JP2018081447A - Prediction device, prediction method, and prediction program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To appropriately predict a demand for a service which is provided in a predetermined facility.SOLUTION: A prediction device includes an acquisition unit and a prediction unit. The acquisition unit obtains web information collected in the web. The prediction unit predicts information on a demand for a service which is provided in a predetermined facility, on the basis of the web information obtained by the acquisition unit. For example, the prediction unit predicts information on a demand for a service which is provided in a predetermined facility located in a predetermined area.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a prediction device, a prediction method, and a prediction program.

  In recent years, with the rapid spread of the Internet, for example, a technology for reserving a service such as accommodation on an EC (Electronic Commerce) site has been provided. In addition, there is known a technique for ranking based on questionnaires collected on hotels that provide accommodation services.

Japanese Patent Laying-Open No. 2005-070991

  However, in the above-described conventional technology, it is not always possible to appropriately predict the demand for services provided in a predetermined facility. For example, it may be difficult to appropriately predict how much demand is in which service based only on a questionnaire result from a user.

  The present application has been made in view of the above, and an object thereof is to provide a prediction device, a prediction method, and a prediction program that appropriately predict the demand for services provided in a predetermined facility.

  The prediction device according to the present application predicts information related to demand for a service provided in a predetermined facility based on an acquisition unit that acquires web information collected on the web and the web information acquired by the acquisition unit. And a section.

  According to one aspect of the embodiment, there is an effect that it is possible to appropriately predict the demand for services provided in a predetermined facility.

FIG. 1 is a diagram illustrating an example of a prediction process according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of the providing apparatus according to the embodiment. FIG. 3 is a diagram illustrating an example of the accommodation facility information storage unit according to the embodiment. FIG. 4 is a diagram illustrating an example of a content information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of a regional information storage unit according to the embodiment. FIG. 6 is a diagram illustrating an example of an event information storage unit according to the embodiment. FIG. 7 is a flowchart illustrating an example of the prediction process according to the embodiment. FIG. 8 is a flowchart illustrating an example of determining information to be provided according to the embodiment. FIG. 9 is a diagram illustrating an example of price determination based on demand according to the embodiment. FIG. 10 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the providing apparatus.

  Hereinafter, modes for carrying out a prediction apparatus, a prediction method, and a prediction program according to the present application (hereinafter referred to as “embodiments”) will be described in detail with reference to the drawings. Note that the prediction device, the prediction method, and the prediction program according to the present application are not limited to the embodiment. In the following embodiments, the same portions are denoted by the same reference numerals, and redundant description is omitted.

(Embodiment)
[1. (Prediction process)
An example of the prediction process according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of a prediction process according to the embodiment. In the prediction process illustrated in FIG. 1, the providing device 100 predicts information related to the demand for services provided in a predetermined facility based on the web information. FIG. 1 shows a case where the predetermined facility is an accommodation facility such as a hotel (hereinafter also simply referred to as “hotel”) and the provided service is an accommodation service. In FIG. 1, the case where the price of each accommodation service is determined based on the demand which the provision apparatus 100 estimated is shown. FIG. 1 shows a case where the providing apparatus 100 provides a list (list information) of accommodation service contents corresponding to the date and area specified by the user. Here, the content includes information indicating the contents of the accommodation service provided at the hotel. The content may be advertisement information for accommodation services provided at hotels. Moreover, although the example of FIG. 1 shows the case where the evaluation regarding an accommodation service is calculated, as long as it is a service provided in a predetermined facility, it may be any service such as a restaurant service in a restaurant.

  As shown in FIG. 1, the providing system 1 includes a terminal device 10, an information providing device 50, and a providing device 100. The terminal device 10, the information providing device 50, and the providing device 100 are connected to be communicable by wire or wireless via a predetermined communication network (not shown). Further, the providing system 1 illustrated in FIG. 1 may include a plurality of terminal devices 10, a plurality of information providing devices 50, and a plurality of providing devices 100.

  The terminal device 10 is an information processing device used by a user. The terminal device 10 is realized by, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. In the example shown in FIG. 1, the case where the terminal device 10 is a smartphone used by the user is shown. Hereinafter, the terminal device 10 may be referred to as a user. That is, hereinafter, the user can be read as the terminal device 10. Specifically, FIG. 1 illustrates a case where the terminal device 10 is a smartphone used by a user identified by the user ID “U1” (hereinafter, may be referred to as “user U1”).

  In the example illustrated in FIG. 1, the terminal device 10 will be described as the terminal devices 10-1 and 10-2 according to the display of the screen of the terminal device 10. The terminal devices 10-1 and 10-2 are the same terminal device 10. Hereinafter, the terminal devices 10-1 and 10-2 will be referred to as the terminal device 10 when they are not particularly distinguished.

The information providing apparatus 50 is an information processing apparatus such as a web server in which various contents such as documents and images are stored. For example, the information providing apparatus 50 transmits web information to the providing apparatus 100 periodically such as every hour or every other day, or in response to a request from the providing apparatus 100. Here, the information acquired by the providing apparatus 100 from the information providing apparatus 50 may include various information such as a news page indicating that an event is held, a Web page provided by SNS, and the like. .

  The providing apparatus 100 is a prediction apparatus that predicts information related to demand for services provided in a predetermined facility based on web information. Further, the providing device 100 determines the price of each accommodation service based on the predicted demand. In addition, the providing device 100 provides an information providing service that provides the terminal device 10 with information on the hotel information request acquired from the terminal device 10. In the example of FIG. 1, the providing device 100 provides list information in which contents corresponding to services are arranged to the terminal device 10 that is the transmission source of the hotel information request. Further, in the example illustrated in FIG. 1, it is assumed that the providing device 100 provides an electronic commerce service related to reservation of an accommodation facility.

  FIG. 1 shows a case where the providing apparatus 100 provides an information providing service or an electronic commerce service. However, when an external information processing apparatus provides an information providing service or an electronic commerce service, the providing apparatus 100 uses the information providing service. And e-commerce services may not be provided. In this case, the providing apparatus 100 may acquire various types of information such as information on accommodation facilities and information on services from an external information processing apparatus that provides an information providing service or an electronic commerce service.

  First, the providing device 100 acquires event information from the information providing device 50 (step S11). In the example of FIG. 1, the providing device 100 acquires event information IV11 indicating that the idol A performs a concert on the X month Y at the X stadium from the information providing device 50. The providing apparatus 100 may acquire information indicating that the idol A performs a concert on X month Y at the X stadium by performing syntax analysis on the information acquired from the information providing apparatus 50.

  Then, the providing apparatus 100 adds the acquired event information IV11 to the event information storage unit 124 (Step S12). For example, the providing apparatus 100 adds event information IV11 indicating that the idol A performs a concert on the X month Y at the X stadium to the event information storage unit 124.

  In the example of FIG. 1, the providing apparatus 100 is held on the date “X month Y day” as the event information (event information IV11) identified by the event ID “IV11” or located in the region “A region”. Information indicating that the event is to be held at the venue “X Stadium” is added to the event information storage unit 124. In the example of FIG. 1, the providing apparatus 100 adds information indicating that the expected number of customers is “50,000” to the event information storage unit 124 as the event information IV11.

  The providing apparatus 100 may determine information such as that the venue “X Stadium” is located in the A area and that the expected number of customers is “50,000” by appropriately using various information. Good. For example, the providing apparatus 100 stores information regarding the association between each venue and the area in the storage unit 120 (see FIG. 2), and determines that the venue “X Stadium” is located in the A area by referring to the storage unit 120. May be. Further, for example, the providing apparatus 100 may determine that the number of customers expected based on the popularity of the idol A, the customer history of the idol A concert, and the like is “50,000”.

  Then, the providing apparatus 100 predicts the demand on the event date based on the acquired event information and information on the area where the event corresponding to the event information is held (step S13). For example, based on the event information IV11 indicating that the idol A will perform a concert on the X month Y on the X stadium and the information on the A region where the X stadium is located, the A region on the event date “X month Y day” Predict the hotel demand. In the example of FIG. 1, it is assumed that the value related to the demand for hotels in area A on the event date “X month Y day” is “50,000”. In the example of FIG. 1, the demand based on other factors is described as “0” in order to simplify the description.

  In the example of FIG. 1, the providing apparatus 100 predicts the demand for hotels in area A on the event date “X month Y day” using the area information stored in the area information storage unit 123.

  In the example of FIG. 1, the providing apparatus 100 stores the “total number of hotels accommodated” in each area as shown in the area information storage unit 123. Here, the “total number of hotels accommodated” indicates the number of people that can be accommodated in one day in all hotels in each region. For example, the area information storage unit 123 stores information relating to the fact that the total number of hotels per day in area A is “25,000”. Therefore, in the example of FIG. 1, it is assumed that the value related to the supply of hotels in the A area on the event date “X month Y day” is “25,000”.

  Accordingly, the providing apparatus 100 has a value “50,000” relating to the demand for hotels in the A area on the event date “X month Y day” and a value “related to the supply of hotels in the A area on the event date“ X month Y day ”. On the basis of “25,000”, a supply and demand index indicating the relationship between the demand and supply of hotels in area A on the event date “X month Y day” is predicted.

  The providing apparatus 100 predicts, as a supply and demand index, a value “2 (= 50000/25000)” obtained by dividing the value “50,000” related to the hotel demand by the value “25,000” related to the hotel supply. For example, when the supply and demand index is greater than 1, it indicates that there is room for price increase because demand exceeds supply. For example, when the supply and demand index is smaller than 1, it indicates that there is no room for price increase because demand is lower than supply and supply is excessive.

  As described above, in the example of FIG. 1, the providing apparatus 100 predicts the demand / supply index of the hotel in area A on the event date “X month / Y” as “2” as shown in the demand / supply information DF11. It is determined that the price of the hotel in area A on the date “X month Y day” is to be increased (step S14).

  In the example of FIG. 1, the providing apparatus 100 stores information about each hotel as shown in the accommodation facility information storage unit 121. For example, the accommodation facility information storage unit 121 stores information relating to the location of the hotel A in the A area.

  In the example of FIG. 1, the providing apparatus 100 stores information regarding content corresponding to the accommodation service provided by each hotel, as shown in the content information storage unit 122. For example, the content information storage unit 122 stores information such as the content CT11 corresponding to the service provided on the X month Y day at the hotel A. For example, the content information storage unit 122 includes a CTR (Click Through Ratio) indicating a click rate of each content, and an index (hereinafter referred to as “conversion rate”) related to an action that leads to a profit of a provider providing a service corresponding to each content. Also, an index value such as CVR (Conversion Rate) is stored.

  For example, the content information storage unit 122 stores the price of a service corresponding to each content. Further, for example, in the content information storage unit 122, the provider of the reservation service is provided when an action leading to the profit of the provider providing the service corresponding to the content via the content is performed. Indicates the percentage of commission received. For example, “fee” indicates a rate of a fee received by a reservation service provider when a service corresponding to the content is provided via the content. For example, when the service corresponding to the content is provided through the content, the providing apparatus 100 may charge the provider that provides the service an amount obtained by multiplying the service price by the fee. In the example of FIG. 1, for the sake of simplicity, the case where the fee associated with each content is “0.1”, that is, 10% is shown. May be associated.

  As described above, “content CT * (* is an arbitrary numerical value)” indicates that the content is content identified by the content ID “CT *”. For example, when “content CT11” is described, the content is the content identified by the content ID “CT11”.

  In the example of FIG. 1, the providing apparatus 100 determines a hotel to be priced, such as a hotel A or a hotel B located in the A area among the hotels stored in the accommodation facility information storage unit 121. In the example of FIG. 1, the providing apparatus 100 stores the price of the service provided on the X month Y day at the hotel A corresponding to the content CT11 or the content CT21 among the contents stored in the content information storage unit 122. It is determined that the price of the service provided on the X month Y at the corresponding hotel B and the price of the service provided on the X month Y at the hotel K corresponding to the content CT55 are increased.

  In the example of FIG. 1, the providing apparatus 100 predicts the demand / supply index of the hotel in the A area on the event date “X month Y day” as “2”, and therefore the hotel in the A area on the event date “X month Y day”. It is determined that the price will be increased by a factor of two based on the supply and demand index.

  As a result, in the example of FIG. 1, as shown in the content information storage unit 122, the price of the service provided on the X and Y days at the hotel A corresponding to the content CT11 increases from “5000 yen” to “10000 yen”. To do. In the example of FIG. 1, as shown in the content information storage unit 122, the price of the service provided on the X month Y day at the hotel B corresponding to the content CT21 increases from “7500 yen” to “15000 yen”. . In the example of FIG. 1, as shown in the content information storage unit 122, the price of the service provided on the X month Y day at the hotel K corresponding to the content CT55 increases from “7000 yen” to “14000 yen”. . As described above, the providing apparatus 100 determines the price according to the demand of the hotel.

  And user U1 inputs the conditions about a hotel via input page W11 of accommodation reservation site A displayed on terminal unit 10-1. In the example illustrated in FIG. 1, information related to the designation of the user U1 related to the provision of the accommodation service is input in the input page W11 displayed on the screen of the terminal device 10-1. For example, the example of FIG. 1 shows a case where information related to the area and date desired by the user U1 is input to the input fields BX11 and BX12. In FIG. 1, in order to simplify the description, a case where information regarding the area and date is received by the input fields BX11 and BX12 in the input page W11 is shown, but various information such as the number of staying days may be received.

  For example, the user U1 inputs “A area” in the input field BX11 for inputting an area. For example, the user U1 inputs “X month Y day” in the input field BX12 for inputting a date. Note that the terminal device 10 may accept an input to the input field BX11 and the input field BX12 by selecting from a list by a displayed combo box or the like, or by selecting a date from a displayed calendar or the like. Thereafter, the user U1 presses the button BT11 in the input page W11 displayed on the screen of the terminal device 10-1.

  The terminal device 10-1 in which the button BT11 is pressed by the user U1 transmits a request for information related to the hotel corresponding to the date “X month Y day” and the area “A region” to the providing device 100. Thereby, the providing apparatus 100 acquires a hotel information request (step S15). In the example of FIG. 1, the providing apparatus 100 obtains a request for information regarding a hotel corresponding to the date “X month Y day” and the area “A area” from the terminal apparatus 10-1 used by the user U 1.

  The providing device 100 that has acquired the hotel information request from the terminal device 10 determines (extracts) a hotel corresponding to the hotel information request. For example, the providing apparatus 100 extracts a hotel located in the A area from the hotels stored in the accommodation facility information storage unit 121. In the example of FIG. 1, the providing apparatus 100 determines a hotel A, a hotel B, and the like located in the A area among the hotels stored in the accommodation facility information storage unit 121 as the hotels corresponding to the request.

  Then, the providing apparatus 100 determines (extracts) the content of the date corresponding to the hotel information request among the accommodation services provided at the determined hotel. For example, the providing apparatus 100 extracts content that has a date of “X month Y day” and remains in stock from the content stored in the content information storage unit 122. In the example of FIG. 1, the providing apparatus 100 includes the content CT11 corresponding to the service provided on the X month and Y at the hotel A among the contents stored in the content information storage unit 122 and the X month and Y on the hotel B. The content CT21 corresponding to the service provided to the user, the content CT55 corresponding to the service provided on the X month Y at the hotel K, etc. are determined as the content corresponding to the request.

  After that, the providing apparatus 100 determines the order of contents based on a predetermined criterion. In the example of FIG. 1, in order to simplify the description, the providing apparatus 100 determines the contents to be displayed in order from the top in the content information storage unit 122 among the contents corresponding to the conditions input by the user U1. Specifically, providing apparatus 100 determines content to be displayed in the order of content CT11, content CT21, content CT55, and the like. The providing apparatus 100 may randomly determine the order of content corresponding to the condition input by the user U1. The providing apparatus 100 may determine the content to be displayed and the display order of the content based on the score (evaluation) calculated based on the information related to the service and the information related to the content. Details will be described later.

  After that, the providing device 100 provides information related to the content based on the determined order to the terminal device 10 (step S16). In the example of FIG. 1, the providing device 100 provides the list information LT11 to the terminal device 10-1.

  The terminal device 10 provided with the list information LT11 from the providing device 100 displays the list information LT11 (step S17). In the example of FIG. 1, the display is transitioned from the terminal device 10-1 to the terminal device 10-2.

  A list page W12 for displaying a list of information is displayed on the screen of the terminal device 10-2. Specifically, on the screen of terminal device 10-2, list page W12 that displays information related to the accommodation service provided in area A on X month Y is displayed.

  In the example of FIG. 1, information related to services provided at the hotel A corresponding to the content CT11 having the first rank is displayed at the top of the list page W12 of the terminal device 10-2. Specifically, information indicating that an overnight breakfast service at Hotel A is provided for 10,000 yen is displayed at the top of list page W12. In addition, in the list page W12 of the terminal device 10-2, information related to services provided at the hotel B corresponding to the content CT21 having the second rank is displayed immediately below the content CT11. Specifically, information indicating that the accommodation service with breakfast at the hotel B is provided for 15000 yen is displayed immediately below the content CT11 in the list page W12. Further, information related to services provided at the hotel K corresponding to the content CT55 in the third rank is displayed immediately below the content CT21 in the list page W12. As described above, in the example of FIG. 1, on the list page W <b> 12 of the terminal device 10-2, the contents related to the accommodation service provided in the A region on the X month Y are displayed side by side in descending order. In addition, for example, when the user U1 selects the content displayed on the list page W12, the terminal device 10 displays a reservation confirmation screen for a service corresponding to the content selected by the user U1.

  As described above, the providing apparatus 100 sets the value related to the demand for hotels in the A area on the event date “X month Y day” and the value related to the supply of hotels in the A area on the event date “X month Y day”. Based on this, the supply and demand index indicating the relationship between the demand and supply of hotels in area A on the event date “X month Y day” is predicted. Thus, for example, the providing apparatus 100 predicts a demand assumed for the supply based on the relationship between the demand and the supply. In the example of FIG. 1, the providing apparatus 100 has a predicted supply and demand index of “2”, which is larger than “1”. Therefore, the demand for the accommodation service provided in the area A on the event date “X month Y day” is supplied. Is expected to be greater than That is, the providing apparatus 100 predicts that demand is higher than supply and there is room for price increases. As described above, the providing apparatus 100 can appropriately predict the demand for services provided in a predetermined facility.

  In the example described above, an example in which the providing device 100 predicts demand based on event information has been shown, but the providing device 100 may predict demand using various information as appropriate. For example, the providing apparatus 100 may predict demand from past trends based on historical information related to information provision of services in a predetermined information providing service. For example, when the target whose demand is predicted is the A area on the X month Y day, the providing apparatus 100 has an average demand on the X month Y day of the A area up to the previous year of the year to be predicted is “1.5”. In this case, the average demand on the X month Y day in the A area in that year may be predicted as “1.5”. For example, when the demand increases in a specific season in a predetermined region as compared with other seasons, the providing apparatus 100 may predict the demand in the specific season to be larger than the other seasons. Further, for example, the providing apparatus 100 may predict information on the number of rooms used for providing an accommodation service provided in an accommodation facility as information on demand. For example, the providing apparatus 100 may predict information regarding the number of hotel rooms that are expected to be in demand on the date of the event, based on the number of people assumed in the event.

  For example, the providing apparatus 100 may determine the price of the service based on the average price of the service and information related to the demand for the service. For example, when the average price of the accommodation service of the hotel A is “5000 yen”, the providing apparatus 100 prices the service corresponding to the content CT11 based on the average price “5000 yen” and the supply and demand index “2”. May be determined as “10000 (= 5000 × 2) yen”. For example, when the service demand satisfies a predetermined condition, the providing apparatus 100 may determine a value obtained by increasing the average price by a predetermined value as the service price. For example, the providing apparatus 100 provides a service provided on the X month Y day at the hotel A corresponding to the content CT11 because the supply and demand index in the A region on the X month Y day is “2” and exceeds a predetermined threshold “1”. The price may be determined as “10000 yen”, increased by “5000 yen”. For example, the providing apparatus 100 may determine the price of the service so as to be equal to or higher than the minimum price associated with the service. For example, when the minimum price of the accommodation service of the hotel A is set to “2500 yen”, the providing apparatus 100 stores the content CT11 in the content CT11 even if the supply and demand index of the A area on X month Y is less than “1”. The price of the service provided on the X month Y at the corresponding hotel A may not be less than “2500 yen”. Thereby, the manager of the hotel A and the like can suppress the price collapse due to the price of the accommodation service being less than “2,500 yen”.

[2. Configuration of providing device]
Next, the configuration of the providing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram illustrating a configuration example of the providing apparatus 100 according to the embodiment. As illustrated in FIG. 2, the providing apparatus 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The providing device 100 includes an input unit (for example, a keyboard and a mouse) that receives various operations from an administrator of the providing device 100 and a display unit (for example, a liquid crystal display) for displaying various types of information. May be.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). The communication unit 110 is connected to the network by wire or wirelessly, and transmits and receives information to and from the terminal device 10 and the information providing device 50 included in the providing system 1, for example.

(Storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. As illustrated in FIG. 2, the storage unit 120 according to the embodiment includes an accommodation facility information storage unit 121, a content information storage unit 122, a region information storage unit 123, and an event information storage unit 124.

(Accommodation information storage unit 121)
The accommodation facility information storage unit 121 according to the embodiment stores information regarding an accommodation facility (hotel). In FIG. 3, an example of the information regarding the accommodation facility memorize | stored in the accommodation facility information storage part 121 is shown. As illustrated in FIG. 3, the accommodation facility information storage unit 121 includes items such as “facility ID”, “accommodation facility”, “access information”, and “facility information” as information regarding the accommodation facility.

  “Facility ID” indicates identification information for identifying an accommodation facility. “Accommodation facility” indicates the name of the accommodation facility identified by the facility ID. “Access information” indicates information related to access to the corresponding accommodation facility. For example, “access information” includes items such as “location” and “time”. The “facility information” indicates information regarding the characteristics of the corresponding accommodation facility. For example, “facility information” includes items such as “hot spring” and “pet”.

  For example, in the example shown in FIG. 3, the hotel identified by the facility ID “H1” is “hotel A”. The location of the hotel A is “A area”, and the required time to the hotel A is “5 minutes on foot from the station A”. Hotel A indicates that the hot spring is “present” and the pet is “impossible”.

  Note that the above is an example of information relating to accommodation facilities, and the accommodation facility information storage unit 121 may store various types of information depending on the purpose as long as the information is related to accommodation facilities.

(Content information storage unit 122)
The content information storage unit 122 according to the embodiment stores various types of information related to content. For example, the content information storage unit 122 stores various types of information related to service content. FIG. 4 is a diagram illustrating an example of a content information storage unit according to the embodiment. The content information storage unit 122 illustrated in FIG. 4 includes “accommodation facility”, “content ID”, “date”, “inventory”, “CTR”, “CVR”, “price”, “fee”, “option information”, and the like. Have items. The “option information” includes an item “breakfast”. “Breakfast” in “Option information” indicates whether or not breakfast is provided in the service corresponding to the content. The “option information” is not limited to “breakfast”, and may include various items such as “dinner” and “pick-up”.

  “Accommodation facility” indicates the name of the accommodation facility identified by the facility ID (see FIG. 3). The “content ID” indicates identification information for identifying content corresponding to a service provided at the accommodation facility. “Date” indicates a date when the corresponding content service is provided. “Inventory” indicates the number of inventory (for example, the number of rooms) on the date when the corresponding content service is provided.

  “CTR” indicates a so-called click rate. For example, “CTR” indicates a value obtained by dividing the number of operations (clicks) for selecting the content identified by the content ID by the number of times the content is displayed. Further, “CVR” indicates an index relating to an action that leads to the benefit of the service provider corresponding to the content identified by the content ID. For example, “CVR” indicates a value obtained by dividing the number of times the service corresponding to the content identified by the content ID is purchased by the number of times the content is displayed. Further, for example, “CVR” may be a value obtained by dividing the number of times reservation is made for the service corresponding to the content identified by the content ID by the number of times the content is displayed. Note that “CTR” and “CVR” may store actually measured values, or may store estimated CTR values and estimated CVR values estimated by various conventional techniques. “Price” indicates the price of the service corresponding to the content identified by the content ID. The “fee” indicates a ratio of a fee received by the provider of the reservation service when an action leading to the profit of the provider providing the service corresponding to the content via the content is performed. For example, “fee” indicates a rate of a fee received by a reservation service provider when a service corresponding to the content is provided via the content. The “fee” may vary depending on the price, date, and the like.

  The example of FIG. 4 indicates that the service provided by the hotel A includes a service corresponding to the content (content CT11) identified by the content ID “CT11”. The service corresponding to the content CT11 indicates that the provided date is “X month Y day” and the stock is “10 (room)”.

  In the example of FIG. 4, the content CT11 has a CTR of “0.1”, a CVR of “0.05”, a price of “5000”, and a fee of “0.1”. Indicates. That is, the example of FIG. 4 indicates that the content CT11 has a CTR of 10%, a CVR of 5%, a price of 5000 yen, and a fee of 10%. In addition, the example of FIG. 4 indicates that the service corresponding to the content CT11 has “None” for breakfast.

  The content information storage unit 122 is not limited to the above, and may store various types of information according to the purpose. For example, the content information storage unit 122 may store information regarding a room in which a service corresponding to the content is provided. For example, when the hotel has a plurality of types of rooms, the content information storage unit 122 may store information related to contents and stock corresponding to the rooms for each type. For example, the content information storage unit 122 may store information related to various rooms such as the size and floor number of a room in which a service corresponding to the content is provided. For example, the content information storage unit 122 may store various types of information used for calculating CTR and CVR. For example, the content information storage unit 122 may store various information such as the number of times content is displayed, the number of times the content is selected, and the number of times that an action leading to the benefit of the service provider corresponding to the content is performed. . Although not shown in FIG. 4, the content information storage unit 122 may store various information such as character information such as titles and explanations of each content and image information of hotels in association with each other.

(Regional information storage unit 123)
The area information storage unit 123 according to the embodiment stores various types of information regarding each area. For example, the area information storage unit 123 stores information on the accommodation service capacity in each area. FIG. 5 is a diagram illustrating an example of a regional information storage unit according to the embodiment. The area information storage unit 123 illustrated in FIG. 5 includes items such as “area ID”, “area”, and “total hotel accommodation number”.

  “Region ID” indicates identification information for identifying a region. “Region” indicates a region identified by a region ID. The “total number of hotels accommodated” indicates the number of people that can be accommodated in one day in the entire hotel in the area identified by the area ID.

  For example, in the example shown in FIG. 5, the area identified by the area ID “RG1” is “A area”, and the total number of hotels per day in the A area is “25,000 people”. Indicates. Further, for example, in the example shown in FIG. 5, the area identified by the area ID “RG2” is “B area”, and the total number of hotels per day in the B area is “50,000 people”. Indicates.

  Note that the area information storage unit 123 is not limited to the above, and may store various information according to the purpose. For example, the area information storage unit 123 may store information indicating the remaining capacity that can be accommodated on each date based on the total number of hotels accommodated and the number of reservations on each date.

(Event information storage unit 124)
The event information storage unit 124 according to the embodiment stores various types of information related to events. For example, the event information storage unit 124 stores various information related to events. FIG. 6 is a diagram illustrating an example of an event information storage unit according to the embodiment. The event information storage unit 124 illustrated in FIG. 6 includes items such as “event ID”, “date”, “venue”, “region”, and “expected number of people”.

  “Event ID” indicates identification information for identifying an event. “Date” indicates the date on which the event identified by the event ID is held. “Venue” indicates the venue where the event identified by the event ID is held. “Region” indicates the region where the event identified by the event ID is held. “Estimated number of people” indicates the number of people expected to attract customers for the event identified by the event ID.

  For example, in the example shown in FIG. 6, the event identified by the event ID “IV11” is held on the date “X month Y day”. For example, in the example illustrated in FIG. 6, the event identified by the event ID “IV11” is held at the venue “X Stadium” located in the region “A region”. For example, in the example illustrated in FIG. 6, the event identified by the event ID “IV11” indicates that the expected number of customers is “50,000”.

  The event information storage unit 124 is not limited to the above, and may store various information according to the purpose. For example, the event information storage unit 124 may store information related to an organizer or performer who holds an event. For example, the event information storage unit 124 may store information indicating an assumed range such as “30,000 to 50,000” as the assumed number of people. For example, when the event is held over a plurality of days, the event information storage unit 124 may store information indicating a range such as “X month Y day-Z day” in the date.

(Control unit 130)
Returning to the description of FIG. 2, the control unit 130 is a controller and is stored in a storage device inside the providing apparatus 100 by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. Various programs (corresponding to an example of a prediction program) are implemented by using the RAM as a work area. The control unit 130 is a controller, and is realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  As illustrated in FIG. 2, the control unit 130 includes an acquisition unit 131, a prediction unit 132, a determination unit 133, and a provision unit 134, and implements or executes the information processing functions and operations described below. .

(Acquisition part 131)
For example, the acquisition unit 131 acquires various types of information. For example, the acquisition unit 131 acquires various types of information from the accommodation facility information storage unit 121, the content information storage unit 122, the regional information storage unit 123, and the event information storage unit 124. The acquisition unit 131 may acquire various types of information from an external information processing apparatus. In addition, the acquisition unit 131 acquires various types of information from the information providing apparatus 50.

  For example, the acquisition unit 131 acquires an information request from the terminal device 10. For example, the acquisition unit 131 acquires a hotel information request from the terminal device 10 used by the user U1. In the example of FIG. 1, the acquisition unit 131 acquires a request for information regarding a hotel corresponding to the date “X month Y day” and the area “A region” from the terminal device 10-1.

  For example, the acquisition unit 131 acquires web information collected on the web. For example, the acquisition unit 131 acquires web information including information regarding an event at a point having a predetermined relationship with a predetermined facility. For example, the acquisition unit 131 acquires web information including information on an event at a point located within a predetermined range from a predetermined facility. For example, the acquisition unit 131 acquires history information related to service information provision in a predetermined information provision service.

  In the example of FIG. 1, the acquisition unit 131 acquires event information from the information providing apparatus 50. For example, the acquisition unit 131 acquires event information IV11 indicating that the idol A performs a concert on the X month Y at the X stadium from the information providing apparatus 50.

(Prediction unit 132)
The prediction unit 132 predicts various information. For example, the prediction unit 132 predicts information related to the demand for services provided in a predetermined facility based on the web information acquired by the acquisition unit 131. For example, the prediction unit 132 predicts information related to the demand for services provided in a predetermined facility located in a predetermined area. For example, the prediction unit 132 predicts information regarding the demand for services provided at a predetermined facility on a predetermined date.

  In the example of FIG. 1, the prediction unit 132 predicts the demand on the event date based on the acquired event information and information on the area where the event corresponding to the event information is held. For example, the prediction unit 132 determines that the event date “X month Y” is based on the event information IV11 indicating that the idol A performs a concert on the X month Y at the X stadium and the information regarding the A area where the X stadium is located. The demand for hotels in area A on “day” is predicted.

  In the example of FIG. 1, the prediction unit 132 predicts the demand for hotels in the A area on the event date “X month Y day” using the area information stored in the area information storage unit 123. For example, the prediction unit 132 sets a value “50,000” related to the demand for hotels in the A area on the event date “X month Y day” and a value “related to the supply of hotels in the A area on the event date“ X month Y day ”. On the basis of “25,000”, a supply and demand index indicating the relationship between the demand and supply of hotels in area A on the event date “X month Y day” is predicted.

  For example, the prediction unit 132 predicts a value “2 (= 50000/25000)” obtained by dividing a value “50,000” related to a hotel demand by a value “25,000” related to a hotel supply as a supply and demand index.

(Determining unit 133)
The determination unit 133 determines various information. For example, the determination unit 133 determines the price of the service based on the information related to the service demand predicted by the prediction unit 132.

  In the example of FIG. 1, the determination unit 133 predicts the demand / supply index of the hotel in the A area on the event date “X month Y day” as “2”, so the hotel in the A area on the event date “X month Y day”. Decide to raise the price of.

  In the example of FIG. 1, the determination unit 133 determines a hotel to be priced, such as a hotel A or a hotel B located in the A area among the hotels stored in the accommodation facility information storage unit 121. Then, for example, the determination unit 133 determines the price of the service provided on the X and Y days at the hotel A corresponding to the content CT11 among the contents stored in the content information storage unit 122, and the hotel B corresponding to the content CT21. The price of the service provided on the X month Y and the price of the service provided on the X month Y at the hotel K corresponding to the content CT55 are determined to increase.

  In the example of FIG. 1, the determination unit 133 predicts the demand / supply index of the hotel in the A area on the event date “X month Y day” as “2”, so the hotel in the A area on the event date “X month Y day”. It is determined that the price will be increased by a factor of two based on the supply and demand index.

  For example, the determination unit 133 determines the price of the service based on the average price of the service and information related to the service demand. For example, when the service demand satisfies a predetermined condition, the determination unit 133 determines a value obtained by increasing the average value by a predetermined value as the service price. For example, the determination unit 133 determines the price of the service so that the price is equal to or higher than the lowest price associated with the service.

  For example, the determination unit 133 extracts (determines) information corresponding to the hotel information request. For example, the determination unit 133 determines information corresponding to the hotel information request acquired by the acquisition unit 131. For example, the determination unit 133 determines information corresponding to the hotel information request transmitted from the terminal device 10. For example, the determination unit 133 extracts content corresponding to the hotel information request transmitted from the terminal device 10 from the content information storage unit 122. For example, the determination unit 133 determines the order of content based on a predetermined criterion.

  In the example of FIG. 1, the determination unit 133 determines (extracts) a hotel corresponding to the hotel information request. For example, the determination unit 133 extracts a hotel located in the A area from the hotels stored in the accommodation facility information storage unit 121. In the example of FIG. 1, the determination unit 133 determines, among the hotels stored in the accommodation facility information storage unit 121, a hotel A or a hotel B that is located in the A area as a hotel corresponding to the request.

  Further, in the example of FIG. 1, the determination unit 133 determines (extracts) the content having the date corresponding to the hotel information request among the accommodation services provided in the determined hotel. In the example of FIG. 1, the determination unit 133 determines the content to be displayed in order from the top in the content information storage unit 122. For example, the determination unit 133 determines the content to be displayed in the order of content CT11, content CT21, content CT55, and the like.

  Moreover, the determination part 133 may calculate various information. For example, the determination unit 133 calculates an evaluation regarding the service based on the information regarding the service and the information regarding the content. For example, the determination unit 133 calculates an evaluation regarding the service based on information regarding the user.

  For example, the determination unit 133 determines the score (hereinafter referred to as “the service” corresponding to the content based on the information related to the accommodation service (eg, price) and the information related to the content of the accommodation service (eg, CTR, CVR, etc.). Content score ”). For example, the determination unit 133 may calculate the content score based on the following equation (1).

  Score = CTR x CVR x price x commission (1)

  “CTR” in the right side of the above equation (1) indicates the click rate of the corresponding content. Further, “CVR” in the right side of the above equation (1) indicates the conversion rate of the corresponding content. The “price” in the right side of the above formula (1) indicates the price of the service corresponding to the content. Further, the “fee” in the right side of the above formula (1) is a fee received by the provider of the reservation service when an action leading to the profit of the provider that provides the service corresponding to the content is performed via the content. Indicates the percentage.

  In addition, said Formula (1) is an example, and the determination part 133 may calculate the score of a content using various information suitably. For example, the determination unit 133 calculates the content score using the above equation (1). For example, the determination unit 133 calculates the score of the content CT11 as in the following formula (2).

  Score of content CT11 = 0.1 × 0.05 × 5000 × 0.1 (2)

  For example, the determination unit 133 calculates the score of the content CT21 as in the following formula (3).

  Score of content CT21 = 0.05 × 0.06 × 7500 × 0.1 (3)

  For example, the determination unit 133 calculates the score of the content CT55 as in the following formula (4).

  Score of content CT55 = 0.1 × 0.05 × 7000 × 0.1 (4)

  As shown in the above formulas (2) to (4), for example, the determination unit 133 calculates the score of the content CT11 of the hotel A as 2.5 and calculates the score of the content CT21 of the hotel B as 2.25. Then, the score of the content CT55 of the hotel K is calculated as 3.5. As described above, the determination unit 133 can appropriately calculate a score (evaluation) related to a service corresponding to the content by calculating a score in consideration of information related to a user operation such as CTR or CVR.

  For example, the determination unit 133 determines the rank of content based on the score calculated by the determination unit 133. For example, the determination unit 133 determines the rank of content in descending order of the score calculated by the determination unit 133. For example, as shown in the list information LT11, the determination unit 133 ranks the content CT55 having the highest score “3.5” first, the content CT11 having the second highest score after the content CT55, and the content CT11 next. The content CT21 having a higher score is determined as the third place.

  For example, the determination unit 133 may calculate the content score by changing the weight of each element of the above equation (1). For example, the determination unit 133 may calculate the content score using the following equation (5).

  Score = α x (CTR x CVR x price x fee) (5)

  For example, the determination unit 133 may calculate the score according to the purpose or the use by changing the value of the weight “α” between 0 and 1 or less according to the purpose or the use. For example, the determination unit 133 may calculate the score by changing the value of the weight “α” according to the content for which the score is to be calculated. For example, the determination unit 133 may calculate the score by changing the value of the weight “α” according to a service, a hotel, or the like corresponding to the content whose score is to be calculated.

  For example, the determination unit 133 may calculate a score (evaluation) related to the service based on information related to the user. For example, the determination unit 133 may calculate a score related to a service based on information related to a user including user attribute information. For example, the determination unit 133 may calculate a service-related score based on information such as the user's sex and age.

  For example, the determination unit 133 may calculate a service-related score based on information such as CTR and CVR that vary according to the user attribute of the user who is the information providing destination. For example, the determination unit 133 acquires history information related to providing information to the user by dividing the display count, the click count, the purchase count, and the like of content for each user attribute, and calculates CTR, CVR, etc. for each user attribute Then, based on the CTR, CVR, or the like, a score related to the service may be calculated according to the user who is the information providing destination. For example, when the user who is the information providing destination is a male in his twenties, the determination unit 133 is a user who is a male in his twenties based on CTR, CVR, and the like calculated according to history information regarding information provision to men in his twenties You may calculate the score regarding the service corresponding to.

  For example, the determination unit 133 may calculate a score regarding the service based on information regarding the service including information regarding a predetermined facility. For example, the determination unit 133 may calculate a score relating to the service based on information relating to access to the hotel, information relating to a review on the hotel, and the like. For example, the determination unit 133 may calculate the score by changing the value of the weight “α” in the above equation (5) according to information on a hotel for which a service corresponding to the content is provided. For example, when the traffic access to a certain hotel (hotel X) is better than that of another hotel, the determination unit 133 compares the content corresponding to the hotel X with respect to the case where the score of the content corresponding to the other hotel is calculated. When calculating the score, a value such as the weight “α” may be increased.

  Further, for example, the determination unit 133 varies the value of the weight “α” in the above equation (5) according to the combination of the user attribute of the user who is the information providing destination and the hotel corresponding to the content, thereby You may calculate the score regarding a service according to the user who becomes a provision place. For example, when the user who is the information providing destination is a woman, the determination unit 133 calculates the score of the content corresponding to the hotel with the high usage rate of the female user, and the score of the content corresponding to the other hotel The value of the weight “α” may be increased as compared with the case of calculating. For example, when the information providing destination user is an elderly person (for example, over 60s), the determination unit 133 supports other hotels when calculating the score of content corresponding to a hotel with good traffic access. The value of the weight “α” may be increased as compared to the case where the score of the content to be calculated is calculated.

  Moreover, the determination part 133 may calculate the score regarding a service based on the date / time designated by the user or the information regarding the user including the information regarding the purpose of use. For example, the determination unit 133 calculates the score related to the service by changing the value of the weight “α” in the above formula (5) according to the date and time specified by the user or the information regarding the purpose of use. Also good. For example, when the usage purpose of the user who is the information providing destination is business, the determination unit 133 corresponds to another hotel when calculating the score of the content corresponding to the hotel having a high ratio of being used in business. The value of the weight “α” may be increased as compared to the case of calculating the content score. For example, when the usage purpose of the user who is the information providing destination is private, the determining unit 133 corresponds to another hotel when calculating the score of the content corresponding to the hotel that is used privately The value of the weight “α” may be increased as compared to the case of calculating the content score. For example, the determination unit 133 may acquire the user's purpose of use by the user's input or the like on the input page W11, or may estimate the user's usage purpose based on an action history or the like until the user's hotel reservation. . Note that the above is an example, and the determination unit 133 may calculate the score based on various information and the like as long as the score regarding the service can be calculated.

(Providing unit 134)
The providing unit 134 provides various types of information to an external information processing apparatus. For example, the providing unit 134 provides the content of each service based on the order determined by the determining unit 133. For example, the providing unit 134 provides content based on the evaluation calculated by the determining unit 133. For example, the providing unit 134 provides the content of each service ranked based on the evaluation regarding each service. For example, the providing unit 134 provides the content determined by the determining unit 133 to the terminal device 10. For example, the providing unit 134 provides information based on the order determined by the determining unit 133 to an external information processing apparatus. For example, the providing unit 134 provides information based on the order determined by the determining unit 133 to the terminal device 10 that is the transmission source of the hotel information request.

  For example, the providing unit 134 provides list information regarding services to the terminal device 10 used by the user U1. For example, the providing unit 134 provides information based on the order determined by the determining unit 133 to the terminal device 10. In the example of FIG. 1, the providing unit 134 provides the list information LT11 to the terminal device 10-1.

[3. (Prediction process flow)
Here, the procedure of the prediction process by the providing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 7 is a flowchart illustrating an example of the prediction process according to the embodiment.

  As shown in FIG. 7, the providing apparatus 100 acquires event information (step S101). In FIG. 1, the providing apparatus 100 acquires information indicating that an idol A concert will be held on the X month Y at the X stadium in the A area.

  Further, the providing device 100 predicts the demand of the hotel in the corresponding region based on the event information (step S102). In FIG. 1, the providing device 100 predicts the demand for hotels on the X month and the Y in the A area.

  Further, the providing apparatus 100 determines the accommodation price of the hotel in the corresponding region based on the predicted demand for the hotel (step S103). For example, the providing device 100 doubles the hotel price on the X month Y in the A area because the demand for the hotel on the X month Y in the A area is twice the total accommodation capacity in the A area. decide.

[4. Decision processing flow)
Here, a procedure for determining information provided by the providing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 8 is a flowchart illustrating an example of determining information to be provided according to the embodiment.

  As shown in FIG. 8, the providing apparatus 100 acquires a hotel information request (step S201). In FIG. 1, the providing apparatus 100 acquires a hotel information request from the terminal apparatus 10 used by the user U1.

  Also, the providing apparatus 100 extracts content corresponding to the request (step S202). In FIG. 1, the providing device 100 extracts content related to a hotel that can be used in the A region on the X month and the Y specified by the user U1.

  After that, the providing apparatus 100 determines the ranking of the content based on the calculated score (Step S203). For example, the providing apparatus 100 determines the order of content based on a predetermined criterion. In FIG. 1, the providing apparatus 100 determines the content CT11 as the first and the content CT21 as the second as shown in the list information LT11.

  After that, the providing apparatus 100 provides content list information based on the determined order (step S204). In FIG. 1, the providing device 100 provides the list information LT11 to the terminal device 10 used by the user U1.

[5. (Prices in the surrounding area)
In the above-described example, the case where the demand is predicted only in the area where the event is held and the price is determined has been described, but the price of the hotel in the surrounding area may be determined. This point will be described with reference to FIG. FIG. 9 is a diagram illustrating an example of price determination based on demand according to the embodiment. Map information MP11 in FIG. 9 schematically shows determination of a price based on demand for hotels located in the area RG11 of the area RG1, which is the A area, and in the area around the area RG11. In addition, about the structure similar to embodiment, the same code | symbol is attached | subjected and description is abbreviate | omitted.

  The map information MP11 in FIG. 9 shows an example of determining the price of each hotel according to the event corresponding to the event information IV11 in the example shown in FIG. Specifically, the map information MP11 indicates a case where an event is held at the stadium X, which is the venue VN11, on the date “X month Y day” as in FIG.

  First, in the example of FIG. 9, as shown in the price change information VC <b> 1, the providing apparatus 100 changes the price of the service provided on the XX month Y at the hotel H <b> 1 in FIG. Decided to raise to "10000 yen". In the example of FIG. 9, the providing apparatus 100 sets the price of the service provided on the X and Y days at the hotel H2 in FIG. 9 as the hotel B from “7500 yen” as shown in the price change information VC2. Decided to raise to "15000 yen".

  Here, in the providing apparatus 100, the total number of hotels accommodated in the area A per day is “25,000”, and the estimated number of events corresponding to the event information IV11 is “50,000”. Predict that 25,000 event attendees cannot stay in area A. Therefore, the providing apparatus 100 predicts that the demand generated by the event corresponding to the event information IV11 will spread to the surrounding area RG11 of the A area and the surrounding area of the surrounding area RG11. Then, providing apparatus 100 determines that the price of hotels in the surrounding area RG11 of area A and the surrounding area of surrounding area RG11 is also increased.

  For example, the providing apparatus 100 determines to increase the price of the hotel in the surrounding area RG11 in the A area by a rate of increase of “2 times” or less in the price of the hotel in the A area. In the example of FIG. 9, providing apparatus 100 determines to increase the price of a hotel in surrounding area RG11 in area A by 1.5 times.

  For example, as shown in the price change information VC21, the providing apparatus 100 determines to increase the price of the service provided on the X month Y in the hotel H21, which is the hotel X, from “10000 yen” to “15000 yen”. . Further, for example, as shown in the price change information VC22, the providing apparatus 100 increases the price of the service provided on the X month Y at the hotel H22, which is the hotel Y, from “5000 yen” to “7500 yen”. decide.

  Further, for example, providing apparatus 100 determines to increase the prices of hotels in the vicinity of surrounding area RG11 at a rate of increase of “1.5 times” or less in the price of hotels in surrounding area RG11. In the example of FIG. 9, providing apparatus 100 determines to increase the price of a hotel in the vicinity of surrounding area RG11 by 1.25 times.

  For example, as shown in the price change information VC31, the providing apparatus 100 determines to increase the price of the service provided on the X month Y at the hotel H31, which is the hotel Z, from “10000 yen” to “12,500 yen”. .

  Thus, the providing apparatus 100 predicts that the demand generated by the event spreads from the area where the event is held to the surrounding area, and determines the price of the hotel in the surrounding area according to the prediction, It is possible to appropriately determine the price of a hotel that takes into account the influence of the event.

[6. effect〕
As described above, the providing apparatus 100 according to the embodiment includes the acquisition unit 131 and the prediction unit 132. The acquisition unit 131 acquires web information collected on the web. Based on the web information acquired by the acquisition unit 131, the prediction unit 132 predicts information related to the demand for services provided in a predetermined facility.

  Thereby, the providing apparatus 100 according to the embodiment appropriately predicts the demand for the service provided at the predetermined facility by predicting the information regarding the demand for the service provided at the predetermined facility based on the web information. can do.

  Moreover, in the providing apparatus 100 according to the embodiment, the prediction unit 132 predicts information related to the demand for services provided in a predetermined facility located in a predetermined area.

  Thereby, the providing apparatus 100 according to the embodiment appropriately predicts the demand for the service provided in the predetermined facility by predicting the information related to the demand for the service provided in the predetermined facility located in the predetermined area. Can be predicted.

  Moreover, in the providing apparatus 100 according to the embodiment, the prediction unit 132 predicts information regarding the demand for services provided at a predetermined facility on a predetermined date.

  Thereby, the providing apparatus 100 according to the embodiment appropriately predicts the demand for the service provided at the predetermined facility by predicting the information regarding the demand for the service provided at the predetermined facility on the predetermined date. Can do.

  In the providing apparatus 100 according to the embodiment, the acquisition unit 131 acquires web information including information regarding an event at a point having a predetermined relationship with a predetermined facility.

  Thereby, the providing apparatus 100 according to the embodiment appropriately predicts the demand for the service provided in the predetermined facility by acquiring the web information including the information regarding the event at the point having the predetermined relationship with the predetermined facility. can do.

  In the providing device 100 according to the embodiment, the acquisition unit 131 acquires web information including information regarding an event at a point located within a predetermined range from a predetermined facility.

  Thereby, the providing apparatus 100 according to the embodiment appropriately satisfies the demand for the service provided in the predetermined facility by acquiring the web information including the information on the event at the point located within the predetermined range from the predetermined facility. Can be predicted.

  In addition, the providing apparatus 100 according to the embodiment includes a determination unit 133. The determination unit 133 determines the price of the service based on the information related to the service demand predicted by the prediction unit 132.

  Thereby, the providing apparatus 100 according to the embodiment appropriately determines the price of the service provided in the predetermined facility based on the demand by determining the price of the service based on the predicted information on the demand of the service. Can be determined.

  In the providing apparatus 100 according to the embodiment, the determination unit 133 determines the price of the service based on the average price of the service and information related to the demand for the service.

  Accordingly, the providing apparatus 100 according to the embodiment determines the price of the service based on the average price of the service and the information related to the demand for the service, so that the price of the service provided in the predetermined facility becomes the demand. Based on this, it can be determined appropriately.

  Further, in the providing apparatus 100 according to the embodiment, when the service demand satisfies a predetermined condition, the determination unit 133 determines a value obtained by increasing the predetermined value to the average price as the service price.

  Accordingly, the provision apparatus 100 according to the embodiment is provided in a predetermined facility by determining a value obtained by increasing the predetermined value to the average price as a service price when the demand for the service satisfies a predetermined condition. The price of the service can be determined appropriately based on the demand.

  In the providing apparatus 100 according to the embodiment, the determination unit 133 determines the price of the service so that the price is equal to or higher than the lowest price associated with the service.

  Thereby, the providing apparatus 100 according to the embodiment is a case where the demand for the service provided in the predetermined facility is small by determining the price of the service so as to be equal to or higher than the minimum price associated with the service. Even the price of the service can be maintained.

  In the providing apparatus 100 according to the embodiment, the acquisition unit 131 acquires history information related to service information provision in a predetermined information provision service.

  Thereby, the providing apparatus 100 according to the embodiment can appropriately predict the demand for the service provided in the predetermined facility by acquiring the history information related to the service information provision in the predetermined information providing service.

[7. Hardware configuration)
The providing apparatus 100 according to the above-described embodiment is realized by a computer 1000 configured as shown in FIG. 10, for example. FIG. 10 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the providing apparatus. The computer 1000 includes a CPU 1100, a RAM 1200, a ROM (Read Only Memory) 1300, an HDD (Hard Disk Drive) 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F). ) 1700.

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

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

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

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

  For example, when the computer 1000 functions as the providing apparatus 100 according to the embodiment, the CPU 1100 of the computer 1000 implements the function of the control unit 130 by executing a program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them. However, as another example, these programs may be acquired from other devices via the network N.

  Although the embodiments of the present application have been described in detail with reference to the drawings, these are merely examples, and various modifications and improvements have been made based on the knowledge of those skilled in the art including the aspects described in the disclosure line of the invention. The present invention can be implemented in other forms.

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

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

  In addition, the processes described in the above-described embodiments can be appropriately combined within a range in which the process contents do not contradict each other.

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

1 Providing System 100 Providing Device (Prediction Device)
121 accommodation facility information storage unit 122 content information storage unit 123 regional information storage unit 124 event information storage unit 130 control unit 131 acquisition unit 132 prediction unit 133 determination unit 134 provision unit 10 terminal device N network

Claims (12)

An acquisition unit for acquiring web information collected on the web;
Based on the web information acquired by the acquisition unit, a prediction unit that predicts information related to demand for services provided in a predetermined facility;
A prediction apparatus comprising: The prediction unit
The prediction apparatus according to claim 1, wherein information relating to a demand for services provided in the predetermined facility located in a predetermined area is predicted. The prediction unit
The prediction apparatus according to claim 1, wherein information related to demand for services provided at the predetermined facility is predicted on a predetermined date. The acquisition unit
The prediction apparatus according to any one of claims 1 to 3, wherein web information including information related to an event at a point having a predetermined relationship with the predetermined facility is acquired. The acquisition unit
The prediction apparatus according to claim 4, wherein web information including information regarding an event at a point located within a predetermined range from the predetermined facility is acquired. A determination unit that determines a price of the service based on information on the demand of the service predicted by the prediction unit;
The prediction apparatus according to claim 1, further comprising: The determination unit
The prediction device according to claim 6, wherein the price of the service is determined based on an average price of the service and information related to a demand for the service. The determination unit
The prediction device according to claim 7, wherein when the demand for the service satisfies a predetermined condition, a value obtained by increasing the average price by a predetermined value is determined as the price of the service. The determination unit
The prediction device according to any one of claims 6 to 8, wherein the price of the service is determined so as to be equal to or higher than a minimum price associated with the service. The acquisition unit
The historical information regarding the information provision of the service in a predetermined information provision service is acquired. The prediction apparatus according to any one of claims 1 to 9. A prediction method performed by a computer,
An acquisition step of acquiring web information collected on the web;
Based on the web information acquired by the acquisition step, a prediction step of predicting information related to demand for services provided in a predetermined facility;
The prediction method characterized by including. An acquisition procedure for acquiring web information collected on the web;
Based on the web information acquired by the acquisition procedure, a prediction procedure for predicting information related to demand for services provided in a predetermined facility;
A prediction program that causes a computer to execute.

Images