JP7361084B2 - Information processing device, information processing method, and information processing program - Google Patents

Description

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

A technique has been disclosed that makes it possible to suitably provide property information depending on the content of an image (see Patent Document 1). Furthermore, a technique for obtaining an aesthetic score of an image has been disclosed (see Non-Patent Document 1).

JP2017-097722A

The feeling of "beautiful" can finally be quantified. Google announces “NIMA” image evaluation technology using AI Gizmodo Japan <URL: https://www.gizmodo.jp/2017/12/google-nima.html>

However, the above-mentioned conventional technology has room for improvement in terms of supporting searches for users to obtain more useful information. Therefore, there is a demand for creating search conditions that can provide more useful information to users.

The present application has been made in view of the above, and aims to create search conditions for providing useful information to users.

The information processing device according to the present application determines the tendency of the objects in the images of the property viewed by the user from the common points of each of the plurality of images of different objects viewed by the user among the images registered for each property. a generation unit that generates a search condition for searching for a property based on the tendency of the object in the image of the specified property ; The present invention is characterized by comprising a providing unit that presents the user with objects whose images have high aesthetic appeal .

According to one aspect of the embodiment, search conditions for providing useful information to a user can be created.

FIG. 1 is an explanatory diagram showing an overview of an information processing method according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of an information processing system according to an embodiment. FIG. 3 is a diagram illustrating a configuration example of a terminal device according to an embodiment. FIG. 4 is a diagram illustrating a configuration example of an information providing apparatus according to an embodiment. FIG. 5 is a diagram showing an example of a user information database. FIG. 6 is a diagram showing an example of a history information database. FIG. 7 is a diagram showing an example of a property image information database. FIG. 8 is a flowchart showing the processing procedure according to the embodiment. FIG. 9 is a diagram showing an example of the hardware configuration.

DESCRIPTION OF THE PREFERRED EMBODIMENTS An information processing apparatus, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail below with reference to the drawings. Note that the information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. In addition, in the following embodiments, the same parts are given the same reference numerals, and redundant explanations will be omitted.

[1. Overview of information processing method]
First, with reference to FIG. 1, an overview of an information processing method performed by an information processing apparatus according to an embodiment will be described. FIG. 1 is an explanatory diagram showing an overview of an information processing method according to an embodiment. In FIG. 1, an example will be described in which tags indicating the characteristics of the image that the user is viewing are aggregated, and corresponding search conditions are generated based on the aggregated results and presented to the user as particular conditions.

As shown in FIG. 1, the information processing system 1 includes a terminal device 10 and an information providing device 100. The terminal device 10 and the information providing device 100 are connected to be able to communicate with each other by wire or wirelessly via a network N (see FIG. 2). In this embodiment, the terminal device 10 cooperates with the information providing device 100.

The terminal device 10 is a smart device such as a smartphone or a tablet used by a user U (user), and can communicate with any server device via a wireless communication network such as 4G (Generation) or LTE (Long Term Evolution). This is a mobile terminal device that can perform Further, the terminal device 10 has a screen such as a liquid crystal display, which has a touch panel function, and displays data such as content through a tap operation, a slide operation, a scroll operation, etc. from the user U using a finger or a stylus. Accepts various operations on. Note that an operation performed on an area of the screen where 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 information providing device 100 cooperates with the terminal device 10 of each user U, and provides API (Application Programming Interface) services for various applications (hereinafter referred to as applications), etc., to the terminal device 10 of each user U, and various It is an information processing device that provides data, and is realized by a server device, a cloud system, etc.

Further, the information providing device 100 may be an information processing device that provides some kind of web service online to the terminal device 10 of each user U. For example, the information providing device 100 provides web services such as Internet connection, search service, SNS (Social Networking Service), electronic commerce (EC), electronic payment, online games, online banking, online trading, accommodation and ticket reservations. , video/music distribution, news, maps, route searches, route guidance, route information, operation information, weather forecasts, and other services may be provided. In reality, the information providing apparatus 100 may cooperate with various servers that provide the above-mentioned Web services, mediate the Web services, or may be in charge of processing the Web services.

Note that the information providing device 100 can acquire user information regarding the user U. For example, the information providing device 100 acquires information regarding attributes of the user U, such as the user's U's gender, age, and area of residence. Then, the information providing device 100 stores and manages information regarding attributes of the user U along with identification information indicating the user U (user ID, etc.).

Further, the information providing device 100 acquires various kinds of history information (log data) indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user ID or the like. For example, the information providing device 100 acquires a location history, which is a history of the user U's location, date and time, from the terminal device 10. The information providing device 100 also acquires a search history, which is a history of search queries input by the user U, from a search server (search engine). The information providing device 100 also acquires a viewing history, which is a history of content viewed by the user U, from the content server. Further, the information providing device 100 acquires a purchase history (payment history) that is a history of product purchases and payment processing by the user U from the electronic commerce server and the payment processing server. Further, the information providing device 100 may acquire the listing history and the sales history, which are the listing history of the user U on the marketplace, from the electronic commerce server or the payment server. The information providing device 100 also acquires a posting history, which is a history of postings by the user U, from a posting server or SNS server that provides a word-of-mouth posting service.

In the present embodiment, the information providing device 100 generates search conditions (search axes) from a different perspective than before from the analysis results of the image of the property that the user U is viewing, and uses the search conditions as the user U's particular criteria. , a property related to the generated search condition is determined as a property to be listed and presented to the user. At this time, the information providing apparatus 100 may create a property list based on the aesthetic score of the image of the property, such as "the exterior is beautiful" and "the plumbing is beautiful".

For example, as shown in FIG. 1, the information providing device 100 accepts viewing of an image of a property from the terminal device 10 of the user U via the network N (see FIG. 2) (step S1).

Subsequently, the information providing device 100 calculates the aesthetic score of the image of the property that the user U is viewing (step S2).

Subsequently, the information providing device 100 estimates the commonality of the characteristics of the images of the properties that the user U is viewing (step S3).

Subsequently, the information providing apparatus 100 generates search conditions based on the commonality of the features of the images (step S4).

Subsequently, the information providing device 100 determines a property related to the search condition as a property to be listed (step S5).

Subsequently, the information providing device 100 presents information regarding the determined property (listed property) to the terminal device 10 of the user U (step S6).

[1-1. Special condition assist based on viewed images]
In this embodiment, the information providing device 100 aggregates tags (or labels) indicating the characteristics of the image the user is viewing, generates corresponding search conditions based on the aggregate results, and presents the search conditions to the user as particular conditions. . At this time, the information providing device 100 extracts and tags the points of interest from the image, aggregates the tags of the image the user is viewing, determines it to be a particular condition, and generates a search condition corresponding to the tag. , presents properties related to the search conditions.

For example, for a user who is viewing only images of tower apartments, the information providing device 100 may add an internal score (score indicating the degree of interest) to determine the user's interest, and add "Popular tower condominium images" to the user. Generates the search condition "Apartment". Then, the information providing device 100 presents properties with high image aesthetic scores (above a threshold value, within the top 10, etc.) among the properties according to the search conditions.

In addition, for users who only view images of water areas such as kitchens, toilets, bathrooms, washrooms, etc., an internal score (score indicating the degree of interest) is added to determine interest. to generate the search condition ``The water area is clean.'' Then, the information providing device 100 presents properties with high aesthetic scores for images of water areas (above a threshold, within the top 10, etc.) among properties that meet the search conditions. In this way, the information providing apparatus 100 assists the generation of particular conditions based on the image that the user is viewing.

Note that "the user is viewing" includes not only displaying or viewing thumbnails, but also the act of viewing an enlarged image by selection such as clicking. Furthermore, in order to determine whether the user is viewing the image, the information providing device 100 estimates whether the user has viewed the image based not only on the user's log of clicks, etc., but also based on the content of the scrolling operation, etc. , processing may be performed based on the estimation results.

Furthermore, "presenting the property to the user" includes the information providing device 100 providing images and detailed information of the property to the user's terminal device 10 via the network N (see FIG. 2). The property is real estate, housing, etc. Images of properties include not only indoor images (indoors, interiors, inner walls, floor plans, etc.) of buildings such as real estate and residences, but also outdoor images (overview, external appearance, external walls, garden, neighborhood, etc.).

The building is, for example, a housing complex such as a condominium or apartment, or a detached house. It can be a rental home, a condominium, or a built home. Also, it may be a newly built house or a used house. In reality, buildings include office buildings such as companies, commercial facilities such as stores, accommodation facilities such as hotels, educational institutions such as schools, medical institutions such as hospitals, research institutions such as laboratories, and industrial facilities such as factories. It may also be a logistics base such as a plant or a distribution center. In addition, large commercial facilities (shopping centers/outlet malls/underground malls), entertainment facilities (theme parks/amusement parks/playgrounds/zoos/aquariums/pools/bathing facilities), and cultural facilities (halls/theaters/libraries/art galleries/museums) , a complex facility, a sports facility, a temple or shrine, a service area (SA), a parking area (PA), a railway station, a roadside station, an airport, a port (boarding area), etc.

Furthermore, buildings have spaces partitioned by walls, partitions, floors, ceilings, and the like. These spaces include, for example, rooms in a building, entrances, hallways, kitchens, baths, toilets, elevators, stairs, passages, garages, warehouses, barns, storerooms, and the like. Rooms are not limited to private rooms, but also include living rooms, studies, lounges, etc. The entrance includes the lobby and entrance. That is, a space is a place where people stay, enter, exit, or pass through. The space may be a place where people live or work, or a place where goods used by people are stored. Moreover, in a building, there may be one space or a plurality of spaces. Furthermore, the space is not limited to, for example, a room in a building, but may also be a cabin of a vehicle, ship, aircraft, or the like. That is, the space is not limited to a space where people live indoors such as a house, but may also be a space where crew members and passengers spend time in a car, express bus, train, large cruise ship, airplane, etc. In other words, the space may be a living space inside a building or a moving object.

Note that the property is not limited to a building, and may be a tourist spot, a park, a waterside (the sea, a river, a lake, etc.), a campsite, a mountain forest, a tunnel, a cave, etc. Furthermore, even outdoors, there are spaces partitioned off by obstacles such as walls, buildings, other structures, and natural objects. Further, the space is not limited to a partitioned space, but may be a space within a predetermined range centered on a certain point.

[1-2. Generating search conditions from image analysis results]
The information providing device 100 analyzes the images linked to the property and creates search conditions based on the object in the image and the characteristics of the image or object obtained as a result of the analysis of the image or object. (search conditions) and present them to the user.

For example, if the object of the image is an "image of the exterior" and the image is viewed by many users/viewed for a large number of times, the information providing apparatus 100 generates a search condition of "property with popular exterior". Furthermore, when the object of the image is an "image of a view" and the aesthetic score of the image is high, the information providing device 100 generates a search condition of "property with a beautiful (good) view."

In addition, the information providing device 100 is configured such that the object of the image is an "image of a water area" such as a kitchen, toilet, bathroom, or washroom, and the image has a high aesthetic score and is viewed by a large number of users. If so, select the search condition ``properties with clean plumbing.'' At this time, the information providing device 100 specifically identifies the target object in the image that the user is viewing, and selects "property with a clean kitchen," "property with a clean toilet," and "property with a clean bathroom." Alternatively, search conditions such as "properties with clean washrooms" may be selected. That is, there are categories such as kitchen, toilet, bathroom, washroom, etc., and there is also a higher-level category "Water area", and it is possible to select search conditions for each category.

Alternatively, if the object of the image is a "storage image" such as a closet, closet, trunk room, etc., and the number of views by the user is large, the information providing device 100 selects the search condition "property with ample storage". Good too. Furthermore, if the image has a high aesthetic score and has been viewed by many users, the information providing device 100 may select the search condition of "property with beautiful storage."

Furthermore, if the object of the image is an "image of the exterior" or "image of the interior" of a used property, the aesthetic score of the image is high, and the number of views by the user is large, the information providing device 100 displays " A search condition such as "property renovated within the past three years" may be generated.

Note that the information providing apparatus 100 may classify images into "beautiful", "cool", etc. through crowdsourcing or the like, and may reflect this as the name of the search condition. For example, the information providing apparatus 100 may have the user manually classify images into "beautiful", "cool", etc., and may reflect this as the name of the search condition. Further, the information providing device 100 may aggregate the tags (or labels) such as "beautiful" and "cool" specified by each user for the image, and classify the tags into the category of the tag specified most frequently. Further, the information providing device 100 may combine word-of-mouth information about the property and comments from the trader and weight the certainty of the feature (adding points if the property has a "good view", etc.).

[1-3. Creation of property list based on aesthetic score]
The information providing device 100 analyzes images linked to properties and determines properties to be listed based on the object in the image and the aesthetic score of the image. For example, the information providing device 100 uses a model to select images that correspond to the "property appearance", takes the aesthetic score of each, and selects properties with images with high scores (within top XXX, above a threshold, etc.). The property to be listed.

Properties to be listed include, for example, "properties with cool exteriors," "properties with beautiful views," "properties with beautiful plumbing," and "properties that have been renovated within the past three years."

It should be noted that relatively more properties that are 30 years old or older have low aesthetic scores. Additionally, properties that are over 30 years old may be avoided even if they have a high aesthetic score. Therefore, the information providing device 100 may exclude properties that are 30 years old or older regardless of the aesthetic score. In this case, the information providing device 100 obtains information that the property is 30 years or older from the property information of the property or by combining information included in the property information. Furthermore, regarding the aesthetics of an object, things such as "beautiful" based on an individual's sense (subjectivity) may be defined by a person, regardless of the aesthetic score.

(Aesthetic score according to this embodiment)
As the aesthetic score according to the present embodiment, the information providing device 100 calculates a score that takes into account both the technical aspects (image quality, etc.) and the aesthetic aspects (image content, etc.) of the image of the property, unlike conventional methods. . The aesthetic score according to this embodiment takes a value of 1 to 10. Although it depends on the domain of the data, as a guideline for the aesthetic score, 5.0 or less is considered low, and 5.5 or more is considered high. Note that if it is greater than 5.0 and less than 5.5, it is determined to be normal. The aesthetic score according to this embodiment is assumed to be used when it is desired to select only high-quality images from an unspecified number of images.

In this way, the information providing device 100 performs image analysis of properties and automatically generates classifications of properties such as those with cool appearance. That is, the information providing apparatus 100 performs category classification of images. For example, the information providing device 100 classifies images of properties into categories such as "water area", "exterior", "view", "cool", and "beautiful".

At this time, the information providing device 100 evaluates the "cleanliness of water areas", "beautiful appearance", etc. of the classified images based on the aesthetic score related to "cleanliness", and groups the evaluation results. The property is then proposed to the user as a "property with beautiful properties." As a result, the information providing device 100 can provide properties with good cost performance, such as properties with clean plumbing such as kitchens even though they are used properties. The information providing device 100 determines which property images to classify into what kind of property based on rules.

Furthermore, when presenting an image of the exterior of a property, for example, the information providing device 100 excludes images of the exterior of a property that is 30 years old or older from being presented. The property may be a single-family house or a rental condominium/apartment.

Furthermore, if the information providing device 100 is old and has a poor exterior aesthetic score but a high interior aesthetic score, it is determined that the value of renovation is high. The information providing device 100 can suggest a property as a recommended property if the property has a high renovation value and the rent etc. are lower than the market price due to the age of the property. Furthermore, the information providing device 100 can perform a relative evaluation of each part of each property, such as whether the interior is clean or the kitchen and other plumbing areas are clean.

At this time, the information providing device 100 determines whether to classify the image based on the relative difference in aesthetic scores. Note that the information providing device 100 may calculate the aesthetic score using the image of the property as it is, or may apply lens correction to the image of the property to calculate the aesthetic score in its actual state.

Note that the information providing device 100 creates a model for estimating and classifying a category for each property image based on a combination of the property image and a category (for example, “beautiful exterior”) resulting from the image classification. / May be updated. Further, the information providing apparatus 100 may create a model for each attribute of the target property or for each user attribute.

Furthermore, the information providing device 100 estimates the user's preference conditions based on the commonality of characteristics (for example, "beautiful exterior") of properties that the user often views (frequently), and calculates the estimated preference conditions. Suggest properties that match your criteria.

For example, the information providing device 100 determines "location", "tower apartment", "rent/price", "5th floor", "location", "tower apartment", "rent/price", "5th floor It estimates whether the user is interested in the following, ``Has a garden,'' ``Size of balcony,'' ``Year of construction,'' etc. Alternatively, the information providing device 100 estimates whether the user is interested in "water" as a feature of each part of the property.

Then, the information providing device 100 displays an image of the appearance of the property when the user is interested in the entire property (the property itself), or an image of that part when the user is interested in a specific part (part) of the property. Present beautiful properties (properties with high aesthetic scores).

Further, the information providing device 100 may propose an AND condition (combination) of tags. For example, if the information providing device 100 estimates that the user is interested in the "bath" and "exterior" of the property from the image of the property that the user is viewing, the information providing device 100 may determine that the "bath" and "exterior" are both beautiful. Suggest properties.

Furthermore, the information providing apparatus 100 may increase the threshold value for determining a property to be proposed. For example, if the information providing device 100 estimates that the user is interested in "clean restrooms," it sets the aesthetic score threshold for "toilet" higher than normal (or average) and suggests properties that are higher than the threshold value. You can do it like this.

[2. Configuration example of information processing system]
Next, the configuration of the information processing system 1 including the information providing apparatus 100 according to the embodiment will be described using FIG. 2. FIG. 2 is a diagram showing a configuration example of the information processing system 1 according to the embodiment. As shown in FIG. 2, the information processing system 1 according to the embodiment includes a terminal device 10 and an information providing device 100. These various devices are connected via a network N so that they can communicate 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.

Furthermore, the number of devices included in the information processing system 1 shown in FIG. 2 is not limited to what is illustrated. For example, in FIG. 2, only one terminal device 10 is shown for simplification of illustration, but this is just an example and is not limited, and there may be two or more terminal devices.

The terminal device 10 is an information processing device used by the user U. For example, the terminal device 10 may be a smart device such as a smartphone or a tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a game console or AV device with a communication function, a car navigation system, a smart watch, or the like. These include wearable devices such as head-mounted displays, smart glasses, etc.

The terminal device 10 also supports wireless communication networks such as LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation), Bluetooth (registered trademark), and wireless LAN (Local It is possible to connect to a network N via short-distance wireless communication such as a local area network) and communicate with the information providing device 100.

The information providing device 100 is, for example, a PC, a server device, a mainframe, a workstation, or the like. Note that the information providing device 100 may be realized by cloud computing.

[3. Configuration example of terminal device]
Next, the configuration of the terminal device 10 will be explained using FIG. 3. FIG. 3 is a diagram showing a configuration example of the terminal device 10. As shown in FIG. As shown in FIG. 3, the terminal device 10 includes a communication section 11, a display section 12, an input section 13, a positioning section 14, a sensor section 20, a control section 30 (controller), and a storage section 40. Be prepared.

(Communication Department 11)
The communication unit 11 is connected to a network N (see FIG. 2) by wire or wirelessly, and transmits and receives information to and from the information providing device 100 via the network N. For example, the communication unit 11 is realized by a NIC (Network Interface Card), an antenna, or the like.

(Display section 12)
The display unit 12 is a display device that displays various information such as position information. For example, the display unit 12 is a liquid crystal display (LCD) or an organic electro-luminescent display (EL display). Further, the display unit 12 is a touch panel type display, but is not limited to this.

(Input section 13)
The input unit 13 is an input device that receives various operations from the user U. For example, the input unit 13 includes buttons for inputting characters, numbers, and the like. Note that the input unit 13 may be an input/output port (I/O port), a USB (Universal Serial Bus) port, or the like. Further, when the display section 12 is a touch panel display, a part of the display section 12 functions as the input section 13. Further, the input unit 13 may be a microphone or the like that receives voice input from the user U. The microphone may be wireless.

(Positioning unit 14)
The positioning unit 14 receives a signal (radio wave) sent from a GPS (Global Positioning System) satellite, and based on the received signal, determines position information (for example, latitude and longitude). That is, the positioning unit 14 positions the terminal device 10 . Note that GPS is just one example of GNSS (Global Navigation Satellite System).

Further, the positioning unit 14 can measure the position using various methods other than GPS. For example, the positioning unit 14 may use various communication functions of the terminal device 10 to measure the position as an auxiliary positioning means for position correction and the like, as described below.

(Wi-Fi positioning)
For example, the positioning unit 14 positions the terminal device 10 using the Wi-Fi (registered trademark) communication function of the terminal device 10 or the communication network provided by each communication company. Specifically, the positioning unit 14 performs Wi-Fi communication, etc., and determines the position of the terminal device 10 by measuring the distance to nearby base stations and access points.

(Beacon positioning)
Further, the positioning unit 14 may use the Bluetooth (registered trademark) function of the terminal device 10 to measure the position. For example, the positioning unit 14 measures the position of the terminal device 10 by connecting to a beacon transmitter connected by a Bluetooth (registered trademark) function.

(geomagnetic positioning)
Furthermore, the positioning unit 14 positions the terminal device 10 based on the geomagnetic pattern of the structure measured in advance and the geomagnetic sensor included in the terminal device 10 .

(RFID positioning)
Further, for example, if the terminal device 10 has an RFID (Radio Frequency Identification) tag function equivalent to a contactless IC card used at station ticket gates, stores, etc., or has a function to read an RFID tag. In this case, the location where the terminal device 10 used the terminal device 10 is recorded together with the information that the payment was made. The positioning unit 14 may measure the position of the terminal device 10 by acquiring such information. Further, the position may be determined by an optical sensor, an infrared sensor, or the like provided in the terminal device 10.

The positioning unit 14 may position the terminal device 10 using one or a combination of the above-mentioned positioning means, if necessary.

(sensor section 20)
The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10. Note that the connection may be a wired connection or a wireless connection. For example, the sensors may be a detection device other than the terminal device 10, such as a wearable device or a wireless device. In the example shown in FIG. 3, the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, an atmospheric pressure sensor 23, an air temperature sensor 24, a sound sensor 25, an optical sensor 26, a magnetic sensor 27, and an image sensor ( camera) 28.

Note that each of the sensors 21 to 28 described above is merely an example and is not limited to the above. That is, the sensor section 20 may be configured to include a portion of each of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or instead of each of the sensors 21 to 28. .

The acceleration sensor 21 is, for example, a three-axis acceleration sensor, and detects the physical movement of the terminal device 10, such as the moving direction, speed, and acceleration of the terminal device 10. The gyro sensor 22 detects physical movements of the terminal device 10 such as tilt in three axes directions based on the angular velocity of the terminal device 10 and the like. The atmospheric pressure sensor 23 detects the atmospheric pressure around the terminal device 10, for example.

Since the terminal device 10 is equipped with the above-mentioned acceleration sensor 21, gyro sensor 22, atmospheric pressure sensor 23, etc., it is possible to implement technologies such as pedestrian autonomous navigation (PDR) using these sensors 21 to 23, etc. It becomes possible to measure the position of the terminal device 10 using the . This makes it possible to obtain indoor position information that is difficult to obtain using positioning systems such as GPS.

For example, a pedometer using the acceleration sensor 21 can calculate the number of steps, walking speed, and distance walked. Furthermore, by using the gyro sensor 22, it is possible to know the direction of travel of the user U, the direction of the line of sight, and the inclination of the user's body. Further, from the atmospheric pressure detected by the atmospheric pressure sensor 23, it is also possible to know the altitude and the number of floors where the terminal device 10 of the user U is located.

The temperature sensor 24 detects, for example, the temperature around the terminal device 10. The sound sensor 25 detects, for example, sounds around the terminal device 10. The optical sensor 26 detects the illuminance around the terminal device 10 . The magnetic sensor 27 detects, for example, the earth's magnetism around the terminal device 10. The image sensor 28 captures an image of the surroundings of the terminal device 10.

The above-mentioned atmospheric pressure sensor 23, temperature sensor 24, sound sensor 25, optical sensor 26, and image sensor 28 each detect atmospheric pressure, temperature, sound, and illuminance, and capture images of the surroundings, so that the terminal device 10 It is possible to detect the surrounding environment and situation. Furthermore, it is possible to improve the accuracy of the location information of the terminal device 10 based on the environment and situation around the terminal device 10.

(Control unit 30)
The control unit 30 includes, for example, a microcomputer having a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM, an input/output port, etc., and various circuits. Further, the control unit 30 may be configured with hardware such as an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control section 30 includes a transmitting section 31, a receiving section 32, and a processing section 33.

(Transmission unit 31)
The transmitting unit 31 receives, for example, various information input by the user U using the input unit 13, various information detected by the sensors 21 to 28 mounted on or connected to the terminal device 10, and information measured by the positioning unit 14. The location information of the terminal device 10 and the like can be transmitted to the information providing device 100 via the communication unit 11.

(Receiving unit 32)
The receiving unit 32 can receive various information provided from the information providing device 100 and requests for various information from the information providing device 100 via the communication unit 11 .

(Processing unit 33)
The processing unit 33 controls the entire terminal device 10, including the display unit 12 and the like. For example, the processing unit 33 can output various types of information transmitted by the transmitting unit 31 and various types of information received by the receiving unit 32 from the information providing device 100 to the display unit 12 for display.

(Storage unit 40)
The storage unit 40 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an optical disk. Ru. The storage unit 40 stores various programs, various data, and the like.

[4. Configuration example of information providing device]
Next, the configuration of the information providing apparatus 100 according to the embodiment will be described using FIG. 4. FIG. 4 is a diagram illustrating a configuration example of the information providing apparatus 100 according to the embodiment. As shown in FIG. 4, the information providing device 100 includes a communication section 110, a storage section 120, and a control section 130.

(Communication Department 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). Further, the communication unit 110 is connected to the network N (see FIG. 2) by wire or wirelessly.

(Storage 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, or a storage device such as an HDD, an SSD, or an optical disk. As shown in FIG. 4, the storage unit 120 includes a user information database 121, a history information database 122, and a property image information database 123.

(User information database 121)
The user information database 121 stores user information regarding the user U. For example, the user information database 121 stores various information such as user U's attributes. FIG. 5 is a diagram showing an example of the user information database 121. In the example shown in FIG. 5, the user information database 121 has items such as "user ID (identifier),""age,""gender,""home,""worklocation," and "interest."

“User ID” indicates identification information for identifying user U. Note that the "user ID" may be user U's contact information (telephone number, email address, etc.), or may be identification information for identifying user U's terminal device 10.

Moreover, "age" indicates the age of the user U identified by the user ID. Note that the "age" may be information indicating the specific age of the user U (for example, 35 years old, etc.), or may be information indicating the age of the user U (for example, 30s, etc.) . Alternatively, the "age" may be information indicating the date of birth of the user U, or may be information indicating the generation of the user U (for example, born in the 1980s). Furthermore, “gender” indicates the gender of the user U identified by the user ID.

Moreover, "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 as an abstract code such as "LC11", but it may also be latitude and longitude information. Furthermore, for example, "home" may be a region name or address.

Moreover, "work place" indicates the location information of the work place (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 as an abstract code such as "LC12", but it may also be latitude/longitude information or the like. Further, for example, the "work location" may be a region name or address.

Moreover, "interest" indicates the interest of the user U identified by the user ID. That is, "interest" indicates an object in which the user U identified by the user ID has a high interest. For example, "interest" may be a search query (keyword) that the user U inputs into a search engine. In the example shown in FIG. 5, one "interest" is shown for each user U, but there may be a plurality of "interests".

For example, in the example shown in FIG. 5, the age of the user U identified by the user ID "U1" is "20s", and the gender is "male". Further, for example, the user U identified by the user ID "U1" indicates that his 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, the user U identified by the user ID "U1" indicates that he is interested in "sports."

Here, in the example shown in FIG. 5, abstract values such as "U1", "LC11", and "LC12" are used for illustration, but "U1", "LC11", and "LC12" have specific values. It is assumed that information such as character strings and numerical values is stored. Below, abstract values may be illustrated in diagrams related to other information as well.

Note that the user information database 121 is not limited to the above, and may store various information depending on the purpose. For example, the user information database 121 may store various information regarding the terminal device 10 of the user U. In addition, the user information database 121 includes information such as demographic (demographic attributes), psychographic (psychological attributes), geographic (geographical attributes), behavioral (behavioral attributes), etc. of user U. Information regarding attributes may also be stored. For example, the user information database 121 includes name, family composition, place of birth (locality), occupation, position, income, qualifications, type of residence (single-family house, condominium, etc.), presence or absence of a car, commuting/commuting time, commuting/commuting, etc. Memorizes information such as routes, commuter pass sections (stations, lines, etc.), frequently used stations (other than the stations closest to your home or work), lessons (location, time zone, etc.), hobbies, interests, lifestyle, etc. You can.

(History information database 122)
The history information database 122 stores various information related to history information (log data) indicating the actions of the user U. FIG. 6 is a diagram showing an example of the history information database 122. In the example shown in FIG. 6, the history information database 122 includes items such as "user ID,""locationhistory,""searchhistory,""browsinghistory,""purchasehistory," and "posting history."

“User ID” indicates identification information for identifying user U. Further, “position history” indicates a position history that is a history of the user U's position and movement. Further, “search history” indicates a search history that is a history of search queries input by the user U. In addition, “browsing history” indicates a browsing history that is a history of contents that the user U has viewed. Moreover, "purchase history" indicates a purchase history that is a history of purchases by user U. Moreover, "posting history" indicates a posting history that is a history of postings by user U. Note that the "posting history" may include questions regarding user U's belongings.

For example, in the example shown in FIG. 6, user U identified by user ID "U1" moves as per "location history #1", searches as per "search history #1", and searches as per "view history #1". This indicates that the content was viewed according to "history #1", a predetermined product, etc. was purchased at a predetermined store etc. according to "purchase history #1", and the content was posted according to "posting history".

Here, in the example shown in FIG. 6, abstracts such as "U1", "location history #1", "search history #1", "browsing history #1", "purchase history #1" and "posting history #1" are used. Although the figures are illustrated using ``U1'', ``Location history #1'', ``Search history #1'', ``Browsing history #1'', ``Purchase history #1'' and ``Posting history #1'', It is assumed that information such as specific character strings and numerical values is stored.

Note that the history information database 122 is not limited to the above, and may store various information depending on the purpose. For example, the history information database 122 may store the user U's usage history of a predetermined service. Further, the history information database 122 may store the user U's visit history to a physical store, visit history to a facility, or the like. Further, the history information database 122 may store the payment history of user U's payment using the terminal device 10 (electronic payment).

(Property image information database 123)
The property image information database 123 stores various information regarding images of properties. FIG. 7 is a diagram showing an example of the property image information database 123. In the example shown in FIG. 7, the property image information database 123 has items such as "property", "object", "category", "feature", and "aesthetic score".

"Property" indicates identification information for identifying a property. Further, "object" indicates identification information for identifying the object in the image of the property. That is, "object" indicates identification information for identifying an image of a property that includes the object. Further, "category" indicates the category of the object of the image of the property. Further, "feature" indicates the feature of the object in the image of the property. Note that the characteristics of the object in the image of the property may include the category, aesthetic score, etc. of the object in the image of the property. Further, the "aesthetic score" indicates the aesthetic score of the object in the image of the property.

For example, in the example shown in FIG. 7, the object "A1" in the image of the property "A" belongs to the category "appearance", has the feature "beautiful", and has an aesthetic score of "55".

Here, in the example shown in FIG. 7, abstract values such as "A" and "A1" are used for illustration, but "A" and "A1" contain information such as concrete character strings and numerical values. shall be remembered.

Note that the property image information database 123 is not limited to the above, and may store various information depending on the purpose. For example, the property image information database 123 contains property information such as "location", "tower apartment", "rent/price", "5th floor or below", "has a garden", "size of balcony", "year of construction", etc. Information regarding the overall characteristics may also be stored. Further, the property image information database 123 may store information regarding the external appearance of other properties existing in the vicinity (surroundings) of the target property.

(Control unit 130)
Returning to FIG. 4, the explanation will be continued. The control unit 130 is a controller, and uses, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array) to control the information providing apparatus 100. This is achieved by executing various programs (corresponding to an example of an information processing program) stored in an internal storage device using a storage area such as a RAM as a work area. In the example shown in FIG. 4, the control unit 130 includes an acquisition unit 131, a calculation unit 132, a totaling unit 133, a generation unit 134, a determination unit 135, and a provision unit 136.

(Acquisition unit 131)
The acquisition unit 131 acquires a search query input by the user U. For example, when the user U inputs a search query into a search engine or the like and performs a keyword search, the acquisition unit 131 acquires the search query via the communication unit 110. That is, the acquisition unit 131 acquires, via the communication unit 110, a keyword input by the user U into a search window of a search engine, site, or application.

Further, the acquisition unit 131 acquires an image of the property via the communication unit 110. For example, the acquisition unit 131 receives, via the communication unit 110, posting of images of properties from real estate agents and the like who buy, sell, exchange, rent, manage, and act as agents or intermediaries for real estate. Alternatively, the acquisition unit 131 receives, from the terminal of the user U, an image of a property owned by the user U or a designation of an image of a property that the user U is interested in via the communication unit 110. , obtain images of those properties. Note that the image of the property may be an image of a specific part (site) of the property.

The acquisition unit 131 also acquires user information regarding the user U via the communication unit 110. For example, the acquisition unit 131 acquires identification information indicating the user U (user ID, etc.), location information of the user U, attribute information of the user U, etc. from the terminal device 10 of the user U. Further, the acquisition unit 131 may acquire identification information indicating the user U, attribute information of the user U, etc. at the time of user U's user registration. The acquisition unit 131 then registers the user information in the user information database 121 of the storage unit 120.

Further, the acquisition unit 131 acquires various types of history information (log data) indicating the behavior of the user U via the communication unit 110. For example, the acquisition unit 131 acquires various types of history information indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user ID or the like. The acquisition unit 131 then registers various types of history information in the history information database 122 of the storage unit 120.

(Calculation unit 132)
The calculation unit 132 calculates the aesthetic score of the image linked to the property. Note that the calculation unit 132 may calculate aesthetic scores of all images of properties viewable by the user in advance and assign them to the images. Further, the calculation unit 132 may calculate the aesthetic score of the image of only the property viewed by the user.

(Tally unit 133)
The aggregation unit 133 aggregates the characteristics of the property that the user is viewing. For example, the totaling unit 133 extracts points of interest from the image of the property that the user is viewing, tags them as features of the image, and totals the tags that indicate the characteristics of the image that the user is viewing. Then, the aggregation unit 133 estimates the commonality of the features of the images that the users are viewing.

Note that the aggregation unit 133 also functions as a specifying unit that specifies a tendency of images (or a tendency of image characteristics) whose viewing mode satisfies a predetermined condition among images registered for each property. Further, the identification unit (aggregation unit 133) identifies the aesthetic score of the image viewed by the user. The aesthetic score of the image may be an aesthetic score assigned to the image in advance (for example, an existing aesthetic score set by another system, etc.). For example, the identification unit (aggregation unit 133) identifies a “tendency” of images that are frequently viewed, such as “water areas” being more common and “balconies” being more common. Alternatively, the identification unit (aggregation unit 133) identifies trends in information such as “water area”, “balcony”, “aesthetic score”, etc. that accompany the image. Note that the identification unit (aggregation unit 133) may identify the object to be photographed included in the image using image recognition technology. Furthermore, the aggregation unit 133 also functions as an extraction unit that extracts the characteristics of each property image from an unspecified number of property images, regardless of whether the user has viewed the images.

Further, the aggregation unit 133 may create/update a model that estimates and classifies categories for each property image. For example, the aggregation unit 133 performs machine learning using the property image and the category of the image as input data, and creates/updates a model that estimates and classifies the category of the property image.

(Generation unit 134)
The generation unit 134 generates search conditions corresponding to the image features based on the aggregation results of the image features. For example, the generation unit 134 generates search conditions corresponding to the characteristics based on the aggregation result of the characteristics of the object in the image of the property viewed by the user. The generation unit also generates search conditions for searching for properties according to the identified tendency (tendency of images whose viewing mode satisfies a predetermined condition). Further, the generation unit 134 generates search conditions based on images whose aesthetic scores satisfy a predetermined condition. For example, the generation unit 134 generates a search condition according to a "tendency" of frequently viewed images, such as "plumbing" or "balcony". Alternatively, the generation unit 134 may generate information based on the tendency of information such as "water area", "balcony", "aesthetic score", etc. attached to the image, such as a tendency such as a large number of tags attached to the image or a tendency to have a high score. Generate search conditions. Further, the generation unit 134 may generate search conditions according to the tendency of an internal score (score indicating the degree of interest) for determining the user's interest.

Furthermore, the generation unit 134 estimates a specific part of the property that the user is interested in based on the tendency of objects in the image of the property viewed by the user, and searches for properties in which the specific part satisfies predetermined conditions. Generate search conditions for

For example, if it is estimated that the user is interested in the exterior of the property based on the object in the image of the property that the user has viewed, the generation unit 134 generates search conditions related to the visual aspect of the exterior. Furthermore, when it is estimated that the user is interested in the plumbing of the property based on the object in the image of the property that the user has viewed, the generation unit 134 generates search conditions related to the plumbing. Further, the generation unit 134 generates search conditions related to storage when it is estimated that the user is interested in storing the property based on the object in the image of the property viewed by the user.

(Decision unit 135)
The determining unit 135 selects a search condition corresponding to the image feature based on the aggregation result of the image feature, and determines a property to be listed based on the aesthetic score of the image of the property according to the search condition. Further, the determining unit 135 attaches a tag to an image according to the characteristics of the image, and when a tag is searched by a user, the determining unit 135 lists properties whose aesthetic score of the image according to the searched tag satisfies a predetermined condition. The property is determined to be At this time, the determining unit 135 may list the properties in descending order of the aesthetic score of the images. Thereby, the determining unit 135 creates a property list based on the aesthetic score.

For example, the determining unit 135 selects a search condition according to a "tendency" of frequently viewed images, such as "water surroundings" being frequently viewed or "balconies" being frequently viewed. Alternatively, the determining unit 135 may determine whether the image has a large number of tags or a high score with respect to the tendency of information such as "water area", "balcony", "aesthetic score", etc. attached to the image. Select search conditions. Further, the determining unit 135 may select search conditions according to the tendency of an internal score (score indicating the degree of interest) for determining the user's interest.

The determining unit 135 analyzes images linked to properties and determines properties to be listed based on the object in the image and the aesthetic score of the image.

The determining unit 135 selects images that meet the search conditions using the model, and determines the property of the image with the top score as the property to be listed based on the aesthetic score of the selected image. That is, the determining unit 135 selects an image according to the tag using the model, and determines as a property to be listed a property whose aesthetic score of the selected image satisfies a predetermined condition. Further, the determining unit 135 uses the learning model to output the aesthetic score of the image of the property that corresponds to the search condition.

Further, if it is estimated that the user is interested in a specific part of the property based on the object in the image of the property that the user has viewed, the determining unit 135 lists the property according to the search conditions regarding the specific part. The property is determined to be For example, if it is estimated that the user is interested in the exterior of the property based on the object in the image of the property viewed by the user, the determining unit 135 selects a property that meets the search conditions regarding the visual aspect of the exterior. Decide as a property to list. Further, when listing properties according to the search conditions regarding the visual appearance of the exterior, the determining unit 135 excludes properties whose building age is at least a predetermined threshold (for example, properties that are 30 years old or older) from the list. do. Further, when it is estimated that the user is interested in the plumbing of the property based on the object in the image of the property viewed by the user, the determining unit 135 lists properties that meet the search conditions regarding the plumbing. Determine as. Further, if it is estimated that the user is interested in storage of the property based on the object in the image of the property viewed by the user, the determining unit 135 determines the property that meets the search conditions regarding storage as the property to be listed. do.

At this time, the determining unit 135 selects an image corresponding to a specific part of the property using the model, and lists properties with images with high scores based on the aesthetic score of the image of the selected specific part. It may be determined as

For example, the determining unit 135 uses a model to select an image that corresponds to the exterior of the property, and based on the aesthetic score of the selected exterior image, determines the property with the image with the highest score as the property to be listed. At this time, when determining a property to list based on the aesthetic score of the image of the exterior of the property, the determining unit 135 selects properties whose building age is at least a predetermined threshold (for example, properties which are 30 years old or older) from the list. exclude.

Further, the determining unit 135 selects images corresponding to the water area of the property using the model, and determines the property with the image with the top score as the property to be listed based on the aesthetic score of the selected image of the water area. .

Further, the determining unit 135 uses the model to select an image corresponding to a storage property, and based on the aesthetic score of the selected storage image, determines the property of the image with the top score as the property to be listed.

(Providing unit 136)
The providing unit 136 presents the listed properties to the user. That is, the providing unit 136 presents properties according to the search conditions to the user. For example, the providing unit 136 generates a search condition corresponding to the tag based on the tag aggregation result, and presents properties related to the search condition. At this time, the providing unit 136 uses the model to select properties that meet the search conditions and presents properties related to the search conditions. Further, the providing unit outputs the aesthetic score of the image of the property that corresponds to the search condition using the learning model.

If it is estimated that the user is interested in a specific part of the property based on the object in the image of the property that the user has viewed, the providing unit 136 presents the user with properties that match the search conditions regarding the specific part. do.

For example, if it is estimated that the user is interested in the exterior of the property based on the object in the image of the property that the user has viewed, the providing unit 136 performs a search regarding the visual aspects of the exterior (such as whether the exterior is beautiful). Present properties to the user that meet the conditions. At this time, when presenting properties to the user according to the search conditions regarding the visual aspect of the exterior, the providing unit 136 selects properties whose building age is at least a predetermined threshold (for example, properties that are 30 years old or older). Exclude from target.

Further, if it is estimated that the user is interested in the plumbing of the property based on the object in the image of the property that the user has viewed, the providing unit 136 presents the user with properties that match the search conditions regarding the plumbing. do.

Further, when it is estimated that the user is interested in storing the property based on the object in the image of the property that the user has viewed, the providing unit 136 presents the user with properties that meet the search conditions regarding storage.

[5. Processing procedure]
Next, a processing procedure by the information providing apparatus 100 according to the embodiment will be described using FIG. 8. FIG. 8 is a flowchart showing the processing procedure according to the embodiment. Note that the processing procedure shown below is repeatedly executed by the control unit 130 of the information providing device 100.

As shown in FIG. 8, the acquisition unit 131 of the information providing device 100 collects images of the property via the communication unit 110 (step S101). The image of the property may be an image of a specific part (site) of the property.

Subsequently, the calculation unit 132 of the information providing device 100 calculates the aesthetic score of the image of the property (step S102). For example, the calculation unit 132 calculates the aesthetic score of the object in the image of the property.

Subsequently, the aggregation unit 133 of the information providing device 100 estimates the commonality of the features of the images that the users are viewing (step S103). For example, the tallying unit 133 extracts points of interest from images of properties viewed by the user, tags them as features of the image, and tallies tags indicating the features of the images viewed by the user. The features of the image may be features of the object in the image.

Next, the generation unit 134 of the information providing device 100 generates search conditions based on the commonality of the image features (step S104).

Subsequently, the determining unit 135 of the information providing device 100 determines a property related to the search condition as a property to be listed (step S104). For example, the determining unit 135 uses a model to select properties that meet the search conditions, and creates a list of properties related to the search conditions (property list).

Subsequently, the providing unit 136 of the information providing device 100 presents information regarding the determined property (listed property) to the user via the communication unit 110 (step S6). For example, the providing unit 136 presents the user with a list of properties related to the search conditions (property list).

[6. Modified example]
The terminal device 10 and the information providing device 100 described above may be implemented in various different forms other than the above embodiments. Therefore, a modification of the embodiment will be described below.

In the embodiment described above, part or all of the processing executed by the information providing device 100 may actually be executed by the terminal device 10. For example, the process may be completed stand-alone (by the terminal device 10 alone). In this case, it is assumed that the terminal device 10 has the functions of the information providing device 100 in the above embodiment. Furthermore, in the embodiment described above, since the terminal device 10 cooperates with the information providing device 100, it appears to the user U that the processing of the information providing device 100 is also executed by the terminal device 10. That is, from another perspective, it can be said that the terminal device 10 includes the information providing device 100.

Furthermore, in the above embodiment, the information providing apparatus 100 uses a set of an image (or its feature) and a category as a data set, and estimates a category for each image using a machine learning method using a neural network or the like. A classification model for classification may be created. That is, the information providing device 100 inputs an image (or its characteristics) into a classification model generated through machine learning using, for example, RNN (Recurrent Neural Network) or LSTM (Long short-term memory), and analyzes the image. You may classify by estimating the category. Note that the RNN and LSTM may be neural networks based on an attention mechanism.

Furthermore, in the embodiment described above, the information providing apparatus 100 may estimate and classify a category for each image according to a predetermined conversion rule (rule-based).

Further, in the above embodiment, the information providing device 100 combines the category of the property image (exterior, kitchen, toilet, living room, entrance, etc.) and the aesthetic score of the property image, and uses the property image as a feature. good.

Furthermore, in the above embodiment, when the information providing apparatus 100 estimates that the user is interested in the color or equipment of a specific part of the property based on the characteristics of the image of the property that the user is viewing, , presents the user with properties according to search conditions regarding the color and equipment of a specific part of the property that the user is interested in. For example, if the user is mainly viewing "properties with a red exterior" or "properties with stylish faucets (designed faucets) in the kitchen, sink, etc.", the information providing device 100 may display "properties with a red exterior". '', ``stylish faucet,'' etc., properties that match search conditions are presented to the user. At this time, the information providing device 100 may calculate a score indicating the redness of the appearance, a score indicating the fashionability of the faucet, etc., such as an aesthetic score.

In the above embodiment, when it is estimated that the user is interested in the exterior of a property, the information providing device 100 not only displays an image of the exterior of the target property but also images of the neighborhood (surroundings) of the property. It may also be possible to present images including external appearances of other properties existing in the area. Even if the exterior of the target property itself is good, there is a possibility that it will not harmonize with the exterior of other properties in the neighborhood (surroundings), or that the impression will be different in relation to the exterior of other properties. This is because there is.

[7. effect〕
As described above, the information processing device (terminal device 10 and information providing device 100) according to the present application includes a specific unit ( The present invention includes a totaling unit 133), a generating unit 134 that generates search conditions for searching for properties according to identified trends, and a providing unit 136 that presents properties according to the search conditions to the user.

The identification unit (aggregation unit 133) extracts points of interest from the image of the property that the user is looking at, tags them as features of the image, and tallies the tags that indicate the features of the image that the user is looking at. The generation unit 134 generates a search axis corresponding to the tag based on the tag aggregation result. The providing unit 136 presents properties related to the search conditions.

The identification unit (aggregation unit 133) identifies the aesthetic score of the image viewed by the user. The generation unit 134 generates search conditions based on images whose aesthetic scores satisfy predetermined conditions.

The generation unit 134 estimates a specific part of the property that the user is interested in based on the tendency of objects in the image of the property viewed by the user, and searches for properties in which the specific part satisfies predetermined conditions. Generate search conditions for.

When it is estimated that the user is interested in the exterior of the property based on the object in the image of the property that the user has viewed, the generation unit 134 generates search conditions related to the visual aspect of the exterior.

When it is estimated that the user is interested in the plumbing of the property based on the object in the image of the property that the user has viewed, the generation unit 134 generates search conditions related to the plumbing.

The generation unit 134 generates search conditions related to storage when it is estimated that the user is interested in storing the property based on the object in the image of the property viewed by the user.

By using any one or a combination of the above-described processes, the information processing apparatus according to the present application can create search conditions for providing useful information to the user. The information processing device according to the present application identifies features (tags, etc.) of images viewed by a user, generates search conditions based on the commonality of the identified features, and provides search results based on the search conditions.

[8. Hardware configuration]
Further, the terminal device 10 and the information providing device 100 according to the embodiments described above are realized by, for example, a computer 1000 having a configuration as shown in FIG. The information providing apparatus 100 will be described below as an example. FIG. 9 is a diagram showing an example of the hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output I/F (Interface) 1060, an input I/F 1070, and a network I/F 1080 are connected to a bus. 1090.

The arithmetic unit 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and performs various processes. The arithmetic device 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 calculation device 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 includes a ROM (Read Only Memory), an HDD (Hard Disk Drive), and an SSD (Solid Disk Drive). This is realized using flash memory, etc. The secondary storage device 1050 may be a built-in storage or an external storage. Further, the secondary storage device 1050 may be a removable storage medium such as a USB (Universal Serial Bus) memory or an SD (Secure Digital) memory card. Further, the secondary storage device 1050 may be a cloud storage (online storage), a 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 the output device 1010 that outputs various information such as a display, a projector, and a printer. (Digital Visual Interface) and HDMI (registered trademark) (High Definition Multimedia Interface). Further, the input I/F 1070 is an interface for receiving information from various input devices 1020 such as a mouse, keyboard, keypad, button, scanner, etc., and is realized by, for example, a USB or the like.

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, output device 1010 and input device 1020 may be wireless devices.

Moreover, 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 an input/output I/F.

Note that the input device 1020 is, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or 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.

Network I/F 1080 receives data from other devices via network N and sends it to computing device 1030, and also sends data generated by computing device 1030 to other devices via network N.

Arithmetic device 1030 controls output device 1010 and input device 1020 via output I/F 1060 and input I/F 1070. For example, the arithmetic device 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 providing device 100, the arithmetic unit 1030 of the computer 1000 realizes the functions of the control unit 130 by executing a program loaded onto the primary storage device 1040. Further, the arithmetic device 1030 of the computer 1000 may load a program obtained from another device via the network I/F 1080 onto the primary storage device 1040, and execute the loaded program. Furthermore, the arithmetic unit 1030 of the computer 1000 may cooperate with other devices via the network I/F 1080, and may call and use program functions, data, etc. from other programs of other devices.

[9. others〕
Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Furthermore, the above-mentioned components include those that can be easily assumed by those skilled in the art, those that are substantially the same, and those that are in a so-called equivalent range. Furthermore, the aforementioned components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the constituent elements can be made without departing from the gist of the embodiments described above.

Further, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed manually. All or part of this can also be performed automatically using known methods. In addition, information including the processing procedures, specific names, and various data and parameters shown in the above documents and drawings may be changed arbitrarily, unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

Furthermore, each component of each device shown in the drawings is functionally conceptual, and does not necessarily need to be physically configured as shown in the drawings. In other words, the specific form of distributing and integrating each device is not limited to what is shown in the diagram, and all or part of the devices can be functionally or physically distributed or integrated in arbitrary units depending on various loads and usage conditions. Can be integrated and configured.

For example, the information providing apparatus 100 described above may be realized by a plurality of server computers, and depending on the function, it may be realized by calling an external platform etc. using an API (Application Programming Interface), network computing, etc. can be changed flexibly.

Furthermore, the above-described embodiments and modifications can be combined as appropriate within a range that does not conflict with the processing contents.

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

1 Information processing system 10 Terminal device 100 Information providing device 110 Communication unit 120 Storage unit 121 User information database 122 History information database 123 Property image information database 130 Control unit 131 Acquisition unit 132 Calculation unit 133 Aggregation unit 134 Generation unit 135 Determination unit 136 Providing department

Claims (10)

an identification unit that identifies a tendency of objects in images of the property viewed by the user from common points of objects in a plurality of images of different objects viewed by the user among images registered for each property;
a generation unit that generates search conditions for searching for a property based on the tendency of the object in the image of the identified property ;
a providing unit that presents to the user properties whose images of objects according to the tendency are highly aesthetically pleasing among the properties according to the search conditions;
An information processing device comprising: The identification unit aggregates tags indicating characteristics of images of properties viewed by the user,
The generation unit generates a search condition corresponding to the tag based on the aggregation result of the tag,
The information processing device according to claim 1, wherein the providing unit presents properties related to the search condition. The identification unit identifies an aesthetic score of an image of a property viewed by the user;
The information processing device according to claim 1 or 2, wherein the generation unit generates the search condition based on an image whose aesthetic score satisfies a predetermined condition. The generation unit estimates a specific part of the property that the user is interested in based on the tendency of the object in the image of the property viewed by the user, and generates a property in which the estimated specific part satisfies a predetermined condition. The information processing apparatus according to claim 2 or 3, wherein the information processing apparatus generates search conditions for searching. The generating unit is characterized in that, when it is estimated that the user is interested in the exterior of the property based on the object in the image of the property viewed by the user, the generation unit generates a search condition regarding the visual aspect of the exterior. The information processing device according to claim 4. The generating unit generates a search condition related to the plumbing when it is estimated that the user is interested in the plumbing of the property based on the object in the image of the property viewed by the user. 5. The information processing device according to 4 or 5. The generation unit generates search conditions related to storage when it is estimated that the user is interested in storage of the property based on the object in the image of the property viewed by the user. 6. The information processing device according to any one of 6. The information processing apparatus according to any one of claims 4 to 7, wherein the providing unit outputs an aesthetic score of an image of a property that corresponds to the search condition using a learning model. An information processing method executed by an information processing device, the method comprising:
an identification step of identifying a tendency of the object in the image of the property viewed by the user from common points of each object in a plurality of images of different objects viewed by the user among the images registered for each property;
a generation step of generating search conditions for searching for a property based on the tendency of the object in the image of the identified property ;
a providing step of presenting to the user properties whose images of objects according to the tendency are highly aesthetically pleasing among the properties according to the search conditions;
An information processing method characterized by comprising: an identification procedure for identifying a tendency of an object in an image of a property viewed by a user based on a common feature of each object in a plurality of images of different objects viewed by the user among images registered for each property;
a generation procedure for generating search conditions for searching for a property based on the tendency of the object in the image of the identified property ;
a providing procedure of presenting to the user properties whose images of objects according to the tendency are highly aesthetically pleasing among the properties according to the search conditions;
An information processing program that allows a computer to execute.

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