KR20230032811A - Method, system, and computer program to dynamically provide sub-item recommendation list for each item included in search results based on search query - Google Patents

Abstract

Disclosed are a method, system, and computer program capable of dynamically providing a sub-item recommendation list for each item included in a search result according to a search query. A search result providing method includes a step of providing an item corresponding to a search query as a search result. In the step of providing a search result, a sub-item corresponding to the search query is recommended among sub-items attached to the corresponding item for each item included in the search result.

Description

A method, system, and computer program capable of dynamically providing a list of sub-item recommendations for each item included in search results according to a search query SEARCH RESULTS BASED ON SEARCH QUERY}

The following description relates to a technique for providing an item search result that meets the query intent.

As user reviews for various items, various evaluation systems such as star rating reviews, text reviews, and photo reviews are being used.

In a review service using a place as an item, a place reservation function, a receipt authentication function, etc. may be used to authenticate a place visited or used by a user, and then the authenticated place information may be submitted together with the review.

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.

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.

Based on the relationship between an item and the sub-items possessed by the item, a sub-item recommendation list for each item included in the search result may be dynamically configured and provided according to a search query.

A search result providing method executed on a computer system, the computer system comprising at least one processor configured to execute computer readable instructions contained in a memory, the search result providing method comprising: the at least one processor , Providing an item corresponding to the search query as a search result, wherein the providing step recommends a lower item corresponding to the search query among lower items attached to the corresponding item for each item included in the search result. It provides a search result providing method characterized by doing.

According to one aspect, the search result providing method further includes searching for, by the at least one processor, a sub-item corresponding to the search query, and the providing includes an item to which the searched sub-item belongs. It may include selecting as an item search result.

According to another aspect, the search result providing method may further include: searching, by the at least one processor, a sub-item corresponding to the search query; and retrieving, by the at least one processor, a review corresponding to the search query among reviews registered for each item, wherein the providing step comprises: an item to which the searched sub-item belongs and the searched review A step of selecting a registered item as an item search result may be included.

According to another aspect, the providing may include selecting an item to which a lower item corresponding to the search query belongs as a candidate item; and selecting some of the candidate items as final items by using the popularity of the candidate items.

According to another aspect, the providing may include ranking the final item using at least one of attribute information of the final item, a candidate item attached to the final item, and a review registered in the final item. can do.

According to another aspect, the providing may include ranking the last item using a matching rate with attribute information of the last item for the search query; and boosting a ranking of the final item by using at least one of a matching rate with a candidate item attached to the final item for the search query and a matching rate with a review registered in the final item. can do.

According to another aspect, the providing may include recommending a review corresponding to the search query among reviews registered to the corresponding item for each item included in the search result together with lower items corresponding to the search query.

According to another aspect, the providing may include selecting a review corresponding to the search query by using an embedding similarity with the search query.

According to another aspect, the providing may further include ranking the selected reviews through positive/negative scoring of the selected reviews.

According to another aspect, the providing may further include ranking the selected review using at least one of sentence length, recency, popularity, and author rating of the selected review.

Provided is a computer program stored in a computer readable recording medium in order to execute the search result providing method on a computer.

A computer system comprising: at least one processor configured to execute computer readable instructions included in a memory, wherein the at least one processor includes a search result provider providing an item corresponding to a search query as a search result; , The search result providing unit provides a computer system for recommending, for each item included in the search result, a lower item corresponding to the search query among lower items attached to the corresponding item.

According to the embodiments of the present invention, based on the relationship between an item and the sub-item possessed by the item, a sub-item recommendation list for each item included in the search result is dynamically configured and provided according to a search query, thereby providing the user's search intention. Search results can be advanced to approach .

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 7 show examples of item search result screens according to one embodiment of the present invention.
8 is a flowchart illustrating an example of a process of ranking item search results according to an embodiment of the present invention.
9 illustrates an example of features used for review ranking according to an embodiment of the present invention.
10 is a flowchart illustrating an example of a process of ranking review recommendation results according to 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 techniques for providing item search results that meet query intent.

Embodiments, including those specifically disclosed in this specification, dynamically configure and provide a list of recommended sub-items for each item included in a search result according to a search query based on the relationship between an item and sub-items possessed by the corresponding item. can

In this specification, an item may mean a comprehensive search or recommendation target. For example, an item may include an object for which a user experience according to visit, use, or purchase may be reviewed. Also, the lower item may refer to an object possessed by the item, that is, an object belonging to the item secondarily. The user review may include a review of an item as well as an individual review of each sub-item.

Places such as restaurants, shops, famous places, and hot places may be cited as typical examples of items. In the case of a restaurant, menus sold by the restaurant may correspond to sub-items, and in the case of a store, items sold by the store may correspond to sub-items.

A search result providing system according to embodiments of the present invention may be implemented by at least one computer system, and a search result providing method according to embodiments of the present invention may include at least one computer system included in the search result providing system. can be performed through At this time, the 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 the search result providing method according to the 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 search result providing 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 (for example, an item review service, etc.) for which the application is intended through an application as a computer program 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 dynamically providing a sub-item recommendation list for each item included in a search result according to a search query 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 search that a computer system according to an embodiment of the present invention may perform. It is a flow chart showing an example of a result providing method.

The computer system 200 according to the present embodiment may provide an item 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 may provide a review space for items through a user's personal service page, and in relation to the item, the user visits or uses the item through a linkage function with a reservation/order service, a receipt authentication function, and the like. After authentication, the review written by the user can be linked and registered along with the authenticated item information. A user may write a review by specifying not only an item but also a sub-item within an item, and at this time, a review of a sub-item may be managed in association with the sub-item and the item to which the sub-item belongs.

The computer system 200 may provide an item-based search and recommendation environment for users, and in this case, reviews of items may be shared among users based on follow.

The processor 220 of the computer system 200 includes an item search unit 310 and a search result providing unit 320 as shown in FIG. 3 as components for performing a search result providing method to be described later. can do. 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 search result providing 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 item search unit 310 may be used as a functional representation of the processor 220 that controls the computer system 200 according to the above-described commands so that the computer system 200 searches for an item corresponding to a search query. there is.

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 search result providing method to be described later.

Steps included in the search result providing method to be described later may be performed in an order different from the order shown, and some of the steps may be omitted or additional processes may be further included.

Referring to FIG. 4 , in step S410, when the search query is received, the item search unit 310 searches for an item corresponding to the search query, and sub-items attached to the item and sub-items registered to the item are information about the searched item. You can provide a review. The item search unit 310 may search sub-items corresponding to the search query and reviews corresponding to the search query in order to provide search results suitable for the context.

Items and sub-items each have attribute information. For example, if the item is a restaurant, attribute information may include the restaurant's location, business name, industry category, phone number, description, rating, review, photo, reservation information, and the like. A sub-item of a restaurant may be a menu sold by the restaurant, and each menu has attribute information including a menu name, price, description, photo, rating, review, and the like.

Reviews are user feedback on items and sub-items, and may include reviews written through various review systems such as star rating reviews, keyword reviews, text reviews, and photo reviews.

The item search unit 310 may select sub-items having attribute information matching the search query and reviews including content matching the search query or content similar in meaning to the search query, from sub-items and reviews. .

In step S420, the search result providing unit 320 may provide an item search result for the search query by using the sub-item search result and the review search result. The search result providing unit 320 may select an item in which an item to which a lower item included in the lower item search result belongs and a review included in the review search result are linked to each other as an item search result or may be used for ranking of item search results.

The search result providing unit 320 may select an item selected as the search result for both the sub-item and the review for the search query in step S410 as the item search result, that is, common to the sub-item search result and the review search result. You can select an existing item with . Depending on the embodiment, an item selected as a search result of any one of sub-items and reviews may be selected as an item search result.

The search result providing unit 320 may provide a list of items selected as the item search result as a final search result corresponding to the search query. and at least some of the review search results may be provided as a recommendation list for a search query.

In other words, the search result providing unit 320 dynamically configures and provides a list of sub-items and review recommendations for each item included in the search result according to a search query, thereby providing search results suitable for the context based on the mutual relationship between items and sub-items. can provide. For each item included in the search results, a list of sub-items and reviews belonging to the item can be exposed. In particular, considering the user's search intention, sub-items and reviews that fit the search query are ranked higher on the list than other sub-items and reviews. can be exposed to

5 illustrates an example of an item search result screen according to an embodiment of the present invention.

Referring to FIG. 5 , the processor 220 may provide an item list 510 as a final search result corresponding to a search query 501 through an item search result screen 500 .

In this case, the item list 510 may be determined based on a lower item search result corresponding to the search query 501 and a review search result. In the item list 510, an item to which a sub-item having attribute information matching the search query 501 belongs, a review including content matching the search query 501 or content similar in meaning to the search query 501 is registered. It may consist of an item that has been selected, an item that belongs to both of the above conditions, and the like.

The processor 220 may provide both a lower item recommendation list 520 and a review recommendation list 530 for each item included in the item list 510 through the item search result screen 500 .

The sub-item recommendation list 520 may include sub-item search results corresponding to the search query 501, and the review recommendation list 530 may also include review search results corresponding to the search query 501.

In other words, the processor 220 may dynamically configure and provide the sub-item recommendation list 520 and review recommendation list 530 for each item included in the search result according to the search query 501 .

For example, when a user uses a restaurant menu keyword as a search query, even if the same restaurant is exposed in the search result, information on the corresponding restaurant may be differently exposed according to the search query.

Referring to FIG. 6 , it is assumed that <Restaurant I> corresponding to the item is included in the search result.

When 'Gangnam Pasta' is entered as a search query, recommended information related to <Restaurant I> consists of pasta menus sold in <Restaurant I> or exposes the pasta menu to the top (eg, the leftmost or topmost portion of the list). It can be configured and provided as a sub-item recommendation list (621) that is exposed to a location first recognized by the user, etc., and can also be provided in a review of <Restaurant Ⅰ>, a review containing pasta-related content, or a pasta menu of <Restaurant Ⅰ> A review recommendation list 631 composed of reviews registered in or exposed to the top may be provided together.

On the other hand, when 'Gangnam Pizza' is entered as a search query, recommendation information related to <Restaurant I> consists of pizza menus sold by <Restaurant I> or exposes the pizza menu to the top (eg, the leftmost side of the list, or It consists of a list of recommended sub-items (622) that is exposed at the position first recognized by the user, such as at the top, and reviews containing pizza-related content in the review of <Restaurant I> or reviews registered for the pizza menu of <Restaurant I>. Alternatively, a review recommendation list 632 that exposes the above may be provided.

In other words, the sub-item recommendation lists 621 and 622 and the review recommendation lists 631 and 632 may be configured differently according to the search query for the same item <Restaurant I>.

For example, as shown in FIG. 7 , when 'Shinjuku Pasta' is input as a search query, among the menus of <Restaurant X>, the list of recommended sub-items 721 that exposes the pasta menu at the top and among the reviews of <Restaurant X> A review recommendation list 731 that exposes reviews related to the pasta menu at the top may be provided. On the other hand, when 'Shinjuku Pizza' is input as a search query, a lower-item recommendation list 722 that exposes the pizza menu higher among the menus of <Restaurant X> and reviews related to the pizza menu among the reviews of <Restaurant X> are displayed higher. A review recommendation list 732 may be provided.

Among contents included in the search results, a visual display may be added for a keyword matching a search query. For example, a text color may be displayed in red or a highlight using a highlight may be added.

The processor 220 may provide an item list suitable for a context as a search result by determining an item search result using a sub-item search result corresponding to a search query and a review search result.

In addition, the processor 220 may provide recommendation information suitable for context among information about items by exposing a list of lower items and a review list corresponding to a search query for each item included in the search result. In this case, the processor 220 may target and preferentially expose a lower item matching the search query among lower items attached to the item and a review matching the search query among reviews registered to the item.

8 is a flowchart illustrating an example of a process of ranking item search results according to an embodiment of the present invention.

The processor 220 may rank item search results using attribute information of each item, sub-items, and reviews.

Referring to FIG. 8 , in step S801, the processor 220 may select a candidate item using a lower item search result corresponding to the search query and a review search result corresponding to the search query. For example, the processor 220 may select an item to which a lower item corresponding to a search query belongs as a candidate item. As another example, the processor 220 selects, as a candidate item, an item to which a review corresponding to the search query is registered as well as to which a sub-item corresponding to the search query belongs, that is, an item that exists in common in the sub-item search result and the review search result. can do.

In step S802, the processor 220 may select an item of a predetermined number or ratio among the candidate items as the final item by using the popularity of the item. Here, popularity may mean a user feedback score, and for example, a higher score may be calculated as the likes or ratings increase, the number of shares increases, and the number of registration reviews increases. In other words, the processor 220 may apply a popularity ranking through a user feedback score for each item.

In step S803, the processor 220 may rank item search results composed of final items by using a query-customized relevance feature using at least one of attribute information, sub-items, and reviews of each item. For example, the processor 220 may use at least one of a matching rate between a search query and attribute information, a matching rate between a search query and sub-items, and a matching rate between a search query and reviews as a query-customized relevance feature.

The processor 220, as attribute information existing in the item database, calculates a matching rate with a search query through the name, description, category, etc. of the item as well as the theme keyword related to the item, so as to perform customized query association for search result ranking. It can also be used as a feature.

Theme keywords include keywords related to sub-items and keywords unrelated to sub-items. In the case of restaurants, theme keywords can be divided into menu keywords and non-menu keywords. The theme keyword of the restaurant can be extracted not only from a pre-determined theme keyword dictionary, but also from restaurant attribute information such as industry category or menu name.

The processor 220 may rank the item search results by integrating a matching rate with lower items attached to an item, a matching rate with reviews registered in the item, and the like, in addition to a matching rate with attribute information.

The processor 220 may maintain a popularity ranking of search results through user feedback scores for each item, but may re-rank item search results using a matching rate with attribute information for a search query. In addition, the processor 220 applies a complementary ranking logic to respond to inaccuracies in attribute information through boosting for re-ranking of search results using a matching rate with sub-items and/or a matching rate with reviews. can do.

In addition, time keywords representing time zones such as 'breakfast', 'lunch', and 'dinner', or purposes representing purposes such as 'party', 'date', 'meeting', 'with family', 'with friends', etc. For queries including keywords, definitions for each keyword can be assigned based on review data through receipt authentication and used in ranking logic.

According to the present embodiments, a list of recommended sub-items for the same item included in a search result may be dynamically configured and exposed according to a search query.

9 illustrates an example of features used for review ranking according to an embodiment of the present invention.

For each item included in the search result, the processor 220 may recommend a review suitable for a context among reviews registered to the item, and may preferentially expose reviews more meaningful and related to the search query.

Referring to FIG. 9 , the processor 220 determines 1) the length of the review sentence, 2) the text quality including the sentimental score according to the positive and negative scoring of the review sentence, 3) the number of images included in the review, 4) Image quality, including the number of images included in the review that fall under the high-quality level, 5) Review writing date, 6) Recency including the difference between the review writing date and the most recent consumption date, 7) User who is the reviewer 's abusive rating, 8) whether or not the user's real name was authenticated, 9) the total number of reviews written by the user, 10) the number of followers of the user, 11) the user's rating including the number of authentication visits, 12) the review rating, 13) the review Review recommendation results may be ranked using popularity including the cumulative number of likes.

1) review sentence length, 2) sentiment score, 3) number of images, 4) number of high-quality images can be criteria for selecting reviews with substantial content, 5) review writing date, 6) review writing date and recent consumption date The difference between the reviews can be a criterion for selecting the most up-to-date review. 7) Abusing rating, 8) Real name verification, etc. can be criteria for selecting reviews with less malicious intent, and 9) total number of reviews written, 10) number of followers, 11) number of visits verified, etc. are written by experts. This can be a criterion for selecting reviews. 12) ratings, 13) cumulative number of likes, etc. can be criteria for selecting popular reviews.

The features described above are examples, and any features that can be weighted in the review ranking can be extensively applied.

10 is a flowchart illustrating an example of a process of ranking review recommendation results according to an embodiment of the present invention.

Referring to FIG. 10 , in step S1001, the processor 220 may select a review to be recommended through a search result using a similarity between a search query and review content. The processor 220 may calculate the degree of similarity with the search query by segmenting the review into meaningful sentence units and extracting a probability that a keyword corresponding to the search query occurs in the segmented sentence. A semantic review matching technique based on embedding can be used to match reviews with keywords matching the search query as well as reviews with content similar to the search query. Semantic review matching is a method of matching reviews with semantically similar content in addition to reviews that accurately include search queries. can For example, when the search query is 'pasta', even if 'pasta' is not directly mentioned, a review including content semantically related to 'pasta' may be selected as a recommendation target.

In step S1002, the processor 220 recommends reviews through scoring using at least one of text quality (emotion score), image quality, recency, user rating, and popularity, which are used as other review selection criteria in addition to similarity to the search query. Results can be ranked.

For example, the processor 220 may calculate a sentiment score according to a positive wording using a ridge-based sentiment dictionary for each keyword, and may assign a ranking weight based on the sentiment score. Sentiment score, one of the features that indicates text quality, is obtained by extracting positive words that are important variables through the Ridge Logistic Regression method that classifies positive and negative words in reviewed sentences and scoring their coefficient values. . The more positive the review sentence is, the larger the value is in a positive number, and the more negative the review sentence is, the smaller the value is in a negative number. Using these sentiment scores, the exposure influence of reviews containing positive wording can be increased.

As another example, the processor 220 may determine the review ranking based on the review's sentence length, recency, rating, cumulative number of likes, and the like. The processor 220 may assign a high ranking weight to a recently written review, a review written with an appropriate length, a review with a large number of accumulated likes, and a review with a high rating.

According to the present embodiments, a review recommendation list for the same item included in a search result may be dynamically configured and exposed according to a search query.

As such, according to the embodiments of the present invention, based on the relationship between an item and the sub-item possessed by the item, a list of sub-items and review recommendations for each item included in the search result is dynamically configured and provided according to a search query, thereby providing user Search results can be advanced to approach the search intention of.

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, one or more general purpose or special purpose computers. 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)

A search result providing method executed on a computer system,
The computer system includes at least one processor configured to execute computer readable instructions contained in a memory;
The search result providing method,
providing, by the at least one processor, an item corresponding to a search query as a search result;
including,
The step of providing,
Recommending a sub-item corresponding to the search query among sub-items attached to the item for each item included in the search result
A search result providing method characterized by According to claim 1,
The search result providing method,
Searching, by the at least one processor, a sub-item corresponding to the search query.
Including more,
The step of providing,
Selecting an item to which the searched sub-item belongs as an item search result
A search result providing method comprising a. According to claim 1,
The search result providing method,
searching for a sub-item corresponding to the search query by the at least one processor; and
Searching, by the at least one processor, a review corresponding to the search query among reviews registered for each item.
Including more,
The step of providing,
Selecting an item to which the searched sub-item belongs and an item to which the searched review is registered as an item search result
A search result providing method comprising a. According to claim 1,
The step of providing,
selecting an item to which a sub-item corresponding to the search query belongs as a candidate item; and
selecting some of the candidate items as final items by using the popularity of the candidate items;
A search result providing method comprising a. According to claim 4,
The step of providing,
Ranking the final item using at least one of attribute information of the final item, a candidate item attached to the final item, and a review registered in the final item.
A search result providing method comprising a. According to claim 4,
The step of providing,
ranking the last item by using a matching rate with attribute information of the last item for the search query; and
Boosting the ranking of the final item by using at least one of a matching rate with a candidate item attached to the final item for the search query and a matching rate with a review registered in the final item.
A search result providing method comprising a. According to claim 1,
The step of providing,
For each item included in the search result, recommending a review corresponding to the search query among reviews registered for the corresponding item together with a sub-item corresponding to the search query
A search result providing method characterized by According to claim 7,
The step of providing,
selecting a review corresponding to the search query by using an embedding similarity with the search query;
A search result providing method comprising a. According to claim 8,
The step of providing,
Ranking the selected reviews through positive/negative scoring of the selected reviews
A search result providing method further comprising a. According to claim 8,
The step of providing,
Ranking the selected reviews using at least one of sentence length, recency, popularity, and author ratings of the selected reviews.
A search result providing method further comprising a. A computer program stored in a computer readable recording medium to cause a computer to execute the search result providing method according to any one of claims 1 to 10. In a computer system,
at least one processor configured to execute computer readable instructions contained in memory;
including,
The at least one processor,
A search result provider providing items corresponding to the search query as search results.
including,
The search result providing unit,
Recommending a sub-item corresponding to the search query among sub-items attached to the item for each item included in the search result
A computer system that processes According to claim 12,
The at least one processor,
A search unit for searching for sub-items corresponding to the search query
Including more,
The search result providing unit,
Selecting an item to which the searched sub-item belongs as an item search result
Characterized by a computer system. According to claim 12,
The at least one processor,
A search unit for searching sub-items corresponding to the search query and searching for reviews corresponding to the search query among reviews registered for each item.
Including more,
The search result providing unit,
Selecting an item to which the searched sub-item belongs and an item to which the searched review is registered as an item search result
Characterized by a computer system. According to claim 12,
The search result providing unit,
Selecting an item to which a sub-item corresponding to the search query belongs as a candidate item;
Selecting some of the candidate items as final items by using the popularity of the candidate items
Characterized by a computer system. According to claim 15,
The search result providing unit,
Ranking the final item using at least one of attribute information of the final item, a candidate item attached to the final item, and a review registered in the final item.
Characterized by a computer system. According to claim 15,
The search result providing unit,
Ranking the final item using a matching rate with attribute information of the final item for the search query;
Boosting the ranking of the final item by using at least one of a matching rate with a candidate item attached to the final item for the search query and a matching rate with a review registered in the final item.
Characterized by a computer system. According to claim 12,
The search result providing unit,
For each item included in the search result, recommending a review corresponding to the search query among reviews registered for the corresponding item together with a sub-item corresponding to the search query
Characterized by a computer system. According to claim 18,
The search result providing unit,
Selecting a review corresponding to the search query using an embedding similarity with the search query
Characterized by a computer system. According to claim 19,
The search result providing unit,
Ranking the selected reviews using at least one of positive and negative scoring, sentence length, recency, popularity, and author rating of the selected reviews
Characterized by a computer system.

Images