KR20230066853A - Method, system, and computer program to provide place-related recommendation based on taste - Google Patents

Abstract

A method, system, and computer program capable of providing taste-related place-related recommendations are disclosed. A place-related recommendation method includes analyzing a user's taste using user feedback related to a place; and providing recommended information related to a place based on a feature corresponding to the user's preference.

Description

METHOD, SYSTEM, AND COMPUTER PROGRAM TO PROVIDE PLACE-RELATED RECOMMENDATION BASED ON TASTE

The description below relates to a technique for providing recommendation information related to a place.

Various evaluation systems such as star rating reviews, text reviews, and photo reviews are being used as user reviews for places.

For example, Korean Patent Laid-open Publication No. 10-2020-0000925 (published on January 6, 2020) discloses a technique for creating store review information using augmented reality.

In the place review service, after authenticating a place visited or used by a user by using a place reservation function, a receipt authentication function, etc., the authenticated place information can be submitted together with the review.

A user review of a place may be exposed in conjunction with a place review service as well as other services providing place information such as a search service or a map service.

Recommendation information corresponding to the user's preference may be provided by analyzing the user's preference based on the user's feedback related to the place.

Depending on the type of feedback, the degree of preference can be classified and used in different recommendation logics.

It is possible to provide person-oriented recommendation information and place or region-oriented recommendation information based on user preference.

A place-related recommendation method executed in a computer system, the computer system comprising at least one processor configured to execute computer readable instructions contained in a memory, wherein the place-related recommendation method is performed by the at least one processor , analyzing user taste using user feedback related to the place; and providing, by the at least one processor, recommendation information related to a place based on a feature corresponding to the user's taste.

According to one aspect, the analyzing of the user taste includes analyzing the user taste by classifying the level of severity of the taste according to the feedback type, and the step of providing the recommendation information is divided into the level of severity of the taste. and providing different recommended objects according to the user's preference.

According to another aspect, the analyzing of the user's taste may include collecting the user's feedback based on a like reaction to the place.

According to another aspect, the analyzing of the user's preference may include the analysis of the user's preference based on at least one of log data related to place search, log data related to receipt authentication or reservation or order for a place, and user review analysis results for the place. A step of collecting user feedback may be further included.

According to another aspect, Analyzing the user's taste may include analyzing the user's taste by distinguishing a like reaction for a place included in another user's review and a like reaction for a place the user personally visited or used.

According to another aspect, the analyzing of the user taste may include extracting characteristics from content related to a place where the user feedback exists; and calculating a taste index for each feature using the user feedback.

According to another aspect, the providing of the recommendation information may include selecting and recommending another user having a taste similar to the user's preference for a place.

According to another aspect, the providing of the recommendation information may include selecting and recommending another user having a similar taste based on at least one of a regional distribution and an industry category according to the user's taste.

According to another aspect, the providing of the recommendation information may include selecting and recommending a place having characteristics corresponding to the user's taste.

According to another aspect, the providing of the recommendation information may include recommending a place commonly specified by a group of experts related to the user taste.

According to another aspect, the providing of the recommendation information may include providing common information about a place with other users based on the user preference.

Provided is a computer program stored in a computer readable recording medium in order to execute the place-related recommendation method on a computer.

A computer system comprising: at least one processor configured to execute computer readable instructions contained in a memory, wherein the at least one processor includes: analyzing user taste using user feedback related to a place; and a computer system that processes a process of providing recommendation information related to a place based on a feature corresponding to the user's taste.

According to embodiments of the present invention, user preference may be analyzed based on user feedback related to a place, and recommendation information corresponding to the user preference may be provided.

According to the embodiments of the present invention, it is possible to provide reviewer-centered recommendation information and place or region-centered recommendation information based on user preference, and classify the severity level of taste according to the type of feedback to be used in different recommendation logics. can

1 is a diagram illustrating an example of a network environment according to an embodiment of the present invention.
2 is a block diagram illustrating an example of a computer system according to one embodiment of the present invention.
3 is a diagram showing an example of components that may be included in a processor of a computer system according to an embodiment of the present invention.
4 is a flowchart illustrating an example of a method that a computer system may perform according to an embodiment of the present invention.
5 to 8 are exemplary diagrams for explaining a process of collecting taste feedback in an embodiment of the present invention.
9 is an exemplary diagram for explaining a process of recommending a reviewer based on a user's taste in an embodiment of the present invention.
10 is an exemplary diagram for explaining a process of recommending a place based on a user's taste in an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Embodiments of the present invention relate to a technique for providing recommendation information related to a place.

Embodiments including those specifically disclosed herein may provide recommendation information corresponding to the user's preference by analyzing the user's preference based on the user's feedback related to the place.

In the present specification, a place may mean all objects that can review user experiences according to visits or use, such as restaurants, shops, famous places, and hot places. A review of a place may include a review of an online user experience, such as a commercial transaction or a virtual performance/exhibition, as well as an offline user experience.

A place-related recommendation system according to embodiments of the present invention may be implemented by at least one computer system, and a place-related recommendation method according to embodiments of the present invention includes at least one computer system included in the place-related recommendation system. can be performed through At this time, a computer program according to an embodiment of the present invention may be installed and driven in the computer system, and the computer system may perform a place-related recommendation method according to embodiments of the present invention under the control of the driven computer program. there is. The above-described computer program may be combined with a computer system and stored in a computer readable recording medium to execute a place-related recommendation method on a computer.

1 is a diagram illustrating an example of a network environment according to an embodiment of the present invention. The network environment of FIG. 1 shows an example including a plurality of electronic devices 110 , 120 , 130 , and 140 , a plurality of servers 150 and 160 , and a network 170 . 1 is an example for explanation of the invention, and the number of electronic devices or servers is not limited as shown in FIG. 1 . In addition, the network environment of FIG. 1 only describes one example of environments applicable to the present embodiments, and the environment applicable to the present embodiments is not limited to the network environment of FIG. 1 .

The plurality of electronic devices 110, 120, 130, and 140 may be fixed terminals implemented as computer devices or mobile terminals. Examples of the plurality of electronic devices 110, 120, 130, and 140 include a smart phone, a mobile phone, a navigation device, a computer, a laptop computer, a digital broadcast terminal, a personal digital assistant (PDA), and a portable multimedia player (PMP). ), tablet PC, game console, wearable device, internet of things (IoT) device, virtual reality (VR) device, augmented reality (AR) device, and the like. As an example, FIG. 1 shows the shape of a smartphone as an example of the electronic device 110, but in the embodiments of the present invention, the electronic device 110 substantially uses a wireless or wired communication method to transmit other information via the network 170. It may refer to one of various physical computer systems capable of communicating with the electronic devices 120 , 130 , and 140 and/or the servers 150 and 160 .

The communication method is not limited, and short-distance wireless communication between devices as well as a communication method utilizing a communication network (eg, a mobile communication network, a wired Internet, a wireless Internet, and a broadcasting network) that the network 170 may include may also be included. For example, the network 170 may include a personal area network (PAN), a local area network (LAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN), and a broadband network (BBN). , one or more arbitrary networks such as the Internet. In addition, the network 170 may include any one or more of network topologies including a bus network, a star network, a ring network, a mesh network, a star-bus network, a tree or a hierarchical network, and the like. Not limited.

Each of the servers 150 and 160 communicates with the plurality of electronic devices 110, 120, 130, and 140 through the network 170 to provide commands, codes, files, contents, services, and the like, or a computer device or a plurality of computers. Can be implemented in devices. For example, the server 150 may be a system that provides a first service to a plurality of electronic devices 110, 120, 130, and 140 accessed through the network 170, and the server 160 may also include a network ( It may be a system that provides a second service to a plurality of electronic devices 110, 120, 130, and 140 accessed through 170). As a more specific example, the server 150 provides a service targeted by the application (eg, a place review service) through an application as a computer program that is installed and driven in the plurality of electronic devices 110, 120, 130, and 140. may be provided to the plurality of electronic devices 110, 120, 130, and 140 as the first service. As another example, the server 160 may provide a service for distributing files for installing and running the above-described application to the plurality of electronic devices 110, 120, 130, and 140 as a second service.

2 is a block diagram illustrating an example of a computer system according to one embodiment of the present invention. Each of the plurality of electronic devices 110 , 120 , 130 , and 140 or each of the servers 150 and 160 described above may be implemented by the computer system 200 shown in FIG. 2 .

As shown in FIG. 2 , the computer system 200 may include a memory 210, a processor 220, a communication interface 230, and an input/output interface 240.

The memory 210 is a computer-readable recording medium and may include a random access memory (RAM), a read only memory (ROM), and a permanent mass storage device such as a disk drive. Here, a non-perishable mass storage device such as a ROM and a disk drive may be included in the computer system 200 as a separate permanent storage device distinct from the memory 210 . Also, an operating system and at least one program code may be stored in the memory 210 . These software components may be loaded into the memory 210 from a computer-readable recording medium separate from the memory 210 . The separate computer-readable recording medium may include a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD/CD-ROM drive, and a memory card. In another embodiment, software components may be loaded into the memory 210 through the communication interface 230 rather than a computer-readable recording medium. For example, software components may be loaded into memory 210 of computer system 200 based on a computer program installed by files received over network 170 .

The processor 220 may be configured to process commands of a computer program by performing basic arithmetic, logic, and input/output operations. Instructions may be provided to processor 220 by memory 210 or communication interface 230 . For example, processor 220 may be configured to execute received instructions according to program codes stored in a recording device such as memory 210 .

The communication interface 230 may provide a function for the computer system 200 to communicate with other devices (eg, storage devices described above) through the network 170 . For example, a request, command, data, file, etc. generated according to a program code stored in a recording device such as the memory 210 by the processor 220 of the computer system 200 is controlled by the communication interface 230 to the network ( 170) to other devices. Conversely, signals, commands, data, files, etc. from other devices may be received into computer system 200 via communication interface 230 of computer system 200 via network 170 . Signals, commands, or data received through the communication interface 230 may be transferred to the processor 220 or the memory 210, and files may be stored as storage media that the computer system 200 may further include (described above). permanent storage).

The input/output interface 240 may be a means for interface with the input/output device 250 . For example, the input device may include a device such as a microphone, keyboard, or mouse, and the output device may include a device such as a display or speaker. As another example, the input/output interface 240 may be a means for interface with a device in which functions for input and output are integrated into one, such as a touch screen. The input/output device 250 may be configured as one device with the computer system 200 .

Also, in other embodiments, computer system 200 may include fewer or more elements than those of FIG. 2 . However, there is no need to clearly show most of the prior art components. For example, the computer system 200 may be implemented to include at least some of the aforementioned input/output devices 250 or may further include other elements such as a transceiver and a database.

Hereinafter, specific embodiments of a method and system capable of providing place-related recommendations according to taste will be described.

3 is a block diagram showing an example of components that may be included in a processor of a computer system according to an embodiment of the present invention, and FIG. 4 is a place where a computer system according to an embodiment of the present invention can perform It is a flow chart showing an example of a related recommendation method.

The computer system 200 according to the present embodiment may provide a place review service to clients through a dedicated application installed on the client or access to a web/mobile site related to the computer system 200 .

The computer system 200 provides a review space for a place through a user's personal service page, and after authenticating the place the user has visited or used through a linkage function with a reservation/order service, a receipt authentication function, etc. Reviews written by users can be matched with place information and registered.

The computer system 200 may provide a place-based search and recommendation environment for users, and in this case, users may share reviews of places based on their followers.

For example, the place review service includes reviews of following users for places in various industries such as restaurants and cafes, a feed tab where recommended places/reviewers tailored to the user's taste are exposed, and a list of places where the user has been certified to visit or use. A visit tab that is exposed, a review tab that allows users to write reviews such as star rating reviews for places they have visited or used, keyword reviews, text reviews, photo reviews, etc. It may include a /orders tab, a storage tab that exposes a list of places that the user has saved as an interest, and the like.

The processor 220 of the computer system 200 is a component for performing a place-related recommendation method to be described later, and as shown in FIG. 3, the feedback collection unit 310, the taste analyzer 320, and the place-related A recommendation unit 330 may be included. Depending on embodiments, components of the processor 220 may be selectively included in or excluded from the processor 220 . Also, components of the processor 220 may be separated or merged to express functions of the processor 220 according to embodiments.

The processor 220 and components of the processor 220 may control the computer system 200 to perform steps included in a place-related recommendation method to be described later. For example, the processor 220 and components of the processor 220 may be implemented to execute instructions according to an operating system code and at least one program code included in the memory 210 .

Here, elements of the processor 220 may be representations of different functions performed by the processor 220 according to instructions provided by program codes stored in the computer system 200 . For example, the feedback collector 310 may be used as a functional representation of the processor 220 that controls the computer system 200 according to the above instructions so that the computer system 200 collects user feedback related to the place. .

The processor 220 may read necessary commands from the memory 210 loaded with commands related to the control of the computer system 200 . In this case, the read command may include a command for controlling the processor 220 to execute a place-related recommendation method to be described later.

Steps included in the place-related recommendation method to be described later may be performed in an order different from the illustrated order, and some of the steps may be omitted or additional processes may be further included.

Referring to FIG. 4 , in step S410, the feedback collector 310 may collect user feedback related to the place. The feedback collector 310 may collect user feedback for each feedback type. The feedback collection unit 310 may collect both a feedback type and information about a place that is a feedback target as user feedback related to a place. The type of feedback may include interest feedback indicating whether the user is interested, visit feedback indicating whether the user has visited/used the information, preference feedback indicating whether the user prefers the information, taste feedback indicating whether the user prefers the information, and the like. For example, the feedback collection unit 310 may collect interest feedback based on log data such as searching, clicking, saving, finding directions, calling, sharing, and the like for a place. The feedback collection unit 310 may collect visit feedback based on log data such as receipt authentication, reservation, order, payment, and the like. The feedback collection unit 310 may collect preference feedback based on a sentiment analysis result of a sentence written as a text review among user reviews of places. In addition to text reviews, preference feedback can be collected using keywords or sentences registered as reviews through other review systems such as keyword reviews. The feedback collection unit 310 may collect taste feedback based on likes or recommended reactions to a place. In the case of taste feedback, it can be collected by classifying the level of severity of taste. For example, if you click the Like button in the recommended list of places exposed in the feed tab or click the Like button after seeing a review written by others, the preference is relatively low in importance. , and when a user clicks the Like button in the process of writing a review after visiting or using it, it can be classified as a heavy taste with a relatively high level of importance.

In step S420, the taste analyzer 320 may analyze the user's taste using the user's feedback related to the place. The taste analyzer 320 may analyze the user's taste by extracting characteristics of the place where user feedback exists. For example, the taste analysis unit 320 may extract characteristic information of a corresponding place from basic information (type of industry, description, picture, etc.) registered by a person concerned with the place. As another example, the taste analyzer 320 may extract feature information automatically tagged to a corresponding place based on content generated by users who have visited or used the place. The characteristics of the place may be classified and tagged according to keywords or text written by the user as a review, or classified and tagged according to product or atmosphere/feeling analysis results of a photo written by the user as a review. Characteristic information for user taste analysis can be extracted centering on the place where the user wrote a review of the same keyword or similar sentence.

The taste analyzer 320 may analyze user taste using at least one of interest feedback, visit feedback, preference feedback, and taste feedback. For example, the taste analyzer 320 may analyze user taste by using interest feedback, visit feedback, preference feedback, and taste feedback but applying the same weight. As another example, the taste analyzer 320 analyzes the user's taste by using the taste feedback as the core feedback among the feedback types, and selectively or mutually selects at least one of the remaining feedback types (interest feedback, visit feedback, preference feedback, and clean feedback). It can be reflected with different weights. The taste analysis unit 320 may calculate a taste index for each feature that a place may have by using user feedback, and for example, a taste index for each feature may be calculated based on a feedback ratio for each feature among the total number of feedbacks. can Among various features that a place may have, at least one feature having a higher taste index than a certain level based on the taste index may be determined as the user's taste.

The taste analysis unit 320 may calculate a user taste index by distinguishing between light taste and heavy taste in the user taste analysis using taste feedback. In this case, the light taste index and the heavy taste index may be used for different recommendation logics. For example, the atmosphere or feeling of a place can be classified by analyzing photos registered by place officials or photos registered by users as reviews. can be utilized A heavy taste index can be used when recommending a place having the same or similar characteristics as the user's taste.

In step S430, the place-related recommendation unit 330 may provide place-related recommendation information corresponding to the user's preference. For example, the place-related recommendation unit 330 may select and recommend a reviewer having a taste similar to the user's taste from among other users (hereinafter referred to as 'reviewer') using the place review service. At this time, the place-related recommendation unit 330 may select reviewers with similar tastes by using the regional distribution of places corresponding to the user's taste or the industry category. As another example, the place-related recommendation unit 330 may select and recommend a place having characteristics corresponding to a user's taste. The characteristics of the place may be classified from keywords or text written by the user as a review, product of a photo written by the user as a review, or a result of analyzing the atmosphere/feeling. Among these characteristics, a place having similar characteristics to the user's taste may be selected, and a corresponding place and a review of the corresponding place may be recommended. As another example, the place-related recommendation unit 330 may select and recommend a specific place that reviewers specified as expert groups on the service or reviewers that the user follows commonly visits or prefers. It is not recommended by individual reviewers or places, but by a group of experts on a specific product (eg, user preferred menu, etc.) or a group of experts on a specific region (eg, user preferred region, etc.) commonly visited or preferred. Can you recommend a specific place to do it? As another example, the place-related recommendation unit 330 may provide common information between a user and a reviewer. For example, when a user visits a reviewer's page (eg, a review home, etc.), the place-related recommendation unit 330 will display a place that has been reviewed in common between the reviewer and the user, a place where a like reaction has been entered, and the like. can In addition, the place-related recommendation unit 330 may provide a filter function using commonalities with users when providing reviews of multiple reviewers. For example, various conditions, such as age, neighborhood, taste, favorite place, and like/reaction place, may be provided as filters, and reviews of reviewers similar to the user may be selected and provided based on the condition selected as the filter. Accordingly, the place-related recommendation unit 330 may provide recommendation information centered on a place or region as well as person-centered recommendation information based on a user's preference.

In providing a review feed, the place-related recommendation unit 330 may provide a feed in which reviews distributed by place are collected by various criteria such as region or industry. The place-related recommendation unit 330 may provide a feed for each administrative district (eg, dong unit, etc.) based on the location set by the user, and may provide a feed for new places in the administrative district and newly registered by the person concerned. You can also provide news, etc. At this time, the place-related recommender 330 may select a place of interest to the user based on user preference among places within the administrative district and recommend a review of the place.

When the place-related recommender 330 provides a list of reviews to the user in the process of searching for a place or recommending a place, the user feedback on the review (for example, the review is not up to date based on the review writing time) feedback) can be provided by listing them based on the cumulative number of times. The place-related recommendation unit 330 may sort and display the review list in the order of accumulated number of review assistance, and may sort and display the review list by other criteria such as reviewer reliability, review quality, and recency according to a user's request. Based on the user's preference, more reviews of places that the user may be interested in can be shown than reviews of other criteria.

5 to 8 are exemplary diagrams for explaining a process of collecting taste feedback in an embodiment of the present invention.

Referring to FIG. 5 , the place detail screen 500 may expose overall information related to the place (eg, company name, location, phone number, photo, description, product, etc.), and in this case, the place detail screen 500 may include a 'save' button 501 for saving the corresponding place as a bookmark.

The processor 220 may provide a place storage screen 510 when the 'save' button 501 is selected on the place detail screen 500 . The place storage screen 510 may include an interface for selecting a place list for storing a corresponding place.

The place storage screen 510 may include a 'Like' button 511 for inputting a like reaction as taste feedback for a place to be saved. The processor 220 may collect a user input using the 'Like' button 511 on the place storage screen 510 as taste feedback.

Referring to FIG. 6 , the processor 220 may provide a review writing screen 610 for places visited or used by the user. The review writing screen 610 includes an interface for writing a star rating review, keyword review, text review, photo review, etc. as a user review of a place.

The review writing screen 610 may include a 'Like' button 611 for inputting a 'Like' reaction as taste feedback for a place. The processor 220 may collect user input using the 'Like' button 611 on the review writing screen 610 as taste feedback.

Referring to FIG. 7 , the processor 220 may provide a review feed screen 710 on a place review service page.

On the review feed screen 710, a list of feeds composed of reviews written by reviewers that the user follows for places in various industries, a list of feeds composed of reviews of recommended places that suit the taste of the user, and the like may be exposed.

The review feed screen 710 may include a 'Like' button 711 for inputting a 'Like' reaction as taste feedback for the place of the corresponding review for each review included in the feed list. The processor 220 may collect a user input using the 'Like' button 711 on the review feed screen 710 as taste feedback.

Referring to FIG. 8 , the processor 220 may provide a review detail screen 810 when a specific review is selected from the review feed screen 710 or the like. The review detail screen 810 may expose information about the reviewer who wrote the review, information about a place subject to the review, review contents such as star rating reviews written by user reviews, keyword reviews, text reviews, and photo reviews.

The review detail screen 810 may include a 'follow' button 801 for setting a follower for the reviewer, a 'like' button 811 for inputting a like reaction as taste feedback for a place, and the like. The processor 220 may collect a user input using the 'Like' button 811 on the review detailed screen 810 as taste feedback.

The above-mentioned paths are some examples, but are not limited thereto, and user feedback on the place may be collected through various other paths.

9 is an exemplary diagram for explaining a process of recommending a reviewer based on a user's taste in an embodiment of the present invention.

Referring to FIG. 9 , the processor 220 may provide a reviewer recommendation list 910 according to user taste on a review feed screen 710 . The reviewer recommendation list 910 may be composed of reviewers having the same or similar preference for places as the user.

For each reviewer included in the reviewer recommendation list 910, a 'follow' button 901 for setting a follower, a 'recommendation exclusion' button 902 for excluding the reviewer from the reviewer recommendation target, and the like may be included.

The reviewer recommendation list 910 is a review list 903 prepared by a recommended reviewer, and may include at least some photo reviews and place names. Recommended reviewers can be classified and recommended according to various criteria, such as reviewers by region, reviewers by menu, and reviewers with similar tastes. For example, in the review list 903, among reviews written by recommended reviewers, reviews of places having the same or similar characteristics as those corresponding to the user's taste may be exposed, and depending on the embodiment, reviews with a high cumulative number of review assistance It is also possible for recently written reviews to be exposed.

10 is an exemplary diagram for explaining a process of recommending a place based on a user's taste in an embodiment of the present invention.

Referring to FIG. 10 , the processor 220 may provide a place recommendation list 1010 according to user taste on a review feed screen 710 . The place recommendation list 1010 may include places having the same or similar features as those corresponding to the user's taste.

For each place included in the place recommendation list (1010), place information (1002), photo review (1003) for each place, reviewer information (1004) for each photo review (1003), and 'Follow' for setting follow for the reviewer. A button 1001 and the like may be included.

In other words, in the place recommendation list 1010, reviews of places having the same or similar characteristics as those corresponding to the user's taste may be exposed.

As described above, according to embodiments of the present invention, user preference may be analyzed based on user feedback related to a place, and recommendation information corresponding to the user preference may be provided. Moreover, according to the embodiments of the present invention, it is possible to provide reviewer-centered recommendation information and place-oriented recommendation information based on user preference, and classify the weight level of taste according to the type of feedback to be used in different recommendation logics. can

The devices described above may be implemented as hardware components, software components, and/or a combination of hardware components and software components. For example, devices and components described in the embodiments include a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), and a programmable PLU (programmable logic unit). logic unit), microprocessor, or any other device capable of executing and responding to instructions. The processing device may run an operating system (OS) and one or more software applications running on the operating system. A processing device may also access, store, manipulate, process, and generate data in response to execution of software. For convenience of understanding, there are cases in which one processing device is used, but those skilled in the art will understand that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that it can include. For example, a processing device may include a plurality of processors or a processor and a controller. Other processing configurations are also possible, such as parallel processors.

Software may include a computer program, code, instructions, or a combination of one or more of the foregoing, which configures a processing device to operate as desired or processes independently or collectively. You can command the device. The software and/or data may be embodied in any tangible machine, component, physical device, computer storage medium or device to be interpreted by or to provide instructions or data to a processing device. there is. Software may be distributed on networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer readable media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer readable medium. In this case, the medium may continuously store a program executable by a computer or temporarily store the program for execution or download. In addition, the medium may be various recording means or storage means in the form of a single or combined hardware, but is not limited to a medium directly connected to a certain computer system, and may be distributed on a network. Examples of the medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROM and DVD, magneto-optical media such as floptical disks, and ROM, RAM, flash memory, etc. configured to store program instructions. In addition, examples of other media include recording media or storage media managed by an app store that distributes applications, a site that supplies or distributes various other software, and a server.

As described above, although the embodiments have been described with limited examples and drawings, those skilled in the art can make various modifications and variations from the above description. For example, the described techniques may be performed in an order different from the method described, and/or components of the described system, structure, device, circuit, etc. may be combined or combined in a different form than the method described, or other components may be used. Or even if it is replaced or substituted by equivalents, appropriate results can be achieved.

Therefore, other implementations, other embodiments, and equivalents of the claims are within the scope of the following claims.

Claims (20)

In a place-related recommendation method executed in a computer system,
The computer system includes at least one processor configured to execute computer readable instructions contained in a memory;
The recommendation method related to the place is,
analyzing, by the at least one processor, user taste using user feedback related to a place; and
Providing, by the at least one processor, recommendation information related to a place based on a feature corresponding to the user's preference.
A place-related recommendation method that includes. According to claim 1,
The step of analyzing the user's taste,
Analyzing the user's taste by classifying the level of preference according to the type of feedback
including,
The step of providing the recommendation information,
Providing different recommendation targets according to the user's preference divided by the severity level
A place-related recommendation method that includes. According to claim 1,
The step of analyzing the user's taste,
Collecting the user feedback based on the like reaction to the place
A place-related recommendation method that includes. According to claim 3,
The step of analyzing the user's taste,
Collecting the user feedback based on at least one of log data related to place search, log data related to receipt authentication or reservation or order for a place, and user review analysis results for a place.
A place-related recommendation method further comprising a. According to claim 3,
The step of analyzing the user's taste,
Analyzing the user's taste by dividing like reactions to places included in other users' reviews and like reactions to places the user has personally visited or used.
A place-related recommendation method that includes. According to claim 1,
The step of analyzing the user's taste,
Extracting a feature from content related to a place where the user feedback exists; and
Calculating a taste index for each feature using the user feedback
A place-related recommendation method that includes. According to claim 1,
The step of providing the recommendation information,
Selecting and recommending other users having similar tastes to the user's preference for a place
A place-related recommendation method that includes. According to claim 1,
The step of providing the recommendation information,
Selecting and recommending other users with similar tastes based on at least one of the regional distribution and industry category according to the user's taste
A place-related recommendation method that includes. According to claim 1,
The step of providing the recommendation information,
Selecting and recommending a place having characteristics corresponding to the user's preference
A place-related recommendation method that includes. According to claim 1,
The step of providing the recommendation information,
recommending a place commonly specified by a group of experts related to the user taste;
A place-related recommendation method that includes. According to claim 1,
The step of providing the recommendation information,
Providing common information about a place with other users based on the user preference
A place-related recommendation method that includes. A computer program stored in a computer-readable recording medium to execute the place-related recommendation method according to any one of claims 1 to 11 on a computer. In a computer system,
at least one processor configured to execute computer readable instructions contained in memory;
including,
The at least one processor,
Analyzing user taste using user feedback related to a place; and
A process of providing recommended information related to a place based on a feature corresponding to the user's preference
A computer system that processes According to claim 13,
The at least one processor,
Analyzing the user's taste by classifying the level of preference according to the type of feedback; and
A process of providing different recommended objects according to the user's taste divided into the level of severity
A computer system that processes According to claim 13,
The at least one processor,
Collecting the user feedback based on a like reaction to the place; and
A process of collecting the user feedback based on at least one of log data related to place search, log data related to receipt authentication or reservation or order for a place, and user review analysis results for a place.
A computer system that processes According to claim 15,
The at least one processor,
The process of analyzing user preferences by distinguishing like reactions to places included in other users' reviews and like reactions to places the user has personally visited or used
A computer system that processes According to claim 13,
The at least one processor,
The process of selecting and recommending other users who have similar tastes to the user's preference for a place
A computer system that processes According to claim 13,
The at least one processor,
A process of selecting and recommending other users with similar tastes based on at least one of the regional distribution and industry category according to the user's preference
A computer system that processes According to claim 13,
The at least one processor,
The process of selecting and recommending a place with characteristics corresponding to the user's preference
A computer system that processes According to claim 13,
The at least one processor,
A process of recommending a commonly specified place by a group of experts related to the user's taste
A computer system that processes

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