JP2021140273A - Information processing apparatus, information processing method, and information processing program - Google Patents

Abstract

To coordinate logistics hubs in accordance with demand prediction.SOLUTION: An information processing apparatus generates merchandise demand information showing regional demand trends for merchandise on the basis of places where individual users have taken actions with respect to the merchandise and the number of actions taken in the places. Then, the information processing apparatus determines a logistics hub of the merchandise on the basis of the merchandise demand information. Further, the information processing apparatus makes a transportation plan to transport the merchandise to the logistics hub of the merchandise beforehand, on the basis of the merchandise demand information. In addition, the information processing apparatus makes a stock transfer plan to transfer the merchandise beforehand from another logistics hub having the merchandise in stock to the logistics hub of the merchandise, on the basis of the merchandise demand information.SELECTED DRAWING: Figure 1

Description

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

Conventionally, there has been known a technique for creating a transportation plan for transporting a package from a plurality of delivery bases to a plurality of delivery destinations at a designated date and time using a plurality of transportation means.

Japanese Unexamined Patent Publication No. 2013-136421

However, in the above-mentioned prior art, the result of the transportation simulation on the day of delivery is evaluated / corrected to merely create a transportation plan that minimizes the empty forwarding of the transportation means used on the day of delivery. In the above-mentioned conventional technology, even if there is demand, if the product is not in stock at a distribution base near the product, it is necessary to wait until the distribution base is in stock or go through the distribution base in stock. , It may not always be possible to say that the optimum transportation plan is created.

The present application has been made in view of the above, and an object of the present application is to adjust a distribution base according to a demand forecast.

The information processing device according to the present application shows the trend of demand for the product in each region based on the place where each user's action related to the product is performed and the number of the actions performed at the place. It is characterized by including a product demand information creation unit that creates product demand information and a distribution base determination unit that determines a distribution base of the product based on the product demand information.

According to one aspect of the embodiment, the distribution base can be adjusted according to the demand forecast.

FIG. 1 is a first explanatory diagram showing an outline of an information processing method according to an embodiment. FIG. 2 is a second explanatory diagram showing an outline of the information processing method according to the embodiment. FIG. 3 is a diagram showing a configuration example of the information processing system according to the embodiment. FIG. 4 is a diagram showing a configuration example of the information processing device according to the embodiment. FIG. 5 is a diagram showing an example of a user database. FIG. 6 is a diagram showing an example of a product demand database. FIG. 7 is a diagram showing an example of a product inventory database. FIG. 8 is a diagram showing an example of a transportation planning database. FIG. 9 is a diagram showing an example of an inventory transportation planning database. FIG. 10 is a flowchart showing a processing procedure according to the embodiment. FIG. 11 is a diagram showing an example of a hardware configuration.

Hereinafter, the information processing apparatus according to the present application, the information processing method, and a mode for carrying out the information processing program (hereinafter, referred to as “the embodiment”) will be described in detail with reference to the drawings. The information processing apparatus, information processing method, and information processing program according to the present application are not limited by this embodiment. Further, in the following embodiments, the same parts are designated by the same reference numerals, and duplicate description is omitted.

[1. Information processing method overview]
First, with reference to FIGS. 1 and 2, an outline of an information processing method performed by the information processing apparatus according to the embodiment will be described. FIG. 1 is a first explanatory diagram showing an outline of an information processing method according to an embodiment. FIG. 2 is a second explanatory diagram showing an outline of the information processing method according to the embodiment. In addition, in FIG. 1 and FIG. 2, the case where the distribution base is adjusted according to the demand forecast will be described as an example.

As shown in FIGS. 1 and 2, the information processing system 1 includes a terminal device 10, an information processing device 100, and a search server 200. The terminal device 10, the information processing device 100, and the search server 200 are connected to each other via a network N (see FIG. 3) so as to be able to communicate with each other by wire or wirelessly.

The terminal device 10 is a smart device such as a smartphone or tablet used by the user U, and communicates with an arbitrary server device via a wireless communication network such as 4G (Generation) or LTE (Long Term Evolution). It is a portable terminal device that can be used. Further, the terminal device 10 is a screen of a liquid crystal display or the like and has a screen having a touch panel function. Accepts various operations. The operation performed on the area of the screen on which the content is displayed may be an operation on the content. Further, the terminal device 10 may be not only a smart device but also an information processing device such as a desktop PC (Personal Computer) or a notebook PC.

The search server 200 is an information processing device (information processing device) that provides a function of searching for contents such as web pages, websites, and / or image files existing on the Internet in response to a search request from the terminal device 10 of the user U. It is a search engine) and is realized by a server device, a cloud system, or the like. For example, the search server 200 may provide a search site including a portal site or the like. Here, the search server 200 is a communication protocol that manages a state between the search server 200 and the web browser from the terminal device 10 or the like via a web browser when the terminal device 10 or the like accesses the search server 200. Alternatively, the HTTP Cookie or the like, which is the data stored in the web browser used there, may be acquired. The search server 200 may be a relay server (Proxy), a redirector (Redirector), or the like.

The information processing device 100 is an information processing device that adjusts a distribution base according to a demand forecast, and is realized by a server device, a cloud system, or the like. The information processing device 100 may be one of the search servers 200. That is, the information processing device 100 may also be an information processing device that provides a function of searching for contents.

[1-1. Outline of information processing method when deciding a distribution base]
First, with reference to FIG. 1, an outline of an information processing method for determining a distribution base will be described.

As shown in FIG. 1, the user U accesses the search server 200 using the terminal device 10 and inputs a search query (search keyword) related to a specific product to perform a search (step S1).

At this time, the search server 200 provides the terminal device 10 with a search result corresponding to the search query as a response. The terminal device 10 displays the search result according to the search query. The search results include sponsored search (SS), direct display (DD), and the like. Sponsored search (SS) indicates a listing advertisement (search-linked advertisement). The direct display (DD) displays the search results directly on the screen. For example, when a search is performed by inputting a place name, a map is directly displayed, and when a talent name is used, an image search result is directly displayed.

The user U uses the terminal device 10 to select an arbitrary link from the search results corresponding to the search query and display the linked web page. The linked web page is, for example, a web page containing detailed information on products related to a search query, product reviews, etc., a post such as SNS (Social Networking Service), or a landing page (LP) for an advertisement for a product related to a search query. ), Electronic shopping streets (online malls) and electronic shops (online shops) that handle products related to search queries.

The search server 200 includes identification information of each user U, location information of the terminal device 10 of each user U when performing a search (location information when accessing the search server 200), and each user U. The access log from each user U is generated by totaling the access from the terminal device 10 (step S2).

That is, the access log of each user U includes the position information of the terminal device 10 of each user U when the search is performed. Actually, the access log and the position information of the terminal device 10 may be linked. The location information is not limited to latitude / longitude and coordinates, but may be an area name or an address.

The information processing device 100 acquires the access log of each user U from the search server 200 (step S3).

At this time, the information processing apparatus 100 may acquire only the access log of the user U who has previously agreed to use the access log. For example, the information processing device 100 may acquire only the access log of the user U registered in advance.

When the information processing device 100 itself provides the content to the terminal device 10 of each user U, the information processing device 100 can generate an access log of each user U regarding the content provided by the information processing device 100. ..

The information processing device 100 aggregates the number of accesses related to a specific product for each region based on the access log of each user U, and creates product demand information for each region based on the aggregated result (step S4). ).

The number of accesses related to a specific product is, for example, the number of searches performed by inputting the name of a specific product as a search query, the number of accesses to a web page related to the specific product, and the specific product by electronic commerce. The number of purchases, or a combination of these. If the number of accesses related to a specific product is rapidly increasing in a certain area, it can be inferred that the demand for the specific product is occurring / increasing in that area. This makes it possible to predict the occurrence / increase in demand for specific products in each region. In other words, the information processing device 100 is based on information about a place where each user U's action (action) related to a specific product is performed and the number (number of times) of the action performed at that place. , Create product demand information for each region.

The information processing device 100 may aggregate the number of accesses within a predetermined period (for example, within the past one month) when totaling the number of accesses related to a specific product, or may aggregate the number of accesses on a regular basis (for example, weekly). , Monthly, etc.) may be aggregated for the number of accesses related to a specific product.

The information processing device 100 collects information on the inventory of specific products at distribution bases in each region from the store S and the delivery company DC, and based on the collected information, the product inventory for each distribution base in each region. Create information (step S5).

The store S may be a retail store that sells a specific product, a manufacturing factory that manufactures a specific product, or a large-scale distribution facility of a delivery company DC. Further, the distribution base may be a warehouse of store S, a store of an affiliated store, or a sales office (directly managed store / distribution center / agency store) of a delivery company DC.

The information processing device 100 determines a distribution base in a region where demand for a product is predicted based on the product demand information for each region (step S6).

For example, the information processing apparatus 100 determines that an area where the number of accesses related to a specific product is equal to or greater than the threshold value is "area B where the number of accesses related to the specific product is relatively high" based on the product demand information for each area, and is more than the threshold value. The area with a small number is determined as "area A with relatively little access to a specific product". The threshold value of the number of accesses may be an arbitrary numerical value, or may be an average value or a median value of the number of accesses for a specific product in each region.

Further, the threshold value of the number of accesses may be two threshold values, an upper limit value and a lower limit value. For example, the information processing apparatus 100 determines that an area equal to or greater than the upper limit of the number of accesses is "area B having a relatively large number of accesses related to a specific product", and an area below the lower limit value is defined as "a region B having a relatively small number of accesses related to a specific product". It may be determined as "Region A".

In the example shown in FIG. 1, the information processing apparatus 100 has a distribution base DB 2 in an area B in which access to a specific product is relatively large, rather than a distribution base DB 1 in an area A in which access to a specific product is relatively small. However, it is judged that it is the most suitable distribution base for actually delivering the product to the consumer of the specific product.

Further, the information processing apparatus 100 optimally selects the distribution base with the highest inventory among the plurality of distribution bases in the region B in which the access to a specific product is relatively high, based on the product inventory information for each distribution base in each region. It may be judged that it is a good distribution base.

The information processing device 100 optimizes the inventory quantity (inventory amount) of a specific product at a distribution base in each region based on the product demand information for each region, so that the appropriate inventory of the specific product at the distribution base in each region is optimized. Is calculated (step S7).

The appropriate inventory of a specific product at a distribution base in each region is calculated based on the product demand information for each region. Therefore, the appropriate inventory of specific products at distribution bases in each region is not uniform. For example, the appropriate inventory of a specific product at the distribution base DB1 in the area A in which access to the specific product is relatively low is reduced. On the contrary, the appropriate inventory of the specific product in the distribution base DB2 in the area B where the access for the specific product is relatively high increases.

For example, the information processing apparatus 100 inputs the number of accesses related to a specific product into a model, and learns the appropriate stock of the specific product as correct answer data by deep learning. Then, the information processing device 100 calculates the appropriate inventory of the specific product by inputting the number of accesses related to the specific product into the trained model.

The information processing device 100 creates a transportation plan for transporting a specific product to a distribution base in each region based on the product inventory information for each distribution base in each region and the appropriate inventory of the specific product at the distribution base in each region. (Step S8).

For example, when the information processing apparatus 100 determines that the inventory of a specific product in the distribution base DB1 in the area A in which access to the specific product is relatively small has reached the appropriate inventory in the distribution base DB1, the distribution base 100 determines that the inventory has reached the appropriate inventory in the distribution base DB1. Create a transportation plan that does not transport a specific product to DB1.

Further, in the information processing apparatus 100, based on the product inventory information for each distribution base in each region, the inventory of the specific product in the distribution base DB 2 in the region B in which the access to the specific product is relatively high is appropriate in the distribution base DB 2. When it is determined that the stock has not been reached, a transportation plan for transporting the shortage of a specific product to the distribution base DB2 is created.

The information processing device 100 provides the created transportation plan to the business operator (retailer or the like) of the store S or the delivery company DC (step S9).

For example, the business operator of the store S and the delivery company DC may own the terminal device 10 as well as each user U. The information processing device 100 provides the created transportation plan to the business operator of the store S and the terminal device 10 of the delivery company DC.

Further, the information processing device 100 may be a server device or the like owned by the business operator of the store S or the delivery company DC. In this case, the information processing device 100 may provide the created transportation plan to the business operator of the store S or the delivery company DC by displaying the created transportation plan on the display device.

The business operator of the store S and the delivery company DC transport the specific product from the store S to the distribution base in each region in advance according to the provided transportation plan (step S10).

“Transporting a specific product in advance” means, for example, transporting a specific product before actual demand is generated / increased. However, it may not necessarily be before the actual demand is generated / increased, but may be during the actual demand is generated / increased. For example, when a transportation plan is created / proposed by detecting the generation / increase of demand, it is possible that the generation / increase of demand has already started.

Actually, the information processing apparatus 100 may provide only the product demand information for each region to the business operator of the store S and the delivery company DC, not the transportation plan. In this case, the business operator of the store S or the delivery company DC creates the product inventory information for each distribution base in each region, and transports the product based on the product demand information for each region and the product inventory information for each distribution base in each region. A plan is created, and a specific product is transported in advance from the store S to the distribution base in each region according to the created transportation plan.

In addition, the distribution base DB2 in the area B where the access to a specific product is relatively high is the final distribution base (so-called last mile distribution) that actually delivers the product to the consumers of the specific product in the area. It is preferable that it is a base).

As described above, in the present embodiment, the occurrence / increase of product demand in each region is detected in advance from the increase in the number of accesses related to the specific product in each region, and the distribution base is optimized. That is, the optimum distribution base is determined according to the demand forecast.

As a result, in an area where demand for a specific product is expected to occur / increase, the specific product can be quickly delivered to the consumers in that area.

In addition, it is possible to optimize the delivery route, optimize the time required for delivery, and reduce the costs associated therewith. For example, by stacking specific products in advance at the nearest distribution base in an area where demand for specific products is expected to occur / increase, it is possible to minimize the delivery route and time required for delivery of specific products. can.

[1-2. Outline of information processing method when adjusting the inventory quantity of each distribution base]
Next, with reference to FIG. 2, an outline of an information processing method for adjusting the inventory quantity of each distribution base will be described.

Note that steps S11 to S15 shown in FIG. 2 are basically the same as steps S1 to S5 shown in FIG.

As shown in FIG. 2, the user U accesses the search server 200 using the terminal device 10 and inputs a search query (search keyword) related to a specific product to perform a search (step S11).

At this time, the search server 200 provides the terminal device 10 with a search result corresponding to the search query as a response. The terminal device 10 displays the search result according to the search query. The user U uses the terminal device 10 to select an arbitrary link from the search results corresponding to the search query and display the linked web page.

The search server 200 includes identification information of each user U, location information of the terminal device 10 of each user U when performing a search (location information when accessing the search server 200), and each user U. The access log from each user U is generated by totaling the access from the terminal device 10 (step S12).

That is, the access log of each user U includes the position information of the terminal device 10 of each user U when the search is performed. Actually, the access log and the position information of the terminal device 10 may be linked. The location information is not limited to latitude / longitude and coordinates, but may be an area name or an address.

The information processing device 100 acquires the access log of each user U from the search server 200 (step S13).

The information processing device 100 aggregates the number of accesses related to a specific product for each region based on the access log of each user U, and creates product demand information for each region based on the aggregated result (step S14). ).

The information processing device 100 collects information on the inventory of specific products at distribution bases in each region from the store S and the delivery company DC, and creates product inventory information for each distribution base in each region (step S15).

The information processing device 100 is based on the product demand information for each region and the product inventory information for each distribution base in each region, and the distribution base DB1 (non-demand region distribution) in the region A where access to a specific product is relatively small. Create an inventory transportation plan for transferring the inventory of a specific product from the base) to the distribution base DB2 (demand area distribution base) in the area B where the access for the specific product is relatively high (step S16).

For example, the information processing apparatus 100 transfers the inventory of a specific product from the non-demand area distribution base to the demand area distribution base so that each of the non-demand area distribution base and the demand area distribution base satisfies the above-mentioned appropriate inventory. Create an inventory delivery plan.

Actually, the number of specific products (transportation amount) to be transferred from the non-demand area distribution base to the demand area distribution base is arbitrary. For example, the entire inventory of a specific product in the non-demand area distribution base may be transferred to the demand area distribution base. In addition, the inventory of a specific product may be transferred so that the inventory of the distribution base in the demand area is larger than the appropriate inventory.

The information processing device 100 provides the created inventory transportation plan to the business operator (retailer or the like) of the store S or the delivery company DC (step S17).

For example, the business operator of the store S and the delivery company DC may own the terminal device 10 as well as each user U. The information processing device 100 provides the created inventory transfer plan to the business operator of the store S and the terminal device 10 of the delivery company DC.

Further, the information processing device 100 may be a server device or the like owned by the business operator of the store S or the delivery company DC. In this case, the information processing apparatus 100 may provide the created inventory transfer plan to the business operator of the store S or the delivery company DC by displaying the created inventory transfer plan on the display device.

The business operator of the store S or the delivery company DC transfers the inventory of a specific product from the non-demand area distribution base to the demand area distribution base in advance according to the provided inventory transportation plan (step S18).

Actually, the business operator of the store S or the delivery company DC may implement the above transportation plan and the inventory transportation plan in combination. For example, the inventory transportation plan may be implemented during the implementation of the transportation plan. Specifically, the inventory of a specific product may be transferred between distribution bases in the middle of the transportation route. Further, when the business operator of the store S or the delivery company DC transfers the inventory of a specific product from the non-demand area distribution base to the demand area distribution base in advance according to the inventory transportation plan, the non-demand area distribution base and / or the demand When an inventory shortage occurs at a regional distribution base, the operator of store S or the delivery company DC identifies in advance from store S to the distribution base in each region in accordance with the transportation plan in order to make up for the shortage. You may want to transport the shortage of the goods.

Further, the information processing apparatus 100 may provide only the product demand information for each region to the business operator of the store S or the delivery company DC, not the inventory transportation plan. In this case, the business operator of the store S or the delivery company DC creates the product inventory information for each distribution base in each region, and inventories based on the product demand information for each region and the product inventory information for each distribution base in each region. Create a transportation plan and transfer the inventory of a specific product from the non-demand area distribution base to the demand area distribution base in advance according to the created inventory transportation plan.

In addition, the distribution base DB2 (demand area distribution base) in the area B where the access to the specific product is relatively high is the final distribution base that actually delivers the product to the consumers of the specific product in the area. (So-called last mile distribution base) is preferable.

In this way, by multiplying the product demand information for each region and the product inventory information for each distribution base in each region, the inventory quantity of each distribution base is optimized. For example, the inventory quantity of each distribution base is adjusted according to the demand forecast.

As a result, at a distribution base in a region where demand for a specific product is occurring / increasing, it is possible to avoid a shortage of the specific product and quickly deliver the specific product to a consumer in the region.

In addition, it is possible to flexibly transfer the inventory of specific products between distribution bases according to fluctuations in demand. As a result, even if a specific product becomes popular locally, for example, the inventory of the specific product can be adjusted between the distribution bases without increasing the production amount or the purchase amount of the specific product.

In addition, it is possible to optimize the delivery route, optimize the time required for delivery, and reduce the costs associated therewith. For example, by stacking specific products in advance at the nearest distribution base in an area where demand for specific products is expected to occur / increase, it is possible to minimize the delivery route and time required for delivery of specific products. can.

[1-3. An example of inventory transfer planning process]
Here, although not shown, an example of the inventory transfer plan creation process shown in step S16 will be described.

The information processing apparatus 100 extracts a region B having a relatively large number of accesses related to a specific product and a region having a relatively small number of accesses based on the product demand information for each region (step S16-1).

Further, the information processing device 100 is specified from the distribution base DB1 (non-demand area distribution base) in the area A in which access to a specific product is relatively small, based on the product inventory information for each distribution base in each region. Extract the distribution bases (excess inventory distribution bases) in which the number of inventories of the products in stock exceeds the appropriate inventory (step S16-2).

Similarly, the information processing device 100 is specified from the distribution base DB2 (demand area distribution base) in the area B where the access to a specific product is relatively high, based on the product inventory information for each distribution base in each region. Extract distribution bases (distribution bases with insufficient inventory) for which the number of products in stock has not reached the appropriate inventory (step S16-3).

The information processing apparatus 100 creates an inventory transfer plan for transferring the inventory of a specific product from at least one excess inventory distribution base to the insufficient inventory distribution base in advance (step S16-4).

As a result, the information processing apparatus 100 transfers the inventory of a specific product from the inventory surplus distribution base to the inventory shortage distribution base so that each of the inventory surplus distribution base and the inventory shortage distribution base satisfies the above-mentioned appropriate inventory. Create a transportation plan.

In the present embodiment, when the access to a specific product is rapidly increasing in a certain area, it is estimated that the demand for the specific product in the area is generated / increased, and the distribution base in the area (or the area) is estimated to be in demand. We propose to increase the inventory of the product at the nearest distribution base).

In addition, if there is almost no access to a specific product in a certain area, it is estimated that the demand for the specific product in that area is disappearing / decreasing, and the demand for the specific product is occurring / increasing from that area. We propose to transfer the inventory of the product to.

We can also propose transportation plans that optimize trunk transportation. For example, when selecting a delivery route along a trunk line, it is possible to determine a product to be delivered to a distribution base in the area along the line by notifying what is currently prevalent in the area along the line. In addition, for example, the amount of the joint delivery contribution can be determined accordingly.

[2. Information processing system configuration example]
Next, the configuration of the information processing system 1 including the information processing device 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. As shown in FIG. 3, the information processing system 1 according to the embodiment includes a terminal device 10, an information processing device 100, and a search server 200. These various devices are communicably connected via network N by wire or wirelessly. The network N is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet.

Further, the number of each device included in the information processing system 1 shown in FIG. 3 is not limited to that shown in the figure. For example, in FIG. 3, for simplification of the illustration, only one terminal device 10 and one search server 200 are shown, but this is merely an example and is not limited, and even if there are two or more terminals. good.

The terminal device 10 is an information processing device used by the user U. For example, the terminal device 10 is a smart device such as a smartphone or tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a car navigation system, a wearable device such as a smart watch or a head-mounted display (Wearable Device). , Smart glasses, etc.

Further, the terminal device 10 includes a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), 5G (5th Generation: 5th generation mobile communication system), Bluetooth (registered trademark), and wireless LAN (Local). It can be connected to the network N via short-range wireless communication such as Area Network) and communicate with the information processing apparatus 100.

The information processing device 100 and the search server 200 are, for example, a PC, a server, a mainframe, a workstation, or the like. The information processing device 100 and the search server 200 may be realized by cloud computing.

[3. Information processing device configuration example]
Next, the configuration of the information processing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 4 is a diagram showing a configuration example of the information processing device 100 according to the embodiment. As shown in FIG. 4, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. Further, the communication unit 110 is connected to the network N (see FIG. 3) by wire or wirelessly.

(Memory unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. As shown in FIG. 4, the storage unit 120 has a user database 121, a product demand database 122, a product inventory database 123, a transportation planning database 124, and an inventory transportation planning database 125.

(User database 121)
The user database 121 stores various information about the user U. For example, the user database 121 stores various information such as the attributes of the user U. FIG. 5 is a diagram showing an example of the user database 121. In the example shown in FIG. 5, the user database 121 has a "user ID (Identifier)", "age", "gender", "home", "work location", "interest", "access log", and the like. Has an item.

The "user ID" indicates identification information for identifying the user U. Further, "age" indicates the age of the user U identified by the user ID. The "age" may be the specific age of the user U identified by the user ID, such as 35 years old. Further, "gender" indicates the gender of the user U identified by the user ID.

Further, "home" indicates the location information of the home of the user U identified by the user ID. In the example shown in FIG. 5, "home" is illustrated with an abstract code such as "LC11", but may be latitude / longitude information or the like. Further, for example, "home" may be an area name or an address.

Further, the "work location" indicates the location information of the work location (school in the case of a student) of the user U identified by the user ID. In the example shown in FIG. 5, the “work location” is illustrated by an abstract code such as “LC12”, but may be latitude / longitude information or the like. Further, for example, the "work location" may be a region name or an address.

Further, "interest" indicates an article or matter in which the user U identified by the user ID is currently interested or interested. For example, "interest" indicates a search query (search keyword) entered by the user U into a search engine or the like, a product posted in a clicked advertisement, a product purchased through electronic commerce, or the like. The number of "interests" may be plural. That is, one user U may use a plurality of services at the same time.

Further, the "access log" is an access log of the user U identified by the user ID, and indicates the access log of the user U acquired from each search server 200. The access log of each user U includes the location information of the terminal device 10 of each user U when the search is performed. Actually, the access log and the position information of the terminal device 10 may be linked. The location information is not limited to latitude / longitude and coordinates, but may be an area name or an address.

For example, in the example shown in FIG. 5, the age of the user U identified by the user ID "U1" is "20's", and the gender is "male". Further, for example, the user U identified by the user ID "U1" indicates that his / her home is "LC11". Further, for example, the user U identified by the user ID "U1" indicates that the work location is "LC12". Further, for example, it indicates that the user U identified by the user ID "U1" is interested in "interest # 11" and the access log is recorded in "log # 1". ..

Here, in the example shown in FIG. 5, although illustrated using abstract values such as "U1", "LC11", "LC12", "interest # 1" and "log # 1", "U1", It is assumed that information such as specific character strings and numerical values is stored in "LC11", "LC12", "interest # 1" and "log # 1". Hereinafter, abstract values may also be illustrated in figures relating to other information.

The user database 121 is not limited to the above, and various information may be stored depending on the purpose. For example, the user database 121 may store various information about the terminal device 10 of the user U. In addition, the user database 121 has attributes such as demographic (demographic attribute), psychographic (psychological attribute), geographic (geographical attribute), and behavioral (behavioral attribute) of user U. May remember information about. For example, the user database 121 includes name, family structure, occupation, position, income, qualification, living style (detached house, apartment, etc.), presence / absence of a car, commuting time, commuting route, commuter pass section (station). , Routes, etc.), Frequently used stations (other than the nearest station to your home / work location), Behavior history (Frequently used location information), Lessons (location, time zone, etc.), Hobbies, interests, lifestyle, etc. Information may be stored.

(Product Demand Database 122)
The product demand database 122 stores product demand information for each region. FIG. 6 is a diagram showing an example of the product demand database 122. In the example shown in FIG. 6, the product demand database 122 has items such as "region", "popular product", and "access count".

“Region” indicates a region that is a unit for totaling the number of accesses. For example, a "region" is a prefecture or municipality. The classification and scope of "region" is arbitrary. Further, for example, the "region" may be identification information for identifying a specific region.

In addition, "popular product" indicates a specific product that is popular in the area. The specific product that is popular in the area is, for example, a specific product in which the number of accesses is equal to or higher than the threshold value in the area. Further, for example, the "popular product" may be identification information for identifying a specific product.

In addition, "access count" indicates the number of accesses related to a specific product. The number of accesses related to a specific product includes, for example, the number of searches performed by inputting the name of the specific product as a search query, the number of accesses to web pages related to the specific product, and the specific product by electronic commerce. Includes the number of purchases, etc.

For example, in the example shown in FIG. 6, it is shown that the number of accesses related to the popular product “product # 11” in the area “region # 1” is “number of accesses # 11”. Further, it is shown that the number of accesses related to the popular product "Product # 11" in the area "Region # 2" is "Number of accesses # 21".

The product demand database 122 is not limited to the above, and various information may be stored depending on the purpose. For example, the product demand database 122 may store detailed information on the product. The detailed information of the product is, for example, the category and price of the product, the related product purchased / used together with the product, and the like. In addition, the product demand database 122 may store information regarding the ranking of popular products. The ranking of popular products is determined based on, for example, the number of accesses.

In addition, the product demand database 122 may store information regarding the breakdown of access. Information on the breakdown of access includes, for example, product purchase by electronic commerce, search by inputting a search query, click of an advertisement, and the like. Further, the number of accesses may be individually totaled for each attribute of each user U. Information such as whether it is popular with people with high purchasing power or whether it is popular with people with low purchasing power is also important.

(Product inventory database 123)
The product inventory database 123 stores product inventory information for each distribution base in each region. FIG. 7 is a diagram showing an example of the product inventory database 123. In the example shown in FIG. 7, the product inventory database 123 has items such as “region”, “distribution base”, “stored product”, and “inventory quantity”.

“Region” indicates the region where the distribution base is located. Further, for example, the "region" is a prefecture or a municipality. The classification and scope of "region" is arbitrary.

In addition, "distribution base" indicates a distribution base in each region. Further, for example, the “distribution base” may be identification information for identifying the distribution base in each region.

In addition, "stored product" indicates a product stored at the distribution base. Further, for example, the "stored product" may be identification information for identifying a specific product. In addition, "inventory quantity" indicates the inventory quantity of the product at the distribution base.

For example, in the example shown in FIG. 7, the distribution base in the region “region # 1” is “distribution base # 1”, and in the “distribution base # 1”, the stored product “product # 11” is “stock quantity # 11”. Indicates that only "is stored. In addition, the distribution base in the area "Region # 2" is "Distribution base # 2", and the stored product "Product # 11" is stored in "Distribution base # 2" only for "Inventory number # 21". Is shown.

The product inventory database 123 is not limited to the above, and various information may be stored depending on the purpose. For example, the product inventory database 123 may store information regarding the appropriate inventory of products. In addition, the product inventory database 123 may store information regarding the storage fee and storage period of the product at the distribution base. In addition, the product inventory database 123 may store information regarding the expiration date / expiration date of the product itself. In addition, the product inventory database 123 may store information regarding the upper limit of the quantity of products that can be stored at the distribution base. In addition, the product inventory database 123 may store information about products that can be accepted at the distribution base. The information on the acceptable product is, for example, information on a product that can be stored at room temperature, a product with a predetermined amount or less, or a product condition such as the size and weight of the product.

(Transport planning database 124)
The transportation plan database 124 stores various information related to a transportation plan for transporting a specific product to a distribution base in each region. FIG. 8 is a diagram showing an example of the transportation planning database 124. In the example shown in FIG. 8, the transportation planning database 124 has items such as “transportation destination”, “transportation product”, “transportation amount”, and “transportation schedule”.

“Destination” indicates a distribution base to which goods are transported. Further, for example, "transportation destination" indicates a distribution base with insufficient inventory. Further, the "transportation destination" may be identification information for identifying the distribution base which is the transportation destination to which the goods are sent.

In addition, "transportation product" indicates a product to be transported to a distribution base in each region. Further, for example, the "transported product" may be identification information for identifying the product to be transported to the distribution base of the transportation destination.

In addition, "transportation volume" indicates the number of products to be transported to the distribution base of the transportation destination. In addition, the "transportation schedule" indicates a schedule (date, date, date, etc.) for transporting goods to the distribution base of the transportation destination.

For example, in the example shown in FIG. 8, transportation in which the transportation product "product # 11" is transferred to the transportation destination "distribution base # 1" by the transportation amount "transportation amount # 1" at the date and time indicated by the transportation schedule "schedule # 1". Show that it is a plan. Indicates that the transportation plan is to transfer the transportation product "Product # 11" to the transportation destination "Distribution base # 2" by the transportation amount "Transportation amount # 2" at the date and time indicated by the transportation schedule "Schedule # 2".

The transportation planning database 124 is not limited to the above, and various information may be stored depending on the purpose. For example, the transportation planning database 124 may store information about a transportation source that ships a specific product to the destination of the product. In addition, the transportation plan database 124 may store information about a delivery company that executes a transportation plan for transporting goods to distribution bases in each region.

(Inventory transport planning database 125)
The inventory transportation plan database 125 stores various information related to the inventory transportation plan for transferring the inventory of goods between distribution bases in each region. FIG. 9 is a diagram showing an example of the inventory transportation planning database 125. In the example shown in FIG. 9, the inventory transfer planning database 125 has items such as "transport source", "transport destination", "transport product", "transport amount", and "transport schedule".

“Transport source” indicates a distribution base that is a source of transport of product inventory. Further, for example, "transportation source" indicates an inventory surplus distribution base. Further, the "transportation source" may be identification information for identifying the distribution base that is the transportation source for sending out the inventory of the product.

In addition, the “transportation destination” indicates a distribution base to which the inventory of goods is transported. Further, for example, “transportation destination” indicates a distribution base with insufficient inventory. Further, the "transportation destination" may be identification information for identifying a distribution base as a transportation destination for sending out the inventory of the product.

Further, the “transported product” indicates a product to be transported from the distribution base of the transportation source (surplus distribution base of inventory) to the distribution base of the transportation destination (distribution base of insufficient inventory). Further, for example, the "transported product" may be identification information for identifying the product to be transported from the distribution base of the transportation source to the distribution base of the transportation destination.

Further, the “transportation amount” indicates the number of products to be transported from the distribution base of the transportation source to the distribution base of the transportation destination. In addition, the “transportation schedule” indicates a schedule (date, date, date, etc.) for transporting products from the distribution base of the transportation source to the distribution base of the transportation destination.

For example, in the example shown in FIG. 9, the transportation product "product # 11" is transferred from the transportation source "distribution base # 1" to the transportation destination "distribution base # 2" by the transportation amount "transportation amount # 1", and the transportation schedule "schedule #". 1 ”indicates that the inventory transportation plan is to be transferred to the date and time indicated. In addition, the transportation product "product # 11" is transferred from the transportation source "distribution base # 3" to the transportation destination "distribution base # 2" at the date and time indicated by the transportation schedule "schedule # 2" by the transportation amount "transportation amount # 2". Indicates that the inventory transportation plan is to be replaced.

The inventory transfer planning database 125 is not limited to the above, and various information may be stored depending on the purpose. For example, the inventory transfer plan database 125 may store information about a delivery company that executes an inventory transfer plan for transferring inventory of goods from a distribution base of a transportation source to a distribution base of a transportation destination.

(Control unit 130)
Returning to FIG. 4, the description will be continued. The control unit 130 is a controller, and is an information processing device 100 using, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like. Various programs (corresponding to an example of an information processing program) stored in the internal storage device of the ASIC are executed by executing a storage area such as a RAM as a work area. In the example shown in FIG. 4, the control unit 130 includes a reception unit 131, an acquisition unit 132, a creation unit 133, a learning unit 134, and a provision unit 135.

(Reception Department 131)
The reception unit 131 receives the registration of various information about each user U from the terminal device 10 of each user U via the communication unit 110, and stores the registration in the user database 121.

(Acquisition unit 132)
The acquisition unit 132 acquires the access log of each user U from the search server 200 via the communication unit 110. The access log of each user U includes the location information of the terminal device 10 of each user U when the search is performed. Actually, the access log and the position information of the terminal device 10 may be linked. The location information is not limited to latitude / longitude and coordinates, but may be an area name or an address.

Further, the acquisition unit 132 acquires information on the inventory of a specific product at the distribution base in each region from the store S or the delivery company DC via the communication unit 110. The store S may be a retail store that sells a specific product, a manufacturing factory that manufactures a specific product, or a large-scale distribution facility of a delivery company DC. Further, the distribution base may be a warehouse of store S, a store of an affiliated store, or a sales office (directly managed store / distribution center / agency store) of a delivery company DC.

(Creation unit 133)
The creation unit 133 aggregates the number of accesses related to a specific product for each region based on the acquired access log of each user U, and creates product demand information for each region based on the aggregation result.

In addition, the creation unit 133 creates product inventory information for each distribution base in each region based on information on product inventory at distribution bases in each region.

In addition, the creation unit 133 creates a transportation plan for transporting a specific product to the distribution base in each region based on the product demand information for each region and the product inventory information for each distribution base in each region.

In addition, the creation unit 133 is based on the product demand information for each region and the product inventory information for each distribution base in each region, and the distribution base DB1 (non-demand area) in the region A in which access to a specific product is relatively low. A distribution plan is created to transfer the inventory of a specific product from the distribution base) to the distribution base DB2 (demand area distribution base) in the area B where the access for the specific product is relatively high.

(Learning Department 134)
The learning unit 134 inputs the number of accesses related to a specific product into the model, and learns the appropriate stock of the specific product as correct answer data. Then, the learning unit 134 calculates the appropriate inventory of the specific product by inputting the number of accesses related to the specific product into the learned model. That is, the learning unit 134 also functions as a calculation unit for calculating the appropriate inventory of a specific product.

Further, the learning unit 134 may input the product demand information for each region and the product inventory information for each distribution base in each region into the model, and learn the transportation plan and / or the inventory transportation plan as correct answer data. Then, the learning unit 134 acquires the transportation plan and / or the inventory transportation plan by inputting the product demand information for each region and the product inventory information for each distribution base in each region into the learned model. In this case, the learning unit 134 may be integrated with the creating unit 133.

The learning is, for example, deep learning (deep learning) using a deep neural network (DNN). Data mining and other machine learning algorithms may also be used. The learning unit 134 learns the model by the various learning methods described above.

Any type of model can be adopted as the model. For example, the information processing apparatus 100 may use an SVM (Support Vector Machine) or a DNN (Deep Neural Network) as a model. Here, the DNN may be a CNN (Convolutional Neural Network) or an RNN (Recurrent Neural Network). Further, the RNN may be an LSTM (Long short-term memory) or the like. That is, any type of model can be adopted as the model. Further, the model may be a model realized by combining a plurality of models, for example, a model in which a CNN and an RNN are combined.

(Providing section 135)
The providing unit 135 provides the created transportation plan and / or inventory transportation plan to the business operator of the store S and the delivery company DC via the communication unit 110.

Further, the providing unit 135 provides the business operator of the store S and the delivery company DC with the product demand information for each region and / or the product inventory information for each distribution base in each region via the communication unit 110. May be good.

Further, the providing unit 135 may provide a function of searching the content to the terminal device 10 of each user U via the communication unit 110.

[4. Processing procedure]
Next, the processing procedure by the information processing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 10 is a flowchart showing a processing procedure according to the embodiment. The processing procedure shown below is repeatedly executed by the control unit 130 of the information processing apparatus 100.

The control unit 130 of the information processing device 100 acquires the access log of each user U from the search server 200 via the communication unit 110 (step S101).

The access log of each user U includes the location information of the terminal device 10 of each user U when the search is performed. Actually, the access log and the position information of the terminal device 10 may be linked. The location information is not limited to latitude / longitude and coordinates, but may be an area name or an address.

The control unit 130 aggregates the number of accesses related to a specific product for each region based on the access log of each user U, and creates product demand information for each region based on the aggregated result (step S102). ..

The control unit 130 collects information regarding the inventory of specific products at the distribution bases in each region from the store S and the delivery company DC via the communication unit 110 (step S103).

The control unit 130 creates product inventory information for each distribution base in each region based on the collected information (step S104).

The control unit 130 determines the distribution base in the region where the demand for the product is predicted based on the product demand information for each region (step S105).

The control unit 130 calculates an appropriate inventory of a specific product at a distribution base in each region in order to optimize the number of stocks of a specific product at the distribution base in each region based on the product demand information for each region (step). S106).

The control unit 130 creates a transportation plan for transporting a specific product to the distribution base in each region based on the product inventory information for each distribution base in each region and the appropriate inventory of the specific product in the distribution base in each region. (Step S107).

Further, the control unit 130 is based on the product demand information for each region and the product inventory information for each distribution base in each region, and the distribution base DB1 (non-demand area) in the region A in which access to a specific product is relatively small. An inventory transportation plan for transferring the inventory of a specific product from the distribution base) to the distribution base DB2 (demand area distribution base) in the area B where the access for the specific product is relatively high is created (step S108).

The control unit 130 provides the created transportation plan and / or inventory transportation plan to the business operator (retailer or the like) of the store S or the delivery company DC via the communication unit 110 (step S109).

[5. Modification example]
The terminal device 10 and the information processing device 100 described above may be implemented in various different forms other than the above-described embodiment. Therefore, a modified example of the embodiment will be described below.

In the above embodiment, based on information on the place where each user U made an electronic payment using the terminal device 10 (location of an actual store, etc.) and the number of payments at that place (aggregation of payment information, etc.). Therefore, product demand information for each region may be created. For example, in a certain area, when each user U purchases a specific product by electronic payment, the location of the actual store where each user U purchased the specific product in the area and each actual in the area. The number of payments for a specific product at a store may be aggregated to create product demand information for that region.

Further, in the above embodiment, the information processing apparatus 100 is newly added when an appropriate distribution base DB2 (demand area distribution base) does not exist in the area B where the specific product shown in the example of FIG. 1 is accessed relatively frequently. It may be proposed to the business operator of the store S or the delivery company DC to provide the distribution base DB2 in the store S.

Further, in the above embodiment, when the information processing apparatus 100 has a plurality of regions B having relatively high access to the specific product shown in the example of FIG. 1, and the regions B are adjacent to each other, those regions The optimum distribution base DB2 may be selected from the plurality of distribution bases in B. That is, one distribution base DB2 that is the core of delivery to a plurality of regions B may be selected.

Further, in the above embodiment, when the information processing apparatus 100 has a plurality of regions B having relatively high access to the specific product shown in the example of FIG. 1 and the regions B are separated from each other, the demand trend. Accordingly, a transportation plan may be created showing the optimum transportation route connecting the distribution bases DB2 in each area B. At this time, for example, a transportation plan showing the optimum transportation route may be created by using the method of the traveling salesman problem. Similarly, in the example shown in FIG. 2, an inventory transportation plan showing an optimum inventory transportation route connecting the distribution bases DB2 in each area B may be created.

Further, in the above embodiment, the information processing apparatus 100 is assigned to the distribution base DB 1 in the area A where the access to the specific product is relatively small and the area B where the access to the specific product is relatively large as shown in the example of FIG. When there are a plurality of physical distribution base DB2s, a transportation plan may be created that shows an optimum transportation route connecting the physical distribution bases according to a demand trend. At this time, for example, a transportation plan showing the optimum transportation route may be created by using the method of the traveling salesman problem. Similarly, in the example shown in FIG. 2, an inventory transportation plan showing an optimum inventory transportation route connecting distribution bases may be created.

Further, in the above embodiment, the information processing apparatus 100 is transferred from the distribution base DB1 (non-demand area distribution base) in the area A where the access to the specific product shown in the example of FIG. 2 is relatively small to another non-demand area. An inventory transportation plan may be created to transfer the inventory of a specific product to a distribution base. Similarly, the information processing apparatus 100 is an inventory that transfers the inventory of a specific product from the distribution base DB2 (demand area distribution base) in the area B where the access to the specific product is relatively high to another demand area distribution base. A transport plan may be created.

Further, in the above embodiment, the information processing apparatus 100 may further create a transportation plan showing an optimum transportation route connecting the distribution bases according to the distance between the distribution bases. Similarly, in the example shown in FIG. 2, an inventory transportation plan showing an optimum inventory transportation route connecting the distribution bases may be created according to the distance between the distribution bases.

Further, in the above embodiment, the information processing apparatus 100 selects a plurality of distribution bases DB2 (demand area distribution bases) in the area B where the specific products shown in the examples of FIGS. 1 and 2 are relatively frequently accessed. The inventory of specific products may be distributed to each distribution base DB2 in advance. For example, if a specific product is concentrated in one distribution base DB2, it is expected that a queue will be generated at that distribution base and a congestion of a delivery route from that distribution base will occur as demand is generated / increased. .. In addition, if a problem occurs in the distribution base or delivery route, delivery of a specific product may be delayed. Therefore, the inventory of specific products is distributed to a plurality of distribution base DB2s in advance, and the specific products are efficiently delivered from each distribution base DB2 according to the generation / increase of demand. That is, the distribution base DB2 (demand area distribution base) in the area B where the access to a specific product is relatively high does not have to be one place.

Further, in the above embodiment, the information processing apparatus 100 may acquire log data indicating the behavior of the user in each region from the log server instead of the search server 200. For example, the log server acquires the position history, which is the history of the user's position, from the terminal device 10. In addition, the log server acquires the search history, which is the history of the search query input by the user, from the search server. In addition, the log server acquires the browsing history, which is the history of the content browsed by the user, from the content server. In addition, the log server acquires the purchase history, which is the purchase history by the user, from the electronic commerce server or the electronic payment server. In addition, the log server acquires the posting history, which is the history of posting by the user, from the posting server or the SNS (Social Networking Service) server that provides the word-of-mouth posting service. The log server can acquire various types of information in addition to the above-mentioned information. For example, a log server acquires information about user attributes such as age, gender, family structure, and financial status of the user. Then, the information processing apparatus 100 acquires the above-mentioned various log data from the log server, aggregates the number of log data (or the number of accesses to the network) related to a specific product for each region, and based on the aggregated result. , Product demand information for each region may be created. In this case, in the above embodiment, "access related to a specific product" may be read as "log data related to a specific product". Further, "number of accesses" may be read as "number of log data".

[6. effect〕
As described above, the information processing apparatus 100 according to the present application demands products for each region based on the place where each user's action related to the product is performed and the number of actions performed at the place. It has a product demand information creation department that creates product demand information that shows the trends of the product, and a distribution base determination department that determines the distribution base of the product based on the product demand information. As a result, the distribution base can be adjusted according to the demand forecast.

Further, the information processing apparatus 100 according to the present application further includes a transportation plan creation unit that creates a transportation plan for transporting the product to the distribution base of the product in advance based on the product demand information. As a result, it is possible to create an optimal transportation plan according to the demand forecast.

Further, the information processing apparatus 100 according to the present application creates an inventory transportation plan for transferring the product inventory from another distribution base in which the product is in stock to the product distribution base in advance based on the product demand information. It also has a planning department. As a result, inventory can be appropriately transferred between distribution bases according to the demand forecast.

Further, the information processing apparatus 100 according to the present application is based on the acquisition unit for acquiring information on the inventory of products at the distribution bases in each region and the information on the inventory of products at the distribution bases in each region, for each distribution base in each region. It also has a product inventory information creation unit that creates the product inventory information of. As a result, it is possible to grasp the inventory of products at the distribution bases in each region.

Further, the information processing apparatus 100 according to the present application further includes an inventory quantity calculation unit that calculates the inventory quantity according to the demand for products for each distribution base in each region based on the product demand information. As a result, it is possible to grasp the appropriate inventory of products for each distribution base in each region.

Further, the information processing apparatus 100 according to the present application further includes a transportation plan creation unit that creates a transportation plan for transporting the products in advance to the distribution base where the inventory of the products does not reach the above-mentioned inventory quantity. As a result, it is possible to create an efficient transportation plan on the condition that the appropriate inventory is not reached according to the demand forecast.

Further, the information processing apparatus 100 according to the present application is an inventory that transfers the inventory of products in advance from a distribution base in which the inventory of products exceeds the above-mentioned inventory quantity to a distribution base in which the inventory of products does not reach the above-mentioned inventory quantity. It also has an inventory transport plan creation unit that creates a transport plan. As a result, inventory can be transferred between distribution bases based on the appropriate inventory according to the demand forecast for each distribution base in each region.

Further, the information processing apparatus 100 according to the present application further includes a learning unit that inputs product demand information into a model and learns the stock quantity as correct answer data. As a result, machine learning about appropriate inventory can be performed by inputting product demand information for each region.

For example, an action is a search performed by entering a search query related to a product. The action is also access to a web page related to the product. The action is the purchase of goods through electronic commerce. This makes it possible to detect an increase in the number of Internet accesses in a certain area and predict the occurrence of demand in that area.

Alternatively, the action is the purchase of goods by electronic payment. As a result, it is possible to detect an increase in the number of electronic payments at a physical store or the like in a certain area and predict the occurrence of demand in that area.

[7. Hardware configuration]
Further, the terminal device 10 and the information processing device 100 according to the above-described embodiment are realized by, for example, a computer 1000 having a configuration as shown in FIG. Hereinafter, the information processing apparatus 100 will be described as an example. FIG. 11 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to the output device 1010 and the input device 1020, and the arithmetic unit 1030, the primary storage device 1040, the secondary storage device 1050, the output I / F (Interface) 1060, the input I / F 1070, and the network I / F 1080 are bused. It has a form connected by 1090.

The arithmetic unit 1030 operates based on a program stored in the primary storage device 1040 or the secondary storage device 1050, a program read from the input device 1020, or the like, and executes various processes. The arithmetic unit 1030 is realized by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used by the arithmetic unit 1030 for various calculations. Further, the secondary storage device 1050 is a storage device in which data used by the calculation device 1030 for various calculations and various databases are registered, and is a ROM (Read Only Memory), an HDD (Hard Disk Drive), and an SSD (Solid). State Drive), flash memory, etc. The secondary storage device 1050 may be internal storage or external storage. Further, the secondary storage device 1050 may be a removable storage medium such as a USB memory or an SD (Secure Digital) memory card. Further, the secondary storage device 1050 may be a cloud storage (online storage), NAS (Network Attached Storage), a file server, or the like.

The output I / F 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various information such as a display, a projector, and a printer. For example, USB (Universal Serial Bus) or DVI. (Digital Visual Interface), HDMI (registered trademark) (High Definition Multimedia Interface), etc. are realized by standard connectors. The input I / F 1070 is an interface for receiving information from various input devices 1020 such as a mouse, keyboard, keypad, buttons, and a scanner, and is realized by, for example, USB.

Further, the output I / F 1060 and the input I / F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, the output device 1010 and the input device 1020 may be wireless devices.

Further, the output device 1010 and the input device 1020 may be integrated like a touch panel. In this case, the output I / F 1060 and the input I / F 1070 may also be integrated as input / output I / F.

The input device 1020 is, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), or a tape. It may be a device that reads information from a medium, a magnetic recording medium, a semiconductor memory, or the like.

The network I / F 1080 receives data from another device via the network N and sends it to the arithmetic unit 1030, and also transmits the data generated by the arithmetic unit 1030 to the other device via the network N.

The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output I / F 1060 and the input I / F 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040, and executes the loaded program.

For example, when the computer 1000 functions as the information processing device 100, the arithmetic unit 1030 of the computer 1000 realizes the function of the control unit 130 by executing the program loaded on the primary storage device 1040. Further, the arithmetic unit 1030 of the computer 1000 may load a program acquired from another device via the network I / F 1080 onto the primary storage device 1040 and execute the loaded program. Further, the arithmetic unit 1030 of the computer 1000 may cooperate with other devices via the network I / F 1080 to call the functions and data of the program from other programs of the other devices and use them.

[8. others〕
Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. In addition, the above-mentioned components include those that can be easily assumed by those skilled in the art, those that are substantially the same, that is, those in a so-called equal range. Furthermore, the components described above can be combined as appropriate. Further, various omissions, replacements or changes of the components can be made without departing from the gist of the above-described embodiment.

Further, among the processes described in the above-described embodiment, all or a part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed can be performed. All or part of it can be done automatically by a known method. In addition, the processing procedure, specific name, and information including various data and parameters shown in the above document and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

Further, each component of each of the illustrated devices is a functional concept, and does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or part of the device is functionally or physically dispersed / physically distributed in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

For example, the information processing device 100 described above may be realized by a plurality of server computers, or may be realized by calling an external platform or the like by API (Application Programming Interface), network computing, or the like depending on the function. Can be changed flexibly.

Further, the above-described embodiments and modifications can be appropriately combined as long as the processing contents do not contradict each other.

Further, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the acquisition unit can be read as an acquisition means or an acquisition circuit.

1 Information processing system 10 Terminal equipment 100 Information processing equipment 110 Communication unit 120 Storage unit 121 User database 122 Product demand database 123 Product inventory database 124 Transportation planning database 125 Inventory transportation planning database 130 Control unit 131 Reception unit 132 Acquisition unit 133 Creation unit 134 Learning Department 135 Providing Department 200 Search Server

Claims (14)

Product demand for creating product demand information showing trends in demand for the product in each region based on the place where each user's action related to the product was performed and the number of the actions performed at the location. Information creation department and
The distribution base determination department that determines the distribution base of the product based on the product demand information,
An information processing device characterized by being equipped with. The information processing apparatus according to claim 1, further comprising a transportation plan creation unit that creates a transportation plan for transporting the product in advance to the distribution base of the product based on the product demand information. Based on the product demand information, it is further provided with an inventory transportation plan creation unit that creates an inventory transportation plan for transferring the inventory of the product from another distribution base in which the product is in stock to the distribution base of the product in advance. The information processing apparatus according to claim 1 or 2, wherein the information processing device is characterized by the above. The acquisition department that acquires information on the inventory of the products at distribution bases in each region,
Of claims 1 to 3, further comprising a product inventory information creation unit that creates product inventory information for each distribution base in each region based on information on the inventory of the products at the distribution bases in each region. The information processing device according to any one. The information processing apparatus according to claim 4, further comprising an inventory quantity calculation unit that calculates an inventory quantity according to the demand for the product for each distribution base in each region based on the product demand information. The information processing apparatus according to claim 5, further comprising a transportation plan creating unit for creating a transportation plan for transporting the product in advance to a distribution base where the inventory of the product has not reached the inventory quantity. An inventory transportation plan for creating an inventory transportation plan for transferring the inventory of the product in advance from a distribution base where the inventory of the product exceeds the inventory quantity to a distribution base where the inventory of the product does not reach the inventory quantity. The information processing apparatus according to claim 5 or 6, further comprising a creating unit. The information processing apparatus according to any one of claims 5 to 7, further comprising a learning unit for inputting the product demand information into a model and learning the stock quantity as correct answer data. The information processing apparatus according to any one of claims 1 to 8, wherein the action is a search performed by inputting a search query related to the product. The information processing device according to any one of claims 1 to 9, wherein the action is an access to a web page related to the product. The information processing device according to any one of claims 1 to 10, wherein the action is the purchase of the product by electronic commerce. The information processing device according to any one of claims 1 to 11, wherein the action is the purchase of the product by electronic payment. It is an information processing method executed by an information processing device.
Product demand for creating product demand information showing trends in demand for the product in each region based on the place where each user's action related to the product was performed and the number of the actions performed at the location. Information creation process and
A distribution base determination process for determining a distribution base for the product based on the product demand information,
An information processing method characterized by including. Product demand that creates product demand information showing trends in demand for the product in each region based on the location where each user's action related to the product was performed and the number of the actions performed at the location. Information creation procedure and
A distribution base determination procedure for determining a distribution base for the product based on the product demand information, and a distribution base determination procedure.
An information processing program that allows a computer to execute.

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