ticket charges and benefits of both are set to the same level, and a better seat than user B is recommended to user A. Further, for example, as shown in FIG. 16, seats of the same level are recommended for both, and the ticket fee of user A is set lower than that of user B. In this way, by recommending better seats or presenting cheap ticket prices to users who have a high degree of preference and a high demand for events, an unfair feeling between them (especially a user with a high degree of preference) Unfairness).
- a privilege may be additionally given to the user A.
- the event information may be presented only to the user A who is a core fan to recommend the event. That is, since the event is just before the event is held, the deals may be provided only to the user A who has a high probability of purchasing a ticket and has a high degree of preference.
- CRM Customer Relationship Management
- a user who participates in the same type of event for example, a concert by the same artist
- a large merit may be set.
- the number of regular customers can be increased and the satisfaction of high-quality customers can be increased.
- the ticket sales and the transition of the ticket fee may be sequentially presented to the user so that the transparency with respect to the change of the ticket fee may be improved.
- the feeling of unfairness particularly by core fans.
- the virtual seat can be recommended to each user by using the matching of the seat vector and the user vector as in the event in the real space, but there is a difference from the event in the real space.
- the seat vector of the virtual seat has a component (or metadata that is the basis of the seat vector) that is different from the seat vector of the actual seat.
- a component or metadata that is the basis of the seat vector
- the seat vector of the actual seat there are no concepts such as the audience around the seat, the seat environment (seat comfort), and the like, and it is not always necessary to include these elements in the seat vector.
- elements unique to virtual events may be included in the user vector.
- elements such as a position for viewing a virtual event (for example, a sofa in a living room, a train for commuting, etc.), a member (for example, one person, a family, a friend, a virtual acquaintance) to be viewed together are reflected in the user vector.
- user characteristics for example, loud voice, dancing, singing, etc.
- real space events can be reflected in the user vector.
- a seat that is not present in an event in a real space such as on the stage, directly above the stage, or directly below the stage.
- the virtual seat may be moved freely during the virtual event.
- the destination virtual seat can be recommended by the method described above.
- an additional fee may be collected when moving a virtual seat.
- the above-described contents can also be applied to live video distribution etc. in which virtual seats are also provided.
- live video distribution it is possible to enhance the sense of reality by reproducing the atmosphere around the seats in the actual venue corresponding to the virtual seats.
- step S101 and step S102 may be switched. That is, after selecting the target user by matching the seat vector and the user vector, the target user may be narrowed down by the intention of the organizer or the like.
- a seat vector may be calculated for each area and the seat may be recommended to the user for each area.
- the average value of the seat vectors of each seat in the area can be set as the seat vector of the area.
- the target event is seated at the target user. It is possible to recommend to.
- the processing in this case can be realized, for example, by executing the processing after step S152 in FIG. 11 for the combination of the target event and the target user.
- the ticket fee for each seat may be changed for each user according to the distance between the seat vector and the user vector. For example, the ticket fee may be set higher for a seat that is smaller for the user and suitable for the user, and the ticket fee is set for a seat that is larger for the user and not suitable for the user.
- a seat that is not suitable for the user with a large distance between the vectors may be clearly indicated for the reason, and the ticket fee may be discounted to be recommended to the user.
- a seat that a normal user tends to avoid can be sold to a user who is not particular about the seat, and the seat can be filled.
- a user who is not particular about the seat can obtain a ticket at a low price.
- the recommendation system 21 can also recommend an action plan before and after the event. In other words, not only recommending events and seats as described above, but also recommending a behavior plan around the event to the user by recommending actions before and after that, and places and seats suitable for those actions. Can be proposed.
- the input information includes user information of each user and condition information including conditions and hopes presented by each user.
- This condition information includes, for example, the desired date and time, the desired area, the type of event desired to participate, the number of people participating together, the atmosphere, and the like.
- the condition information includes, for example, the type of action desired before and after the event, the number of participants, the atmosphere, etc., the total budget for the day, and the total time. Note that the total time may be specified in a time zone, for example, from what time to what time.
- the condition information is not necessarily detailed information and may be rough information.
- the recommendation system 21 may select a part of the condition information or the information based on the information in the user profile DB 27 and the purchase history information DB 28, answers to previous questionnaires, or the like. You may make it guess all.
- event information related to each event and information on seats at the event venue are given as input information.
- information on candidate places to go before and after the event and information on seats at the candidate places are given as input information.
- candidate places to go before the event include salon systems (for example, hair salons, nail salons, esthetic salons, etc.), restaurants, and the like, and detailed information including information on seats at those places is given as input information. .
- behavior information of each user is given as input information.
- Each user's behavior information includes, for example, event ticket purchase history, access history (for example, history of sites including information on each event and sites accessed before and after the event), behavior before and after past events, and ticket purchases. Information indicating the relationship between the two is included.
- the recommendation system 21 analyzes the input information, for example, finds conditions for increasing the event participation rate and repeat rate of each user, and outputs the recommendation information provided to each user at an appropriate timing.
- the recommendation information includes, for example, a recommended event and an action plan before and after the event (for example, recommended facility, seat, clerk, etc.).
- the user uses the information presentation unit 22 to easily input desired conditions in a free format as shown in FIG.
- the desired date and time (from 12:00 to 23:00 on Saturday of this weekend), the desired area (Yokohama neighborhood), the type and atmosphere of the desired event (a musical that motivates after watching), the total budget ( Maximum 20,000 yen) is given as a condition.
- the desired place near the performance venue
- the desired action and the type of facility (salon)
- the hope for the clerk female staff of the same age. Theater lovers
- the desired seat ( The window side with a view) is given as a condition.
- the desired action and the type of facility restaurant
- the number of participants three female friends
- the hope for the store music or piano
- the desired seat half private room
- the recommendation system 21 recommends an event and an action plan before and after the event as shown in FIG.
- the preferred date and time, musicals held in the area and theater seats are recommended.
- a hair salon, nail salon, where there is a theater clerk who is close to the theater, has a good appreciation of theater and is good at talking, so that the mood before appreciation can be raised A bright window seat in the esthetic salon is recommended.
- a semi-private room seat where you can talk about the current situation while looking back at the drama watched by three women at a nearby restaurant & piano bar is recommended.
- the user is presented with an image related to the seat recommended in the event and the action plan before and after the event.
- the user is presented with an image showing the state of each salon recommended before appreciation of the musical and the recommended seats (seats where the facial mark in the image is displayed).
- the user is presented with an image showing a seating chart of a theater where a musical is held and a recommended seat (a seat on which a facial mark in the image is displayed).
- an image showing a seating chart of a restaurant recommended after appreciation of the musical and a recommended seat (a seat displaying a facial mark in the image) is presented to the user.
- the recommendation system 21 provides sales to an event organizer (for example, a box office etc.), a ticket seller, owners of each store to be recommended for action plans before and after the event, and the like. Strategic information for promotion can be output.
- This strategy information includes, for example, a method of providing event information, store information, and information on those seats to the user, information indicating the relationship between behavior before and after the event and ticket purchase (for example, event participation rate). (Reservation information for action plans with high costs).
- Action preference ranking update process before and after the event First, the action desire ranking update process before and after the event will be described with reference to the flowchart of FIG. This process is executed periodically, for example.
- step S201 the information analysis unit 55 identifies a combination of the category of the user who purchased or reserved the ticket within the predetermined period and the category of the event. Specifically, the information analysis unit 55 extracts the purchase history of each user from before the predetermined period to the present time from the purchase history information DB 28. And the information analysis part 55 specifies the combination of the user category of the user who purchased or reserved a ticket, and the event category of the event used as the object about all the purchase histories in the period.
- the information analysis unit 55 identifies the user category of each user based on the information in the user profile DB 27 and the information in the purchase history information DB 28.
- the user category is classified according to user attributes such as age group, gender, birthplace, educational history, and preference and behavior patterns based on the user purchase history. In the following, an example in which user categories are classified by combinations of age group and sex will be described.
- the information analysis unit 55 specifies the event category of each event according to the classification shown in FIG.
- the event category is classified into Japanese music, Western music, jazz, classical music, opera, theater and the like.
- the event category classification method is not limited to this example, and can be classified according to an arbitrary criterion.
- step S202 the information analysis unit 55 totals the action category and the atmosphere category desired by the user before the event for each combination of the event category and the user category.
- the information analysis unit 55 divides the category of the behavior and the atmosphere category desired by the user who purchased or reserved the ticket within the above-described period for each combination of the event category and the user category. Tally. This aggregation is performed based on information such as a questionnaire input by the user at the time of ticket purchase or reservation, for example.
- FIG. 22 shows an example of action category classification.
- the action category is classified into meal, karaoke, movie, salon, and the like.
- the meals are further classified according to the genre of a dish such as Japanese food, Western food, Chinese, Italian, ramen, cafe bar, or the like.
- the salon is classified according to the type of salon such as esthetic salon, nail salon, hair salon.
- the action category classification method is not limited to this example, and can be classified according to an arbitrary criterion.
- the atmosphere category is classified into atmospheres such as “Gayagaya”, “Slowly”, “Slowly”, and the like.
- the atmosphere category is not limited to this example, and can be classified according to any standard.
- step S203 the information analysis unit 55 aggregates the action category and the atmosphere category desired by the user after the event for each combination of the event category and the user category by the same processing as in step S202.
- step S204 the information analysis unit 55 updates the desired action ranking before and after the event based on the previous counting result.
- the action desired ranking is a ranking of combinations of action categories and atmosphere categories of actions that the user wants to perform before or after the event.
- FIG. 23 shows an example of an action preference ranking before and after an event when the event category is Japanese music and the user category is a male in their 30s.
- the combination of the action category “karaoke” and the atmosphere category “Yagaya” is ranked first in the action request ranking before the event. That is, it is shown that a man in his 30s who participates in a Japanese music event most desires to liven up with karaoke before the event, for example.
- the combination of the action category “Chinese” and the atmosphere category “carefully” is ranked first. That is, it is shown that a man in his 30s who participates in a Japanese music event most desires to enjoy a conversation while enjoying Chinese food after the event.
- the combination of “Western food” and “slowly” is 2nd
- the combination of “Japanese food” and “slow” is 3rd
- the combination of “Japanese food” and “slow” is 4th
- the combination of “ramen” and “slowly” Is in 5th place.
- a ranking for each event category or a ranking for each user category may be created.
- a ranking only for the action category or a ranking only for the atmosphere category may be created.
- the above-described categories and combinations thereof are examples thereof, and other categories and combinations of other categories may be used.
- This process is executed, for example, when the target user purchases or reserves a ticket for the target event, browses information about the target event, or recommends the target event to the target user. Alternatively, this process is executed, for example, at a predetermined timing (for example, immediately before the date of the target event or on the date of the target event) after the target user purchases or reserves a ticket for the target event.
- a predetermined timing for example, immediately before the date of the target event or on the date of the target event
- step S231 the recommendation unit 53 identifies a combination of the event category of the target event and the user category of the target user. Note that the classification of the event category and the user category is the same as in the above-described action desired ranking update process.
- step S232 the recommendation unit 53 acquires the pre-event action desired ranking corresponding to the combination of the identified event category and user category from the action plan DB 30. For example, if the target user is a male in their 30s and the target event is an artist belonging to the event category “Japanese music”, the pre-event action for the combination of the event category “Japanese music” and the user category “30s male” shown in FIG. The desired ranking is acquired.
- step S233 the recommendation unit 53 determines a combination of an action category and an atmosphere category used for recommendation. For example, when the condition is not specified by the target user, the recommendation unit 53 employs a combination of a higher action category and an atmosphere category in the pre-event action desired ranking acquired in the process of step S232. For example, the combination of the action category and the atmosphere category from the first place to the fifth place in the pre-event action desired ranking of FIG. 25 is employed.
- the recommendation unit 53 employs a combination of one or more action categories and atmosphere categories that satisfy the designated condition.
- step S234 the recommendation unit 53 extracts facilities and seats that are candidates for recommendation based on the determined combination of the action category and the atmosphere category. Specifically, the recommendation unit 53 extracts facilities and seats that are candidates for recommendation to the target user from the facility DB held by the action plan DB 30.
- FIG. 26 shows an example of the data structure of the facility DB.
- the facility DB holds information regarding facilities (for example, shops, entertainment facilities, public facilities, etc.) that can be used in an action plan that can be recommended to the target user.
- the facility DB includes at least four items of facility name, action category, seat type, and atmosphere category.
- Facility name indicates the name of each facility. For example, in the case of a store name, up to a branch name is registered.
- the action category indicates a category of actions that can be performed at each facility, and one or more of the action categories described above with reference to FIG. 22 are set.
- Seat type indicates the type of seat that each facility has.
- the seat types are classified into counter seats, table seats, private rooms, semi-private rooms, window seats, smoking seats, and non-smoking seats.
- the atmosphere category indicates a category representing the atmosphere of each seat type of each facility, and one or more of the above-described atmosphere categories are set. For example, in a salon where you can make noise, the atmosphere category “Yagaya” is set, and a quiet seat where you can talk carefully is set in the atmosphere category “Slow”. Atmosphere category is set to “slow”.
- a facility “AAA cafe Yokohama store” whose behavior category belongs to “cafe bar” and a facility “sushi BBB Yokohama store” whose behavior category belongs to “Japanese food” are registered.
- the “AAA cafe” includes counter seats belonging to the atmosphere category “Yagaya”, table seats belonging to the atmosphere category “carefully”, and table window side seats belonging to the atmosphere category “carefully”.
- “Sushi BBB” has a table seat belonging to the atmosphere category “carefully” and a private room belonging to the atmosphere category “slow”.
- facility information such as address, telephone number, e-mail address, business hours, fee, menu, access method, etc.
- information such as reservation status, facility and employee atmosphere and characteristics, etc. are stored in the facility DB. You may make it register. In addition, you may make it acquire such information from the website etc. of each facility, without registering in facility DB.
- the atmosphere and characteristics of facilities and employees should be collected not only from information provided by the facility, but also from articles posted on websites, social media, etc., user reviews and ratings, etc. May be.
- the recommendation unit 53 extracts a facility and a seat corresponding to the combination condition of the action category and the atmosphere category determined in the process of step S233 from the facility DB. For example, when the combination of the action category “cafe bar” and the atmosphere category “Yagaya” is given as a condition, the counter seat of the AAA cafe Yokohama store is extracted from the facility DB of FIG.
- the recommendation unit 53 further extracts a facility and a seat that satisfy a condition specified by the target user from the extracted facilities and seats.
- the facilities and seats that are in the area designated by the user and can be reserved at the designated date and time are extracted.
- the facility having the designated seat type is extracted.
- a facility having the designated feature or a facility having an employee having the designated feature is extracted.
- step S235 the recommendation unit 53 narrows down the recommended facilities and seats based on the conditions presented by the organizer of the target event, the owner of the facility, and the like.
- the conditions presented by the organizer of the target event, the owner of the facility, etc. are, for example, the priority of the recommended facility or seat.
- a facility and a seat set with high priority are preferentially selected from the facilities and seats extracted in the process of step S234.
- the priority of that facility is set high.
- the priority of the facility is set high when a facility that contributes to an increase in the participation rate of an event is found by analyzing the reservation information of each past facility and the purchase history data of the event ticket, the priority of the facility is set high.
- the A facility that contributes to an increase in the participation rate of an event is, for example, a facility where the user who reserved the facility has a high probability of participating in the event, a facility where the event participant has a high reservation rate before the event, or the like.
- step S236 the information processing system 11 recommends a pre-event action plan to the target user.
- the presentation control unit 56 generates pre-event action plan information for recommending a pre-event action plan to the target user.
- the pre-event action plan information includes, for example, information such as a facility recommended for the target user, a seat, and a reservationable time. Then, the presentation control unit 56 transmits the generated pre-event action plan information to the information presentation unit 22 used by the target user.
- the information presentation unit 22 presents information related to the recommended action plan to the target user based on the received pre-event action plan information.
- a method for presenting information any method can be adopted as in the case of recommending an event and a seat in step S104 in FIG. 6 described above.
- FIG. 27 shows an example of information presented in the information presentation unit 22 of the target user at this time.
- a recommended plan before the target event a list of recommended facility names (store names), seat types, and reservationable times is displayed in the order of recommendation.
- discount information when participating in the target event for example, 20% discount for those who participated in the target event
- This can be expected to improve both the participation rate of the target event and the reservation rate for the presented action plan.
- This process is executed, for example, when the target user purchases or reserves a ticket for the target event, browses information about the target event, or recommends the target event to the target user. Alternatively, this process is executed, for example, at a predetermined timing (for example, immediately before the date of the target event or on the date of the target event) after the target user purchases or reserves a ticket for the target event.
- a predetermined timing for example, immediately before the date of the target event or on the date of the target event
- step S261 the combination of the event category of the target event and the user category of the target user is specified as in the process of step S231 of FIG.
- step S262 the recommendation unit 53 acquires a post-event action desired ranking corresponding to the combination of the identified event category and user category from the action plan DB 30. For example, if the target user is a male in their 30s and the target event is an artist belonging to the event category “Japanese music”, the post-event behavior for the combination of the event category “Japanese music” and the user category “30s male” shown in FIG. The desired ranking is acquired.
- step S263 similar to the processing in step S233 of FIG. 24, the combination of the action category and the atmosphere category used for recommendation is determined.
- step S264 similar to the process in step S234 of FIG. 24, based on the determined combination of the action category and the atmosphere category, facilities and seats that are candidates for recommendation are extracted.
- step S265 similar to the processing in step S235 of FIG. 24, the recommended facilities and seats are narrowed down based on the conditions presented by the organizer of the target event, the owner of the facility, and the like.
- step S266 the action plan after the event is recommended to the target user as in the process of step S236 in FIG.
- FIG. 30 is a diagram similar to FIG. 27, and shows an example of information presented to the information presentation unit 22 of the target user at this time.
- the facilities are the same, if the seat types are different, they are presented as different plans.
- events suitable for each user and actions before and after the event can be recommended as a total plan.
- a user's willingness to participate in an event can be raised and the purchase rate of a ticket can be raised.
- the utilization rate of recommended facilities will be improved.
- the user can easily find and reserve an action plan that suits his / her conditions and preferences. Further, the user can spend not only the event but also the time until the event starts and the time after the event ends, and the overall satisfaction increases. As a result, the willingness to participate in the event increases, and the repeat rate can be increased.
- the action plans before and after the event may be recommended together with the target event, or may be recommended at a timing different from the target event. Further, when recommending together with the target event, only one of the action plan before the event or the action plan after the event may be recommended. Furthermore, after the target user purchases or reserves a ticket for the target event, it is possible to recommend an action plan before or after the target event.
- the content of the recommended action plan may be changed according to the recommended time. For example, when recommending on the day of the target event, add conditions such as weather and temperature on the day to change the action category or atmosphere category used for recommendation, or change the area range of the recommended facility It is possible.
- the action plan after the target event can be recommended before the target event is held, during the target event, or at the timing after the end of the target event, but the mood of the target user changes at each timing Is assumed. Therefore, assuming such a mood change, for example, the action category or the atmosphere category used for recommendation may be changed according to the timing of recommendation.
- the mood of the target user at that time depends on the status of the target event that has participated.
- the status of the target event includes, for example, whether or not the target event has risen, whether or not the target event has been prolonged or ended early, and whether or not the supporting team has won if the target event is a sports event. Therefore, for example, the action category or the atmosphere category used for recommendation may be changed according to the situation of the target event.
- an action plan that includes not only a single action but also two or more actions that change in time.
- an action plan including a restaurant seat to eat after the target event and a karaoke seat to go after the meal.
- the recommended action plan is not necessarily limited to the action plan immediately before or after the target event.
- the recommended action plan is not necessarily the same day as the target event. For example, for a user who participates in a target event from a distance, a hotel room or restaurant seat that stays the day before the target event may be recommended, or a restaurant seat the day after the target event may be recommended. Is possible.
- the action desired ranking before and after the event may be updated based on the reservation status of the action plan before and after the actual event of each user.
- a desired behavior ranking may be created for each user. For example, it is possible to create or update an action desire ranking for each user based on a user's preliminary questionnaire, user's preference information, user's comments on social media, and the like. Further, for example, based on the history of the action plan actually reserved by the user, the action desired ranking of each user may be updated. And it becomes possible to recommend the action plan more suitable for each user by using the action desired ranking for every user.
- a service that links the target event and the action plan may be provided in a facility that is used in the action plan.
- a service such as providing discounts to event participants at a restaurant that uses a recommended action plan for a special dish that appears in a theater or movie that is the target event is assumed.
- event organizers can use the recommendation system 21 to set and implement event ticket sales strategies for each seat and make changes as appropriate according to the sales situation. it can.
- This process is started when, for example, the host of the target event inputs a sales strategy setting command using the information presentation unit 23. Further, this process is executed, for example, until the ticket sales of the target event are completed.
- step S301 the information processing system 11 sets a sales strategy.
- the information presentation unit 23 transmits a sales strategy setting command input by the organizer or the like to the recommendation system 21.
- the sales strategy setting unit 54 of the recommendation system 21 generates sales strategy information based on the received command and stores it in the organizer profile DB 29.
- This sales strategy information includes, for example, information indicating the timing of executing the sales strategy and the sales strategy table shown in FIG.
- the sales strategy table includes, for example, items of seat number, priority, sales strategy (default), sales strategy (when canceled), and sales strategy (when empty).
- the seat number indicates the seat number of each seat at the target event venue.
- the priority indicates the priority for selling each seat, and is set to a value of “priority” or “normal”, for example.
- a seat whose priority is set to “priority” (hereinafter referred to as priority sales seat) is sold in preference to a seat that is set to “normal” (hereinafter referred to as normal sales seat).
- priority sales seat a seat whose priority is set to “priority”
- normal sales seat a seat that is set to “normal”
- the priority sales seat is recommended in preference to the normal sales seat.
- priorities may be classified into three or more levels.
- Sales strategy (default), sales strategy (when canceled), and sales strategy (when seats are empty) indicate the sales strategy applied to each seat.
- the sales strategy (default) indicates a sales strategy that is normally executed.
- the sales strategy (at the time of cancellation) indicates a sales strategy executed when a cancellation occurs.
- the sales strategy (at the time of vacant seats) is, for example, a sales strategy that can be set when a seat is vacant even after the set time limit.
- the sales strategy is set from, for example, four types of “invitation”, “attraction (discount)”, “swap”, and “normal”.
- a seat whose sales strategy is set to “attract” (hereinafter referred to as “attracting seat”) is, for example, a target recommended to the user in the event recommendation process described above.
- a seat whose sales strategy is set to “attract (discount)” (hereinafter referred to as “attract discount seat”) is, for example, a target recommended for the user in the event recommendation process described above, and a ticket price discount target. Become.
- a seat whose sales strategy is set to “swap” (hereinafter referred to as “swap seat”) is, for example, a seat that is exchanged from a purchased seat for a user who has already purchased a ticket in the event recommendation process described above. As a target to be recommended.
- a seat whose sales strategy is set to “normal” (hereinafter referred to as a normal strategy seat) is not a target to be recommended to a user in an event recommendation process, for example.
- the priority is set to “priority”
- the sales strategy (default) is set to “attract”
- the sales strategy (when canceling) is set to “swap”
- the sales strategy (When seats are empty) is set to “Attract”.
- the priority is set to “normal”
- the sales strategy (default) is set to “normal”
- the sales strategy (at the time of cancellation) is set to “invite”
- the sales strategy (when vacant) is set to “Attract (discount)”.
- step S302 the recommendation unit 53 determines whether it is time to execute the sales strategy. If it is determined that it is time to execute the sales strategy, the process proceeds to step S303.
- step S303 the recommendation unit 53 sets all the seats of the target event as targets for executing the sales strategy.
- step S304 the recommendation unit 53 executes a sales strategy execution process, and then the process proceeds to step S305.
- the details of the sales strategy execution processing will be described with reference to FIG.
- step S331 the recommendation unit 53 selects a target seat that is a target for setting the implementation details of the sales strategy. That is, the recommendation unit 53 selects one seat that has not yet been set as the sales strategy execution contents from among the seats that are the target of the sales strategy, and sets the selected seat as the target seat.
- step S332 the recommendation unit 53 determines whether the target seat is an empty seat. If it is determined that the target seat is vacant, the process proceeds to step S333.
- step S333 the recommendation unit 53 determines whether cancellation of the target seat has occurred. If it is determined that the target seat has been canceled, the process proceeds to step S334.
- step S334 the recommendation unit 53 sets the sales strategy for the target seat to the sales strategy at the time of cancellation based on the sales strategy table of the target event.
- step S333 determines whether the target seat has been canceled. If it is determined in step S333 that the target seat has not been canceled, the process proceeds to step S335.
- step S335 the recommendation unit 53 determines whether or not the target seat remains empty even if the target seat expires. When the time limit set in the sales strategy for the vacant seat at the current time has passed, the recommendation unit 53 determines that the target seat remains vacant even after the time limit has passed, and the process proceeds to step S336. .
- step S336 the recommendation unit 53 sets the sales strategy for the target seat to the sales strategy for cancellation based on the sales strategy table for the target event.
- step S335 determines whether the time limit set in the sales strategy when the target seat is vacant has not yet passed. If it is determined in step S335 that the time limit set in the sales strategy when the target seat is vacant has not yet passed, the process proceeds to step S337.
- step S337 the recommendation unit 53 sets the sales strategy for the target seat to the default sales strategy based on the sales strategy table for the target event.
- step S332 determines whether the target seat is vacant. If it is determined in step S332 that the target seat is not vacant, the processing in steps S333 to S337 is skipped, and the processing proceeds to step S338. In other words, the target seat is already filled, so no sales strategy is set.
- step S338 the recommendation unit 53 determines whether or not processing has been performed for all seats to be subjected to the sales strategy. If it is determined that not all the seats for which the sales strategy is to be implemented have been processed, the process returns to step S331.
- steps S331 to S338 are repeatedly executed until it is determined in step S338 that all seats to be subjected to the sales strategy have been processed.
- the implementation details of the sales strategy are set for all vacant seats included in the seats set as targets for the sales strategy.
- step S338 determines whether all seats to be subjected to the sales strategy have been processed. If it is determined in step S338 that all seats to be subjected to the sales strategy have been processed, the process proceeds to step S339.
- step S339 the push type event recommendation process described above with reference to FIG. 6 is executed.
- a seat set as an invitation seat and an invitation discount seat is recommended together with the target event to a user having a feature that matches the feature of the seat.
- a seat set as a swap seat is recommended to a user who has characteristics that match the characteristics of the seat and has already purchased another seat.
- step S302 if it is determined in step S302 that it is not time to execute the sales strategy, the processes in steps S303 and S304 are skipped, and the process proceeds to step S305.
- step S305 the sales strategy setting unit 54 determines whether or not a change in the sales strategy has been commanded. If it is determined that the sales strategy change is not instructed, the process returns to step S302. Thereafter, the processes in steps S302 to S305 are repeatedly executed until it is determined in step S305 that a change in sales strategy has been commanded.
- step S305 for example, when the sales strategy setting unit 54 receives a sales strategy change command input by the organizer or the like from the information presentation unit 23, the sales strategy setting unit 54 determines that a sales strategy change command has been issued, Advances to step S306.
- step S306 the information processing system 11 executes a sales strategy change process.
- the details of the sales strategy change process will be described with reference to FIG.
- step S361 the information processing system 11 presents the transition of the ticket sales status. Specifically, the information analysis unit 55 totals the sales status of the ticket of the target event based on the purchase history information held in the purchase history information DB 28. For example, the information analysis unit 55 totals the number of tickets sold for the target event for each day.
- the presentation control unit 56 generates ticket sales status information for presenting the transition of the sales status of the ticket of the target event based on the counting result by the information analysis unit 55, and transmits the ticket sales status information to the information presentation unit 23.
- the information presentation unit 23 presents the transition of the ticket sales status of the target event based on the received ticket sales status information.
- step S362 the information processing system 11 presents the sales situation of the passenger seat. Specifically, when the organizer or the like inputs a command for presenting the sales situation of the audience seat, the information presenting unit 23 transmits the command to the recommendation system 21.
- the information analysis unit 55 of the recommendation system 21 totals the sales status of the seats of the current target event based on the information stored in the customer seat sales status DB 26. For example, the information analysis unit 55 calculates whether each seat of the target event is full, vacant, or cancelled.
- the information analysis unit 55 collects information indicating the characteristics of the users assigned to the seats already buried from the user profile DB 27, and classifies the users into a plurality of types.
- the criteria for classifying the user type is specified by the organizer or the like. For example, the type of the user is classified based on at least one of a user attribute, a physical feature, a preference feature, and an event viewing feature.
- the presentation control unit 56 generates audience seat sales status information for presenting the sales status of the audience seats of the current target event based on the counting result of the information analysis unit 55, and transmits it to the information presentation unit 23.
- the information presentation unit 23 presents the sales situation of the audience seat of the target event based on the received audience sales situation information.
- FIG. 35 shows an example of a screen presented by the information presentation unit 23 in the processing of steps S361 and S362.
- a graph showing the transition of the number of tickets sold for each day of the target event from the ticket sales start date to the present is displayed.
- an image showing the current sales status of the seats will pop up.
- a diagram schematically showing the arrangement of the stage and the audience seats is displayed, and the seats are classified and displayed as seats where each seat is buried, vacant seats, and seats where cancellations have occurred.
- filled seats are indicated by diagonal lines, empty seats are painted white, and canceled seats are painted black.
- an image showing the current sales status of the seats can be automatically displayed in a pop-up when the seats are canceled.
- seats that are already filled may be displayed separately by color classification or the like for each type of user assigned to each seat.
- the user may be displayed by distinguishing between a user who is a good rider and an adult user, a man and a woman, and an age group.
- organizers can easily check the distribution of seats by audience type. For example, in order to excite the event, it is possible to develop a strategy such as which type of user should be attracted to which seat. it can.
- step S363 the information processing system 11 changes the sales strategy. Specifically, for example, the organizer or the like designates a seat whose sales strategy is to be changed, and inputs a command to change the sales strategy of the designated seat to the information presentation unit 23.
- the information presentation unit 23 transmits the input command to the recommendation system 21.
- the sales strategy setting unit 54 of the recommendation system 21 changes the sales strategy of the designated seat in the sales strategy table of the target event held in the organizer profile DB 29 based on the received command. At this time, the sales strategy for a plurality of seats can be changed together.
- step S307 the recommendation unit 53 sets a seat whose sales strategy has been changed as a target for implementing the sales strategy.
- step S308 sales strategy execution processing is executed in the same manner as in step S304. That is, the changed sales strategy is executed for the seats whose sales strategy has been changed.
- step S302 Thereafter, the process returns to step S302, and the processes after step S302 are executed.
- organizers can easily set and implement a sales strategy for each seat.
- the organizer can change the sales strategy of each seat in real time while checking the sales status of tickets and seats. For example, when the sales of tickets are not good, the number of invitation seats and invitation discount seats can be increased, and the user can be actively invited to the target event by means such as mail distribution. Further, for example, when a cancellation occurs just before the event is held, it is possible to attract a user who has already purchased a ticket to a better seat.
- the recommendation system 21 can present the transition of the sales situation of tickets and seats in more detail when presenting in the sales strategy change process described above, and can support analysis of factors such as ticket sales fluctuation factors.
- an instruction for presenting the sales status transition of the target event is input to the information presentation unit 23 by the organizer of the target event that is the target of presenting the sales status transition, and the command is displayed as the information presentation. It is started when it is transmitted from the unit 23 to the recommendation system 21.
- step S401 the information processing system 11 presents the transition of the ticket sales status along with the events related to the target event. Specifically, the information analysis unit 55 aggregates the sales status of the ticket of the target event by the same process as step S361 in FIG.
- the presentation control unit 56 collects information from the organizer profile DB 29 regarding events that may affect the sales of tickets among events related to the target event. For example, the presentation control unit 56 collects information on the ticket sales movement, the promotion movement, the movement of the performer of the target event, and the like from the organizer profile DB 29.
- the presentation control unit 56 generates ticket sales status information for presenting the transition of the ticket sales status together with the events related to the target event, based on the aggregation result of the information analysis unit 55 and the information collected by the presentation control unit 56 itself. To the information presentation unit 23. Based on the received ticket sales status information, the information presentation unit 23 presents the transition of the ticket sales status along with the events related to the target event.
- step S402 the information processing system 11 presents the sales situation of the seats on the designated day. Specifically, when the date on which the sales situation of the audience seat is designated by the organizer, the information presentation unit 23 transmits information indicating the designated date to the recommendation system 21.
- the information analysis unit 55 of the recommendation system 21 totals the sales situation of the audience seats of the target event on the specified day by the same process as step S362 in FIG.
- the presentation control unit 56 generates audience seat sales status information for presenting the sales status of the audience seat of the target event on the specified day based on the counting result of the information analysis unit 55, and transmits it to the information presentation unit 23.
- the information presenting unit 23 presents the sales situation of the audience seat of the target event on the specified day based on the received audience sales situation information.
- FIG. 37 shows an example of a screen presented by the information presentation unit 23 in this process.
- a graph showing the transition of the number of tickets sold for each day of the target event from the ticket sales start date to the present is displayed.
- events related to the target event (“newspaper advertisement”, “artist hospitalization”, invitation mail distribution) are displayed. It is possible to easily confirm the event that affected the event.
- the distance between the seat vector of the facility seat used in the recommended action plan and the user vector of the user is obtained by the same process as when recommending the event. Based on this, a recommended seat may be selected.
- the compatibility with the spectators of the surrounding seats may be obtained by using the user vector, and the seats in the vicinity of the spectators with good compatibility may be recommended.
- the compatible audiences are, for example, audiences with similar preferences, audiences with similar ways of viewing events, and the like. Thereby, for example, there is a high possibility that a good communication with the surrounding audience can be established or a sense of unity can be experienced through the event.
- a group of men and women of the same number who seems to meet their preferences in a predetermined area (one or multiple locations) in the venue may be arranged, and a plan such as an encounter party through an event. It is also possible to implement. Then, an action plan after the event may be recommended to the groups by the above-described processing so that communication between the groups can be deepened.
- the recommended combination of the seat and the user is selected based on the distance between the seat vector of the seat and the user vector of the user by the above-described method. can do.
- the series of processes described above can be executed by hardware or can be executed by software.
- a program constituting the software is installed in the computer.
- the computer includes, for example, a general-purpose personal computer capable of executing various functions by installing various programs by installing a computer incorporated in dedicated hardware.
- FIG. 38 is a block diagram showing an example of the hardware configuration of a computer that executes the above-described series of processing by a program.
- a CPU Central Processing Unit
- ROM Read Only Memory
- RAM Random Access Memory
- an input / output interface 405 is connected to the bus 404.
- An input unit 406, an output unit 407, a storage unit 408, a communication unit 409, and a drive 410 are connected to the input / output interface 405.
- the input unit 406 includes a keyboard, a mouse, a microphone, and the like.
- the output unit 407 includes a display, a speaker, and the like.
- the storage unit 408 includes a hard disk, a nonvolatile memory, and the like.
- the communication unit 409 includes a network interface.
- the drive 410 drives a removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory.
- the CPU 401 loads, for example, a program stored in the storage unit 408 to the RAM 403 via the input / output interface 405 and the bus 404 and executes the program, and the series described above. Is performed.
- the program executed by the computer (CPU 401) can be provided by being recorded on a removable medium 411 as a package medium, for example.
- the program can be provided via a wired or wireless transmission medium such as a local area network, the Internet, or digital satellite broadcasting.
- the program can be installed in the storage unit 408 via the input / output interface 405 by attaching the removable medium 411 to the drive 410.
- the program can be received by the communication unit 409 via a wired or wireless transmission medium and installed in the storage unit 408.
- the program can be installed in the ROM 402 or the storage unit 408 in advance.
- the program executed by the computer may be a program that is processed in time series in the order described in this specification, or in parallel or at a necessary timing such as when a call is made. It may be a program for processing.
- the system means a set of a plurality of components (devices, modules (parts), etc.), and it does not matter whether all the components are in the same housing. Accordingly, a plurality of devices housed in separate housings and connected via a network and a single device housing a plurality of modules in one housing are all systems. .
- the present technology can take a cloud computing configuration in which one function is shared by a plurality of devices via a network and is jointly processed.
- each step described in the above flowchart can be executed by one device or can be shared by a plurality of devices.
- the plurality of processes included in the one step can be executed by being shared by a plurality of apparatuses in addition to being executed by one apparatus.
- the present technology can take the following configurations.
- An information processing apparatus comprising: a recommendation unit that matches a feature of a seat or area assigned to a user in an event with a feature of the user and selects a combination of the recommended seat or area and the user.
- the recommendation unit selects a combination of a recommended seat or area and a user based on a distance between a seat vector which is a vector representing a seat or area feature and a user vector which is a vector representing a user feature.
- the information processing apparatus according to (1).
- the information processing apparatus according to (2) further including a presentation control unit that controls the information.
- the recommendation unit has a seat vector that has a seat vector smaller than the first seat or area for a user to whom a first seat or area is assigned.
- the information processing apparatus according to (2) or (3) wherein a seat or an area is recommended.
- a seat vector generation unit that generates the seat vector of each seat or area based on metadata about each seat or area;
- the screen simulates the appearance of the event area, which is the area where the event is held in the event venue, from the seat or area recommended to the user, and the surroundings of the seat or area recommended to the user
- the information processing apparatus according to (6).
- the seat or area features include user features that are preferentially assigned to the seat or area
- the recommendation unit selects a recommended seat or area and user combination based on the user characteristics and the user characteristics preferentially assigned to each seat or area. Any one of (1) to (7)
- the information processing apparatus described in 1. (9)
- the recommendation unit recommends facilities and seats used by the target user before the event or after the event based on a combination of the category to which the event belongs and the category to which the target user to be recommended belongs.
- the feature of the seat or area is a feature related to how the event area is an area where the event is performed in the event venue from the seat or area, a feature related to how sound is heard in the seat or area, Including at least one of a feature related to the audience around the seat or area, a feature related to the environment of the seat or area, and a feature of the user assigned in preference to the seat or area,
- the user's characteristics include at least one of the user's attributes, the user's physical characteristics, characteristics of the user's preferences, and characteristics of the user's view of the event (1) to (9)
- the information processing apparatus according to any one of the above.
- the event audience is classified into a plurality of types based on at least one of audience attributes, audience physical characteristics, audience preference characteristics, and audience event viewing characteristics.
- a sales strategy setting unit capable of setting a sales strategy indicating whether or not to make a recommendation to the user for each seat or area of the event;
- the information processing apparatus according to any one of (1) to (11), wherein the recommendation unit recommends a seat or an area that is set to recommend to a user.
- the said sales strategy setting part can set the said sales strategy different in the case where cancellation occurs, the case where it is vacant even after a predetermined time limit, and the case other than that, Information according to (12) Processing equipment.
- the recommendation unit further sets a fee for the event and a privilege for the event participant, and recommends a seat or area to be recommended, the fee, and the privilege based on the user's preference for the event.
- the information processing apparatus according to any one of (1) to (13), wherein the content of the combination is adjusted.
- the recommendation unit recommends a virtual seat or area that determines how an event area that is an area in which the event is performed in the video when the event is an event for delivering a video to a user's environment.
- the information processing apparatus according to any one of (1) to (14).
- An information processing method for an information processing apparatus including a recommendation step of matching a feature of a seat or area allocated to a user in an event with a feature of the user and selecting a combination of the recommended seat or area and the user.
- a program for causing a computer to execute a process including a recommendation step of matching a feature of a seat or area assigned to a user in an event with a feature of the user and selecting a combination of the recommended seat or area and the user.
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Abstract
Description
1.実施の形態
2.変形例
[情報処理システム11の構成例]
図1は、本技術を適用した情報処理システム11の一実施の形態を示すブロック図である。
図3は、推薦システム21の機能の構成例を示すブロック図である。推薦システム21は、席ベクトル生成部51、ユーザベクトル生成部52、推薦部53、販売戦略設定部54、情報分析部55、及び、提示制御部56を含むように構成される。
次に、図4乃至図16を参照して、情報処理システム11により実行されるイベント及び席の推薦処理について説明する。なお、以下、処理の対象となるイベントを対象イベントと称し、処理の対象となるユーザを対象ユーザと称する。
まず、図4のフローチャートを参照して、推薦システム21により実行される席ベクトル生成処理について説明する。
次に、図5のフローチャートを参照して、推薦システム21により実行されるユーザベクトル生成処理について説明する。
次に、図6のフローチャートを参照して、情報処理システム11により実行されるプッシュ型のイベント推薦処理について説明する。なお、この処理は、例えば、対象イベントに対するプッシュ型のプロモーションを行う場合に実行される。
次に、図11のフローチャートを参照して、情報処理システム11により実行されるプル型のイベント推薦処理について説明する。
上述した図6及び図11のイベント推薦処理においては、チケット料金及び特典の設定を行う例を示した。このチケット料金及び特典の設定は、主に販売促進を目的にして行われるものであり、例えば、イベントの開催直前までチケットが売れ残っている場合等に、チケット料金の割引や特典の付与が行われる。
仮想イベントにおいても、現実空間のイベントと同様に、席ベクトルとユーザベクトルのマッチングを用いて、各ユーザに仮想席の推薦を行うことができるが、現実空間のイベントと異なる点がある。
ここで、上述したイベント及び席の推薦処理の変形例について説明する。
次に、図17乃至図30を参照して、イベント前後の行動プランを推薦する場合の処理について説明する。
ここで、まず、図17乃至図19を参照して、イベント及びイベント前後の行動プランの推薦処理の概要について説明する。
まず、図20のフローチャートを参照して、イベント前後の行動希望ランキング更新処理について説明する。なお、この処理は、例えば、定期的に実行される。
次に、図24のフローチャートを参照して、情報処理システム11により実行されるイベント前行動プラン推薦処理について説明する。
次に、図28のフローチャートを参照して、情報処理システム11により実行されるイベント後行動プラン推薦処理について説明する。
ここで、上述したイベント前後の行動プランの推薦処理の変形例について説明する。
次に、図31乃至図37を参照して、販売戦略に関する処理について説明する。
ここで、図31のフローチャートを参照して、情報処理システム11により実行される販売戦略処理について説明する。
また、推薦システム21は、チケット及び席の販売状況の推移を、上述した販売戦略変更処理で提示するときより詳細に提示し、チケットの売れ行きの変動要因等の分析を支援することができる。
以下、上述した以外の本技術の実施の形態の変形例について説明する。
上述した一連の処理は、ハードウエアにより実行することもできるし、ソフトウエアにより実行することもできる。一連の処理をソフトウエアにより実行する場合には、そのソフトウエアを構成するプログラムが、コンピュータにインストールされる。ここで、コンピュータには、専用のハードウエアに組み込まれているコンピュータや、各種のプログラムをインストールすることで、各種の機能を実行することが可能な、例えば汎用のパーソナルコンピュータなどが含まれる。
イベントにおいてユーザに割り当てられる席又はエリアの特徴とユーザの特徴とのマッチングを行い、推薦する席又はエリアとユーザの組み合わせを選択する推薦部を
備える情報処理装置。
(2)
前記推薦部は、席又はエリアの特徴を表すベクトルである席ベクトルとユーザの特徴を表すベクトルであるユーザベクトルとの間の距離に基づいて、推薦する席又はエリアとユーザとの組み合わせを選択する
前記(1)に記載の情報処理装置。
(3)
前記イベントの席又はエリアの配置をユーザに提示する場合に、各席又はエリアの前記席ベクトルと前記ユーザの前記ユーザベクトルとの間の距離に基づいて、各席又はエリアを区別して提示するように制御する提示制御部を
さらに備える前記(2)に記載の情報処理装置。
(4)
前記推薦部は、第1の席又はエリアが割り当てられているユーザに対して、前記ユーザの前記ユーザベクトルとの間の距離が前記第1の席又はエリアより小さい前記席ベクトルを有する第2の席又はエリアを推薦する
前記(2)又は(3)に記載の情報処理装置。
(5)
各席又はエリアに関するメタデータに基づいて、各席又はエリアの前記席ベクトルを生成する席ベクトル生成部と、
各ユーザに関するメタデータに基づいて、各ユーザの前記ユーザベクトルを生成するユーザベクトル生成部と
をさらに備える前記(2)乃至(4)のいずれかに記載の情報処理装置。
(6)
ユーザに推薦する席又はエリアからの視界をシミュレートした画面の提示を制御する提示制御部を
さらに備える前記(1)、(2)、(4)又は(5)に記載の情報処理装置。
(7)
前記画面は、ユーザに推薦する席又はエリアからの前記イベントの会場内の前記イベントが行われる領域であるイベント領域の見え方、及び、ユーザに推薦する席又はエリアの周囲の様子をシミュレートしたものである
前記(6)に記載の情報処理装置。
(8)
前記席又はエリアの特徴は、当該席又はエリアに優先的に割り当てるユーザの特徴を含み、
前記推薦部は、ユーザの特徴、及び、各席又はエリアに優先的に割り当てるユーザの特徴に基づいて、推薦する席又はエリアとユーザの組み合わせを選択する
前記(1)乃至(7)のいずれかに記載の情報処理装置。
(9)
前記推薦部は、前記イベントの属するカテゴリと推薦を行う対象となる対象ユーザが属するカテゴリとの組み合わせに基づいて、前記イベントの前又は前記イベントの後に前記対象ユーザが利用する施設及び席の推薦をさらに行う
前記(1)乃至(8)のいずれかに記載の情報処理装置。
(10)
前記席又はエリアの特徴は、当該席又はエリアからの前記イベントの会場内の前記イベントが行われている領域であるイベント領域の見え方に関する特徴、当該席又はエリアにおける音の聴こえ方に関する特徴、当該席又はエリアの周囲の観客に関する特徴、当該席又はエリアの環境に関する特徴、及び、当該席又はエリアに優先して割り当てるユーザの特徴のうち少なくとも1つを含み、
前記ユーザの特徴は、当該ユーザの属性、当該ユーザの身体的特徴、当該ユーザの嗜好に関する特徴、及び、当該ユーザのイベントの見方に関する特徴のうち少なくとも1つを含む
前記(1)乃至(9)のいずれかに記載の情報処理装置。
(11)
観客の属性、観客の身体的特徴、観客の嗜好に関する特徴、及び、観客のイベントの見方に関する特徴のうち少なくとも1つに基づいて前記イベントの観客を複数のタイプに分類し、前記イベントの客席の観客の分布を前記タイプ毎に区別して提示するように制御する提示制御部を
さらに備える前記(10)に記載の情報処理装置。
(12)
ユーザへの推薦を行うか否かを示す販売戦略を前記イベントの席又はエリア毎に設定可能な販売戦略設定部を
さらに備え、
前記推薦部は、ユーザへの推薦を行うように設定されている席又はエリアの推薦を行う
前記(1)乃至(11)のいずれかに記載の情報処理装置。
(13)
前記販売戦略設定部は、キャンセルが発生した場合、所定の期限を過ぎても空席である場合、及び、それ以外の場合とで異なる前記販売戦略を設定可能である
前記(12)に記載の情報処理装置。
(14)
前記推薦部は、さらに前記イベントの料金及び前記イベントの参加者への特典の設定を行うとともに、前記イベントに対するユーザの嗜好度に基づいて、推薦する席又はエリア、前記料金、及び、前記特典の組み合わせの内容を調整する
前記(1)乃至(13)のいずれかに記載の情報処理装置。
(15)
前記推薦部は、前記イベントがユーザの環境に映像を配信するイベントの場合、前記映像内の前記イベントが行われる領域であるイベント領域の見え方を決める仮想的な席又はエリアの推薦を行う
前記(1)乃至(14)のいずれかに記載の情報処理装置。
(16)
イベントにおいてユーザに割り当てられる席又はエリアの特徴とユーザの特徴とのマッチングを行い、推薦する席又はエリアとユーザの組み合わせを選択する推薦ステップを
含む情報処理装置の情報処理方法。
(17)
イベントにおいてユーザに割り当てられる席又はエリアの特徴とユーザの特徴とのマッチングを行い、推薦する席又はエリアとユーザの組み合わせを選択する推薦ステップを
含む処理をコンピュータに実行させるためのプログラム。
Claims (17)
- イベントにおいてユーザに割り当てられる席又はエリアの特徴とユーザの特徴とのマッチングを行い、推薦する席又はエリアとユーザの組み合わせを選択する推薦部を
備える情報処理装置。 - 前記推薦部は、席又はエリアの特徴を表すベクトルである席ベクトルとユーザの特徴を表すベクトルであるユーザベクトルとの間の距離に基づいて、推薦する席又はエリアとユーザとの組み合わせを選択する
請求項1に記載の情報処理装置。 - 前記イベントの席又はエリアの配置をユーザに提示する場合に、各席又はエリアの前記席ベクトルと前記ユーザの前記ユーザベクトルとの間の距離に基づいて、各席又はエリアを区別して提示するように制御する提示制御部を
さらに備える請求項2に記載の情報処理装置。 - 前記推薦部は、第1の席又はエリアが割り当てられているユーザに対して、前記ユーザの前記ユーザベクトルとの間の距離が前記第1の席又はエリアより小さい前記席ベクトルを有する第2の席又はエリアを推薦する
請求項2に記載の情報処理装置。 - 各席又はエリアに関するメタデータに基づいて、各席又はエリアの前記席ベクトルを生成する席ベクトル生成部と、
各ユーザに関するメタデータに基づいて、各ユーザの前記ユーザベクトルを生成するユーザベクトル生成部と
をさらに備える請求項2に記載の情報処理装置。 - ユーザに推薦する席又はエリアからの視界をシミュレートした画像の提示を制御する提示制御部を
さらに備える請求項1に記載の情報処理装置。 - 前記画像は、ユーザに推薦する席又はエリアからの前記イベントの会場内の前記イベントが行われる領域であるイベント領域の見え方、及び、ユーザに推薦する席又はエリアの周囲の様子をシミュレートしたものである
請求項6に記載の情報処理装置。 - 前記席又はエリアの特徴は、当該席又はエリアに優先的に割り当てるユーザの特徴を含み、
前記推薦部は、ユーザの特徴、及び、各席又はエリアに優先的に割り当てるユーザの特徴に基づいて、推薦する席又はエリアとユーザの組み合わせを選択する
請求項1に記載の情報処理装置。 - 前記推薦部は、前記イベントの属するカテゴリと推薦を行う対象となる対象ユーザが属するカテゴリとの組み合わせに基づいて、前記イベントの前又は前記イベントの後に前記対象ユーザが利用する施設及び席の推薦をさらに行う
請求項1に記載の情報処理装置。 - 前記席又はエリアの特徴は、当該席又はエリアからの前記イベントの会場内の前記イベントが行われている領域であるイベント領域の見え方に関する特徴、当該席又はエリアにおける音の聴こえ方に関する特徴、当該席又はエリアの周囲の観客に関する特徴、当該席又はエリアの環境に関する特徴、及び、当該席又はエリアに優先して割り当てるユーザの特徴のうち少なくとも1つを含み、
前記ユーザの特徴は、当該ユーザの属性、当該ユーザの身体的特徴、当該ユーザの嗜好に関する特徴、及び、当該ユーザのイベントの見方に関する特徴のうち少なくとも1つを含む
請求項1に記載の情報処理装置。 - 観客の属性、観客の身体的特徴、観客の嗜好に関する特徴、及び、観客のイベントの見方に関する特徴のうち少なくとも1つに基づいて前記イベントの観客を複数のタイプに分類し、前記イベントの客席の観客の分布を前記タイプ毎に区別して提示するように制御する提示制御部を
さらに備える請求項10に記載の情報処理装置。 - ユーザへの推薦を行うか否かを示す販売戦略を前記イベントの席又はエリア毎に設定可能な販売戦略設定部を
さらに備え、
前記推薦部は、ユーザへの推薦を行うように設定されている席又はエリアの推薦を行う
請求項1に記載の情報処理装置。 - 前記販売戦略設定部は、キャンセルが発生した場合、所定の期限を過ぎても空席である場合、及び、それ以外の場合とで異なる前記販売戦略を設定可能である
請求項12に記載の情報処理装置。 - 前記推薦部は、さらに前記イベントの料金及び前記イベントの参加者への特典の設定を行うとともに、前記イベントに対するユーザの嗜好度に基づいて、推薦する席又はエリア、前記料金、及び、前記特典の組み合わせの内容を調整する
請求項1に記載の情報処理装置。 - 前記推薦部は、前記イベントがユーザの環境に映像を配信するイベントの場合、前記映像内の前記イベントが行われる領域であるイベント領域の見え方を決める仮想的な席又はエリアの推薦を行う
請求項1に記載の情報処理装置。 - イベントにおいてユーザに割り当てられる席又はエリアの特徴とユーザの特徴とのマッチングを行い、推薦する席又はエリアとユーザの組み合わせを選択する推薦ステップを
含む情報処理装置の情報処理方法。 - イベントにおいてユーザに割り当てられる席又はエリアの特徴とユーザの特徴とのマッチングを行い、推薦する席又はエリアとユーザの組み合わせを選択する推薦ステップを
含む処理をコンピュータに実行させるためのプログラム。
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Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH1125188A (ja) * | 1997-06-30 | 1999-01-29 | Masanobu Kujirada | 遠隔利用方法 |
JP2001236405A (ja) * | 2000-02-24 | 2001-08-31 | Sumisho Computer Systems Corp | 販売促進支援装置および方法、記録媒体 |
JP2002109336A (ja) * | 2000-07-24 | 2002-04-12 | Hiroko Matsuzawa | 座席予約システム及び座席確認システム |
JP2002197224A (ja) | 2000-12-25 | 2002-07-12 | Sony Corp | 電子チケット管理システム,電子チケット情報読み出し装置,電子チケットプラットフォームセンタ,情報記憶チップ,携帯装置,プログラム記憶媒体および電子チケット管理方法 |
JP2003296620A (ja) * | 2002-04-05 | 2003-10-17 | Japan Racing Association | インターネットを使用する指定席予約システム |
JP2004280643A (ja) * | 2003-03-18 | 2004-10-07 | Fuji Photo Film Co Ltd | 座席予約方法 |
JP2008027301A (ja) * | 2006-07-24 | 2008-02-07 | Nec System Technologies Ltd | 座席予約システム、座席予約装置、座席予約方法、及びプログラム |
JP2010176483A (ja) * | 2009-01-30 | 2010-08-12 | Nec Corp | サーバ、座席割当システム、通信端末、サーバの制御方法、座席予約方法、及びプログラム |
JP2011135183A (ja) | 2009-12-22 | 2011-07-07 | Sony Corp | 情報処理装置および方法 |
JP2012014518A (ja) * | 2010-07-01 | 2012-01-19 | Ntt Docomo Inc | コンテンツ間類似度算出装置及びコンテンツ間類似度算出方法 |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6023685A (en) * | 1996-05-23 | 2000-02-08 | Brett; Kenton F. | Computer controlled event ticket auctioning system |
AU2001297635A1 (en) * | 2000-10-31 | 2002-09-12 | Motorola Inc. | A method and apparatus for ticket reservation and payment |
JP3872307B2 (ja) * | 2001-03-21 | 2007-01-24 | インターナショナル・ビジネス・マシーンズ・コーポレーション | オークション方法、オークションシステムおよびプログラム |
JP2003108839A (ja) * | 2001-09-28 | 2003-04-11 | Matsushita Electric Ind Co Ltd | 利用状況情報処理装置、利用状況情報処理方法及び端末 |
-
2014
- 2014-07-22 US US14/895,150 patent/US20160125324A1/en not_active Abandoned
- 2014-07-22 JP JP2015529521A patent/JPWO2015016094A1/ja active Pending
- 2014-07-22 CN CN201480041565.2A patent/CN105474246A/zh active Pending
- 2014-07-22 EP EP14831723.3A patent/EP3029620A4/en not_active Withdrawn
- 2014-07-22 WO PCT/JP2014/069275 patent/WO2015016094A1/ja active Application Filing
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH1125188A (ja) * | 1997-06-30 | 1999-01-29 | Masanobu Kujirada | 遠隔利用方法 |
JP2001236405A (ja) * | 2000-02-24 | 2001-08-31 | Sumisho Computer Systems Corp | 販売促進支援装置および方法、記録媒体 |
JP2002109336A (ja) * | 2000-07-24 | 2002-04-12 | Hiroko Matsuzawa | 座席予約システム及び座席確認システム |
JP2002197224A (ja) | 2000-12-25 | 2002-07-12 | Sony Corp | 電子チケット管理システム,電子チケット情報読み出し装置,電子チケットプラットフォームセンタ,情報記憶チップ,携帯装置,プログラム記憶媒体および電子チケット管理方法 |
JP2003296620A (ja) * | 2002-04-05 | 2003-10-17 | Japan Racing Association | インターネットを使用する指定席予約システム |
JP2004280643A (ja) * | 2003-03-18 | 2004-10-07 | Fuji Photo Film Co Ltd | 座席予約方法 |
JP2008027301A (ja) * | 2006-07-24 | 2008-02-07 | Nec System Technologies Ltd | 座席予約システム、座席予約装置、座席予約方法、及びプログラム |
JP2010176483A (ja) * | 2009-01-30 | 2010-08-12 | Nec Corp | サーバ、座席割当システム、通信端末、サーバの制御方法、座席予約方法、及びプログラム |
JP2011135183A (ja) | 2009-12-22 | 2011-07-07 | Sony Corp | 情報処理装置および方法 |
JP2012014518A (ja) * | 2010-07-01 | 2012-01-19 | Ntt Docomo Inc | コンテンツ間類似度算出装置及びコンテンツ間類似度算出方法 |
Non-Patent Citations (2)
Title |
---|
See also references of EP3029620A4 * |
YUKA KATO: "A Recommender System Indicating Accurate and Subconscious Items for On-line Shopping", TRANSACTIONS OF INFORMATION PROCESSING SOCIETY OF JAPAN, vol. 46, no. SIG13T, 15 September 2005 (2005-09-15), pages 53 - 64, XP055312825 * |
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CN105474246A (zh) | 2016-04-06 |
EP3029620A4 (en) | 2017-04-12 |
US20160125324A1 (en) | 2016-05-05 |
JPWO2015016094A1 (ja) | 2017-03-02 |
EP3029620A1 (en) | 2016-06-08 |
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