KR102536775B1 - Method and system for providing search results incorporating the intent of search query - Google Patents

Abstract

According to an embodiment of the present disclosure, a method for providing search results reflecting the intention of a search query performed by at least one processor is provided. A method of providing search results reflecting the intent of a search query includes receiving a search query from a user terminal, determining one or more query pattern types for a search query based on one or more query intents extracted from the search query, and performing one or more query pattern types. and determining a ranking of each of a plurality of contents related to the search query based on the query pattern type.

Description

Method and system for providing search results reflecting the intention of a search query

The present disclosure relates to a method and system for providing search results reflecting the intent of a search query, and more particularly, to a method and system for providing content and snippets corresponding to the intent of a search extracted from a search query.

With the spread of mobile devices such as smart phones and the development of the Internet, users can input search words in applications having a search function to obtain desired search results easily and quickly in daily life, and can access various contents as search results. When a user inputs a search word, the search system extracts content including the keyword extracted from the search word from the database and provides it as a search result. Such a search system may determine the ranking of contents according to the degree of matching of keywords between search terms and contents, arrange the contents according to the determined ranking, and provide the contents to the user. In other words, content with a high degree of matching between a search word and a keyword may be ranked higher, and accordingly, content with a high degree of keyword matching may be preferentially provided to the user.

In this case, the user may input a search word with a clear intention to receive specific information and content. In the case of the conventional search result providing method, since the content ranking is determined according to the degree of keyword matching with the search term and the content is provided based on the determined ranking, there is a problem that the search result does not accurately reflect the user's search intention. . Therefore, in order to find content that satisfies the user's search intention, the user has to inconveniently check the content output as a search result in order or perform a re-search using a different keyword combination.

The present disclosure provides a search result providing method reflecting the intention of a search query, a computer program stored in a recording medium, and an apparatus (system) to solve the above problems.

The present disclosure may be implemented in a variety of ways, including a method, apparatus (system) or computer program stored on a readable storage medium.

A method for providing search results reflecting the intention of a search query performed by at least one processor according to an embodiment of the present disclosure includes receiving a search query from a user terminal, performing a search based on one or more query intentions extracted from the search query. Determining one or more query pattern types for the query, and determining a ranking of each of a plurality of contents associated with the search query based on the one or more query pattern types.

A computer program stored in a computer readable recording medium is provided to execute a search result providing method reflecting a query intention according to an embodiment of the present disclosure in a computer.

A search result providing system reflecting the intention of a search query according to an embodiment of the present disclosure includes a communication module, a memory, and at least one processor connected to the memory and configured to execute at least one computer-readable program included in the memory. and at least one program receives a search query from a user terminal, determines one or more query pattern types for the search query based on one or more query intents extracted from the search query, and determines one or more query pattern types based on the one or more query pattern types. and instructions for determining a ranking of each of a plurality of contents associated with a search query.

In various embodiments of the present disclosure, a query intention is identified from a search query input by a user, and a ranking factor suitable for the query intention is dynamically applied to rank content, thereby providing user needs. Priority can be given to content that suits you. That is, as a search result, the user may be preferentially provided with content corresponding to the user's query intention rather than simply content that matches the keyword of the search query.

In various embodiments of the present disclosure, snippets corresponding to each query intent are extracted in advance, and when a search query is input by a user, a snippet suitable for the query intent of the search query may be selected in real time and provided to the user. Therefore, the user is not simply a snippet that includes a part that uniformly matches a search query and a keyword in the body of content, but a part corresponding to the user's query intention, that is, a part that includes target information and content that the user actually wants to receive. A snippet containing may be provided.

In various embodiments of the present disclosure, not only the text of the content but also the document content, text structure, attached file, image, etc. are analyzed, so that content and snippets matching the query intent of the search query can be more accurately extracted.

According to various embodiments of the present disclosure, since a region corresponding to the query intent is highlighted in the snippet, the user may be provided with a highly readable snippet.

Embodiments of the present disclosure will be described with reference to the accompanying drawings described below, wherein like reference numbers indicate like elements, but are not limited thereto.
1 is a diagram illustrating an example in which a search result for a search query is provided to a user through a screen of a user terminal according to an embodiment of the present disclosure.
2 is a schematic diagram illustrating a configuration in which a plurality of user terminals are communicatively connected to an information processing system according to an embodiment of the present disclosure.
3 is a block diagram showing internal configurations of a user terminal and an information processing system according to an embodiment of the present disclosure.
4 is a detailed block diagram of a processor of an information processing system according to an embodiment of the present disclosure.
5 is a detailed block diagram of a processor of an information processing system according to another embodiment of the present disclosure.
6 is a flowchart illustrating a method of providing a search result reflecting a query intention according to an embodiment of the present disclosure.
7 is a diagram illustrating an example of providing search results reflecting the query intention of a search query according to an embodiment of the present disclosure.
8 is a diagram illustrating an example of providing search results reflecting the query intention of a search query according to another embodiment of the present disclosure.
9 is a diagram illustrating an example of providing search results reflecting the query intention of a search query according to another embodiment of the present disclosure.
10 is a diagram illustrating an example of providing different snippets according to the query intent of a search query according to an embodiment of the present disclosure.
11 is a diagram illustrating an example of providing a snippet in which a region associated with a query intent of a search query is highlighted according to an embodiment of the present disclosure.

Hereinafter, specific details for the implementation of the present disclosure will be described in detail with reference to the accompanying drawings. However, in the following description, if there is a risk of unnecessarily obscuring the gist of the present disclosure, detailed descriptions of well-known functions or configurations will be omitted.

In the accompanying drawings, identical or corresponding elements are given the same reference numerals. In addition, in the description of the following embodiments, overlapping descriptions of the same or corresponding components may be omitted. However, omission of a description of a component does not intend that such a component is not included in an embodiment.

Advantages and features of the disclosed embodiments, and methods of achieving them, will become apparent with reference to the following embodiments in conjunction with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms, but only the present embodiments make the present disclosure complete, and the present disclosure does not extend the scope of the invention to those skilled in the art. It is provided only for complete information.

Terms used in this specification will be briefly described, and the disclosed embodiments will be described in detail. The terms used in this specification have been selected from general terms that are currently widely used as much as possible while considering the functions in the present disclosure, but they may vary according to the intention of a person skilled in the related field, a precedent, or the emergence of new technologies. In addition, in a specific case, there is also a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the invention. Therefore, the terms used in the present disclosure should be defined based on the meaning of the terms and the general content of the present disclosure, not simply the names of the terms.

Expressions in the singular number in this specification include plural expressions unless the context clearly dictates that they are singular. Also, plural expressions include singular expressions unless the context clearly specifies that they are plural. When it is said that a certain part includes a certain component in the entire specification, this means that it may further include other components without excluding other components unless otherwise stated.

Also, the term 'module' or 'unit' used in the specification means a software or hardware component, and the 'module' or 'unit' performs certain roles. However, 'module' or 'unit' is not meant to be limited to software or hardware. A 'module' or 'unit' may be configured to reside in an addressable storage medium and may be configured to reproduce one or more processors. Thus, as an example, a 'module' or 'unit' includes components such as software components, object-oriented software components, class components, and task components, processes, functions, and attributes. , procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, or variables. Functions provided within components and 'modules' or 'units' may be combined into a smaller number of components and 'modules' or 'units', or further components and 'modules' or 'units'. can be further separated.

According to one embodiment of the present disclosure, a 'module' or 'unit' may be implemented with a processor and a memory. 'Processor' should be interpreted broadly to include general-purpose processors, central processing units (CPUs), microprocessors, digital signal processors (DSPs), controllers, microcontrollers, state machines, and the like. In some circumstances, 'processor' may refer to an application specific integrated circuit (ASIC), programmable logic device (PLD), field programmable gate array (FPGA), or the like. 'Processor' refers to a combination of processing devices, such as, for example, a combination of a DSP and a microprocessor, a combination of a plurality of microprocessors, a combination of one or more microprocessors in conjunction with a DSP core, or a combination of any other such configurations. You may. Also, 'memory' should be interpreted broadly to include any electronic component capable of storing electronic information. 'Memory' includes random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erasable-programmable read-only memory (EPROM), It may also refer to various types of processor-readable media, such as electrically erasable PROM (EEPROM), flash memory, magnetic or optical data storage, registers, and the like. A memory is said to be in electronic communication with the processor if the processor can read information from and/or write information to the memory. Memory integrated with the processor is in electronic communication with the processor.

In the present disclosure, a 'search query' may include text (eg, keywords, words, phrases, sentences, etc.) that can be entered and searched through a search engine, but is not limited thereto. For example, a search query includes text that a user inputs through an input UI of a search program such as a web browser or a search application, or text that a user can select by clicking one of a list of search words provided by the search program. can include In another example, the search term is not limited to text, and may include text or information that can be extracted from multimedia content such as images, videos, voices, and sounds.

In the present disclosure, 'intent of query' may refer to a purpose for which a user searches through a search query or target information to be actually obtained by searching through a search query. For example, the query intention may be expressed or extracted through at least a part of a keyword, word, or phrase included in a search query input by a user. For example, the purpose of a user's search through a search query for 'currently popular songs' is information on 'songs that have been listened to or selected by the public in the recent past (eg, within the last week or month). can include This query intention may be expressed by one or more of the keywords included in the search query, or other keywords, symbols, numbers, identifiers, etc. related to the keyword.

In the present disclosure, a 'query pattern' may be a keyword or information indicating a query intention of a search query. For example, a query pattern of a search query of 'currently popular songs' may be expressed as the keyword 'currently'. Also, in the present disclosure, a 'query pattern type' may be information or a symbol indicating a type of a query pattern of a search query. For example, 'nowadays', which is a query pattern of a search query such as 'currently popular songs', is unique information or an identifier that can indicate or identify it (for example, a 4-digit binary number in which the first digit is 1 ' 0x0001') may have a query pattern type.

In the present disclosure, a 'ranking factor' may refer to one or more factors that determine the rank or ranking of search results based on a search query. The ranking factor is the number of search keywords included in search results including various types of content (eg, web documents including text, images, or videos), and the number of user visits or clicks on the search results. , correlation with the search keyword, etc., but is not limited thereto and may include various factors that may affect the ranking of search results. For example, in the search query 'currently popular songs', a ranking factor associated with the keyword 'currently' indicating the query intention may be 'recent'. Accordingly, the rank or ranking of the search results according to the search query may be determined according to the time or date when the corresponding search results are generated or the newness of information included in the corresponding search results.

In the present disclosure, a 'snippet' refers to a portion of content or a document (eg, a web page, document, text or video content, etc.) retrieved through a search query and exposed as a search result. can refer to Snippets may be automatically generated based on content or documents retrieved through a search query. Specifically, the snippet may be generated to highlight or provide a preview or summary of a portion of content or documents highly relevant to a search query or search keyword. For example, in the case of documents retrieved through a search query, a snippet is displayed in a form of extracting a part of the body of a document matched with a search keyword included in the search query and highlighting the keyword from the corresponding part, or displaying the corresponding document It can be presented in the form of a pre-prepared representative explanation and summary.

1 is a diagram illustrating an example in which a search result for a search query is provided to a user 100 through a screen 120 of a user terminal 110 according to an embodiment of the present disclosure. The screen 120 shown in FIG. 1 shows an example in which the user 100 uses a search service by executing a search application on the user terminal (eg, smart phone) 110 . For example, the user 100 may perform a search by inputting a search query into the search word input unit 122 located at the top of the search application screen. Here, the search query may include one or more keywords representing one or more query intentions or search intentions of the user.

The user terminal 110 may display the content retrieved by the search query input from the user 100 on the screen 120 by arranging the content corresponding to a higher ranking in order. In one embodiment, the user terminal 110 may preferentially display content ranked higher according to the user 100's query intention. To this end, an information processing system (not shown) providing content may receive a search query from the user terminal 110 and determine a query pattern type of the search query based on a query intention extracted from the search query. The information processing system determines the ranking of each of a plurality of contents related to the search query based on the query pattern type of the search query, and arranges at least one or more contents among the plurality of contents based on the determined ranking through the user terminal 110. can be output. Here, the plurality of contents related to the search query may be contents matching one or more keywords included in the search query. For example, the plurality of contents related to the search query may be contents including one or more keywords included in the search query. Meanwhile, in order to determine the ranking of each of a plurality of contents based on the query pattern type of the search query, the information processing system determines the query pattern type of each of the plurality of contents in advance and labels the query pattern type corresponding to the corresponding contents. can do.

As shown in the screen 120, among search results including keywords ('dermatology', 'price') included in the search query 'dermatology price' input by the user 100, extracted from the search query Contents corresponding to 'price' or 'price information', which are the query intentions, may be ranked higher and displayed preferentially. For example, '[Gangnam Station Dermatology Mulgwangpil] Skin care at the price of a meal!', 'Real review of scar treatment ointment at dermatology acne extrusion price' and 'Suwon A dermatology clinic price ' is ranked at the top, and may be displayed on the user terminal 110 with priority over content that does not include dermatology price information.

The user terminal 110 may display one or more content links, titles, snippets, thumbnail images, hashtags, similar content links, etc. on the screen as search results. In one embodiment, the snippet displayed on the screen may be a part corresponding to the query intent among contents of the search result. To this end, the information processing system may extract a plurality of snippets associated with each query pattern type for a plurality of contents in advance. Thereafter, the information processing system may output a snippet associated with a query pattern type of a search query from among a plurality of snippets extracted in advance through the user terminal 110 .

As shown in the screen 120 , when displaying content as a search result, the user terminal 110 may also display a snippet corresponding to a query intention among a plurality of snippets of displayed content. For example, among the entire body of content displayed as a search result, a snippet including dermatology price information, that is, actual price information may be displayed. Actual amount information among the entire contents of each content displayed on the screen 120 '...but not even 100,000 won...', '...if you proceed to the 4th round, you should think of it in the middle of 200,000 won...' and ' ... A dermatology 33,000 won within 2 months, 1 year ...' may be displayed on the user terminal 110 as a snippet.

Accordingly, the user 100 may preferentially receive, as a search result, content corresponding to the user 100's query intention rather than simply content matching a keyword of a search query. In addition, the user 100 may be provided with a snippet including a part corresponding to the user 100's query intention, not a snippet including a part simply matching a search query and a keyword in the entire body of the provided content. there is. Meanwhile, in FIG. 1 , three pieces of content are displayed on the screen 120 of the user terminal 110, but the content is not limited thereto, and different numbers of content may be displayed.

2 is a schematic diagram illustrating a configuration in which a plurality of user terminals 210_1, 210_2, and 210_3 are communicatively connected to an information processing system 230 according to an embodiment of the present disclosure. As shown, a plurality of user terminals 210_1 , 210_2 , and 210_3 may be connected to an information processing system 230 capable of providing a search service through a network 220 . In one embodiment, the information processing system 230 includes one or more server devices and/or databases capable of storing, providing, and executing computer-executable programs (eg, downloadable applications) and data related to providing search services, or the like. It may include one or more distributed computing devices and/or distributed databases based on cloud computing services.

The search service provided by the information processing system 230 may be provided to the user through a search application installed in each of the plurality of user terminals 210_1, 210_2, and 210_3, a mobile browser application, or a web browser. For example, the information processing system 230 may provide information corresponding to a search query received from the user terminals 210_1, 210_2, and 210_3 through a search application or the like, or may perform a corresponding process.

A plurality of user terminals 210_1 , 210_2 , and 210_3 may communicate with the information processing system 230 through the network 220 . The network 220 may be configured to enable communication between the plurality of user terminals 210_1, 210_2, and 210_3 and the information processing system 230. Depending on the installation environment, the network 220 may be, for example, a wired network such as Ethernet, a wired home network (Power Line Communication), a telephone line communication device and RS-serial communication, a mobile communication network, a wireless LAN (WLAN), It may consist of a wireless network such as Wi-Fi, Bluetooth, and ZigBee, or a combination thereof. The communication method is not limited, and the user terminals (210_1, 210_2, 210_3) as well as a communication method utilizing a communication network (eg, mobile communication network, wired Internet, wireless Internet, broadcasting network, satellite network, etc.) that the network 220 may include ), short-range wireless communication between them may also be included.

In FIG. 2, a mobile phone terminal 210_1, a tablet terminal 210_2, and a PC terminal 210_3 are illustrated as examples of user terminals, but are not limited thereto, and the user terminals 210_1, 210_2, and 210_3 may perform wired and/or wireless communication. It can be any computing device that is capable of this and can have a search application, mobile browser application or web browser installed and running. For example, the user terminal includes a smartphone, a mobile phone, a navigation device, a computer, a laptop computer, a digital broadcasting terminal, a PDA (Personal Digital Assistants), a PMP (Portable Multimedia Player), a tablet PC, an AI speaker, a game console, It may include a wearable device, an internet of things (IoT) device, a virtual reality (VR) device, an augmented reality (AR) device, a set-top box, and the like. In addition, although three user terminals 210_1, 210_2, and 210_3 are shown in FIG. 2 to communicate with the information processing system 230 through the network 220, it is not limited thereto, and a different number of user terminals may be connected to the network ( 220) to communicate with the information processing system 230.

According to one embodiment, the information processing system 230 may receive a search query or a request for a search query from a plurality of user terminals 210_1, 210_2, and 210_3. In response to the search query or request received in this way, the information processing system 230 may provide at least one or more contents among a plurality of contents related to the search query to the plurality of user terminals 210_1, 210_2, and 210_3. For example, the information processing system 230 may provide ranking information and snippets of each of a plurality of contents determined based on the query intention of the search query to the plurality of user terminals 210_1, 210_2, and 210_3.

Figure 3 is a block diagram showing the internal configuration of the user terminal 210 and the information processing system 230 according to an embodiment of the present disclosure. The user terminal 210 may refer to any computing device capable of executing a search application, mobile browser application, or web browser and capable of wired/wireless communication, for example, the mobile phone terminal 210_1 of FIG. 2, a tablet It may include a terminal 210_2, a PC terminal 210_3, and the like. As shown, the user terminal 210 may include a memory 312 , a processor 314 , a communication module 316 and an input/output interface 318 . Similarly, the information processing system 230 may include a memory 332 , a processor 334 , a communication module 336 and an input/output interface 338 . As shown in FIG. 3, the user terminal 210 and the information processing system 230 are configured to communicate information and/or data through the network 220 using respective communication modules 316 and 336. It can be. In addition, the input/output device 320 may be configured to input information and/or data to the user terminal 210 through the input/output interface 318 or output information and/or data generated from the user terminal 210.

The memories 312 and 332 may include any non-transitory computer readable media. According to one embodiment, the memories 312 and 332 are non-perishable mass storage devices such as random access memory (RAM), read only memory (ROM), disk drives, solid state drives (SSDs), flash memory, and the like. (permanent mass storage device) may be included. As another example, a non-perishable mass storage device such as a ROM, SSD, flash memory, or disk drive may be included in the user terminal 210 or the information processing system 230 as a separate permanent storage device separate from memory. In addition, the memories 312 and 332 may store an operating system and at least one program code (eg, a code for a search application installed and driven in the user terminal 210).

These software components may be loaded from a computer readable recording medium separate from the memories 312 and 332 . A recording medium readable by such a separate computer may include a recording medium directly connectable to the user terminal 210 and the information processing system 230, for example, a floppy drive, a disk, a tape, a DVD/CD- It may include a computer-readable recording medium such as a ROM drive and a memory card. As another example, software components may be loaded into the memories 312 and 332 through a communication module rather than a computer-readable recording medium. For example, at least one program is loaded into the memories 312 and 332 based on a computer program installed by files provided by developers or a file distribution system that distributes application installation files through the network 220 . It can be.

The processors 314 and 334 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input/output operations. Instructions may be provided to processors 314 and 334 by memories 312 and 332 or communication modules 316 and 336 . For example, processors 314 and 334 may be configured to execute instructions received according to program codes stored in a recording device such as memory 312 and 332 .

The communication modules 316 and 336 may provide configurations or functions for the user terminal 210 and the information processing system 230 to communicate with each other through the network 220, and the user terminal 210 and/or information processing. System 230 may provide configurations or functions for communicating with other user terminals or other systems (eg, separate cloud systems, etc.). For example, a request or data generated by the processor 314 of the user terminal 210 according to a program code stored in a recording device such as the memory 312 (eg, a search query or a search request) is transmitted through the communication module 316 ) may be transmitted to the information processing system 230 through the network 220 according to the control. Conversely, a control signal or command provided under the control of the processor 334 of the information processing system 230 passes through the communication module 336 and the network 220 and through the communication module 316 of the user terminal 210. It may be received by the user terminal 210 . For example, the user terminal 210 may receive information about a plurality of contents and snippets associated with a search query from the information processing system 230 through the communication module 316 .

The input/output interface 318 may be a means for interfacing with the input/output device 320 . As an example, the input device may include a device such as a camera, keyboard, microphone, mouse, etc. including an audio sensor and/or image sensor, and the output device may include a device such as a display, speaker, haptic feedback device, or the like. can As another example, the input/output interface 318 may be a means for interface with a device in which a configuration or function for performing input and output is integrated into one, such as a touch screen. For example, when the processor 314 of the user terminal 210 processes a command of a computer program loaded into the memory 312, information and/or data provided by the information processing system 230 or other user terminals are used. A service screen or the like configured as described above may be displayed on the display through the input/output interface 318 . Although the input/output device 320 is not included in the user terminal 210 in FIG. 3 , it is not limited thereto, and the user terminal 210 and the user terminal 210 may be configured as one device. In addition, the input/output interface 338 of the information processing system 230 is connected to the information processing system 230 or means for interface with a device (not shown) for input or output that the information processing system 230 may include. can be In FIG. 3, the input/output interfaces 318 and 338 are shown as separate elements from the processors 314 and 334, but are not limited thereto, and the input/output interfaces 318 and 338 may be included in the processors 314 and 334. there is.

The user terminal 210 and the information processing system 230 may include more components than those shown in FIG. 3 . However, there is no need to clearly show most of the prior art components. According to one embodiment, the user terminal 210 may be implemented to include at least some of the aforementioned input/output devices 320 . In addition, the user terminal 210 may further include other components such as a transceiver, a global positioning system (GPS) module, a camera, various sensors, and a database. For example, when the user terminal 210 is a smart phone, it may include components that are generally included in a smart phone, for example, an acceleration sensor, a gyro sensor, a camera module, various physical buttons, and a touch screen. Various components such as a button using a panel, an input/output port, and a vibrator for vibration may be implemented to be further included in the user terminal 210 . According to one embodiment, the processor 314 of the user terminal 210 may be configured to operate an application providing a search service. At this time, codes related to the application and/or program may be loaded into the memory 312 of the user terminal 210 .

While a program for an application providing a search service is running, the processor 314 uses an input device such as a camera, microphone, or the like including a touch screen, keyboard, audio sensor, and/or image sensor connected to the input/output interface 318. Inputted or selected text, image, video, voice and/or action may be received, and the received text, image, video, voice and/or action may be stored in the memory 312 or the communication module 316 and network It can be provided to the information processing system 230 through 220. For example, processor 314 may receive user input for a search query.

In one embodiment, the processor 314 receives user input including a search query or search request entered on a web browser or an application providing a search service through the input device 320, and processes the search query or search request. It can be provided to the information processing system 230 through the network 220 and the communication module 316 . For example, the processor 314 may receive a user input for a search query input to a search word input unit through an input device 320 such as a touch screen or a keyboard, and transmit the received search query to the communication module 316 and the communication module 316. It can be provided to the information processing system 230 through the network 220 . As another example, the processor 314 may receive a user input including a search query through an input device 320 such as a touch screen, mouse, or keyboard, and in response to the user input, the processor 314 may transmit the search query to the information processing system. (230).

The processor 314 of the user terminal 210 manages, processes, and/or stores information and/or data received from the input device 320, other user terminals, the information processing system 230, and/or a plurality of external systems. can be configured to Information and/or data processed by processor 314 may be provided to information processing system 230 via communication module 316 and network 220 . The processor 314 of the user terminal 210 may transmit and output information and/or data to the input/output device 320 through the input/output interface 318 . For example, the processor 314 may display the received information and/or data on the screen of the user terminal. In one embodiment, the processor 314 may display at least one or more contents among a plurality of contents on a screen based on a ranking of each of a plurality of contents related to a search query in which the query intention is reflected. For example, the processor 314 arranges a plurality of contents related to the search query received from the memory 312 and/or the information processing system 230 in order from the contents corresponding to the highest ranking, and displays them on the screen 120. can do. In another embodiment, the processor 314 may display links, snippets, thumbnail images, hashtags, and the like of one or more content on the screen. For example, the processor 314 may display a snippet corresponding to the query intent received from the memory 312 and/or the information processing system 230 with respect to one or more contents on the screen. In one embodiment, the processor 314 may highlight and display a partial region associated with one or more query pattern types in the snippet on the screen. For example, the processor 314 may highlight a partial region associated with one or more query pattern types in the snippet through at least one of bold text processing and background processing and display the highlighted portion on the screen.

The processor 334 of the information processing system 230 may be configured to manage, process, and/or store information and/or data received from a plurality of user terminals 210 and/or a plurality of external systems. Information and/or data processed by the processor 334 may be provided to the user terminal 210 through the communication module 336 and the network 220 . In one embodiment, the processor 334 of the information processing system 230 determines one or more query pattern types of the search query based on one or more query intents extracted from the search query received from the user terminal 210. , and a ranking of each of a plurality of contents related to the search query may be determined based on one or more query pattern types. To this end, the processor 334 may extract one or more keywords corresponding to one or more query intents from the search query and determine one or more query pattern types corresponding to the one or more extracted keywords. Alternatively, the processor 334 may extract one or more query intents from the search query through natural language processing (NLP) and determine one or more query pattern types for the extracted one or more query intents.

In one embodiment, one or more query pattern types are represented by one or more bits, and the one or more bits may be pre-matched with one or more ranking factors that are weighted factors in determining the ranking of a plurality of contents. there is. In this case, the processor 334 calculates a ranking score of each of the plurality of contents associated with the search query based on one or more ranking factors, and ranks each of the plurality of contents associated with the search query based on the ranking score of each of the plurality of contents. can determine

In one embodiment, the processor 334 may pre-label query pattern types of a plurality of contents included in the contents DB. For example, the processor 334 may label the determined query pattern type based on at least one of text, text structure, attached file, and image included in the plurality of contents. In this case, the processor 334 may determine a ranking of each of the plurality of contents associated with the search query based on the query pattern type of the plurality of contents and one or more ranking factors.

In one embodiment, the processor 334 may pre-extract at least one snippet from each of a plurality of contents included in the contents DB. For example, the processor 334 may extract at least one or more snippets from each of the plurality of contents by analyzing at least one of text, text structure, attached file, and image included in each of the plurality of contents. Also, the processor 334 may extract one or more snippets associated with the query pattern type of each of the plurality of contents determined based on at least one of text, text structure, attached file, and image included in each of the plurality of contents.

The processor 334 of the information processing system 230 uses the output device 320 such as a display output capable device (eg, a touch screen, a display, etc.) or an audio output capable device (eg, a speaker) of the user terminal 210. It may be configured to output processed information and/or data. In one embodiment, the processor 334 may output at least one or more contents of a plurality of contents related to the search query through the user terminal 210 based on the determined ranking. For example, the processor 334 may cause the user terminal 210 to arrange and output a plurality of contents related to a search query in order from contents corresponding to a higher ranking.

In one embodiment, the processor 334 may output a snippet of at least one or more contents among a plurality of contents related to the search query through the user terminal 210 based on the determined ranking. For example, when the processor 334 extracts one or more snippets associated with each query pattern type of a plurality of contents, the processor 334 sends the snippet associated with one or more query pattern types among the one or more snippets to the user terminal. can be output through In addition, the user terminal 210 may output at least some of one or more snippets through the user terminal according to preset priorities for one or more query pattern types. In one embodiment, the processor 334 may emphasize and output a partial region associated with one or more query pattern types in the snippet. For example, the processor 334 may emphasize and output a partial region associated with one or more query pattern types in the snippet through at least one of bold text processing and background processing.

4 is a detailed block diagram of a processor 334 of an information processing system according to an embodiment of the present disclosure. As shown, the processor 334 includes a query pattern type determining unit 410 according to query intent classification, a ranking determining unit 420, and a content providing unit 430, and may be connected to a content DB 440. . Here, the content DB 440 may be included in an internal storage device of the information processing system or included in an external storage device connected to the information processing system. Information on a plurality of contents may be stored in the contents DB 440 . For example, the content DB 440 may store a plurality of contents, links to the plurality of contents, one or more snippets extracted from each of the plurality of contents, thumbnail images, and the like.

According to the query intent classification, the query pattern type determiner 410 may receive a search query from a user terminal and extract one or more query intents from the received search query. In an embodiment, the query pattern type determiner 410 according to the query intent classification may extract one or more keywords corresponding to one or more query intents from a search query. For example, the query pattern type determiner 410 according to the query intent classification may extract one or more of the keywords and/or similar keywords included in Table 1 below from the search query, and thus generate one or more queries from the search query. intent can be extracted. That is, the query pattern type determination unit 410 according to the query intention classification extracts the keyword 'nowadays' and the keyword 'list' from the search query 'list of restaurants in Busan these days', and accordingly, each 'view point' from the corresponding search query. Query intentions for 'trend' and 'item recommendation' can be extracted.

query intent keyword point of view trend These days, recently, today, tomorrow, ... Price information price, cost, estimate, how much, ... time information time, period, schedule, ... location information Address, store, location, place, ... other numbers Population, age, height, phone number,... multimedia information Images, videos, wallpapers, photo collections, ... Item recommendation List, list, recommendation, ...

In another embodiment, the query pattern type determiner 410 according to the query intent classification may extract one or more query intents from the search query through natural language processing. For example, when the search query includes the sentence 'Find a list of popular restaurants in Busan these days', the query pattern type determiner 410 according to the query intent classification performs syntax analysis, semantic analysis, etc. on the above sentence. Through the execution of , it can be derived that the query intent indicated by the above sentence includes 'view trend' and 'item recommendation'. In an embodiment, the query pattern type determiner 410 according to the query intent classification may be any one of a natural language processing model, a stochastic statistical model, and an artificial neural network model configured to derive a query intent corresponding to an input sentence or phrase. can include

Based on the query intent classification, the query pattern type determiner 410 may determine one or more query pattern types of the search query based on one or more query intents extracted from the search query. Here, one or more query pattern types are represented by one or more bits, and one or more query pattern types may be matched with one or more query intentions in advance. For example, as shown in Table 2 below, the query intention and the query pattern type may be matched in advance.

query intent query pattern type point of view trend 0x0001 Price information 0x0010 Item recommendation 0x0100

For example, based on the query intent 'view trend' and 'item recommendation' extracted from the search query 'list of recent restaurants in Busan', the query pattern type of the search query is '0x0001' and '0x0001' corresponding to each query intent. It can be determined as 0x0100'. Alternatively, these plurality of query pattern types may be merged and expressed as '0x0101'.

After that, the ranking determining unit 420 may determine a ranking of each of a plurality of contents related to the search query based on one or more query pattern types determined by the query pattern type determining unit 410 according to the query intention classification. Here, information on a plurality of contents related to the search query may be received from the contents DB 440 . In one embodiment, the ranking determiner 420 determines one or more ranking factors, calculates a ranking score for each of a plurality of contents associated with a search query based on the one or more ranking factors, and calculates a ranking score for each of a plurality of contents. Based on this, a ranking of each of a plurality of contents related to the search query may be determined. Here, one or more bits of one or more query pattern types may be pre-matched with one or more ranking factors as shown in Table 3 below, and the ranking factor may be an element that assigns a weight to determining the ranking of a plurality of contents.

query pattern type ranking factor 0x0101 Up-to-date, cataloged information 0x0010 number-price information

For example, when the query pattern type determined by the query pattern type determiner 410 according to the query intent classification is '0x0101', the ranking determiner 420 determines 'up-to-date' and 'list-type information' corresponding thereto. may be determined as a ranking factor. After that, the ranking determining unit 420 may assign a weight to a ranking score of content related to 'recentness', which is a ranking factor, among a plurality of contents. Also, the ranking determiner 420 may assign a weight to a ranking score of content related to 'list-type information', which is a ranking factor, among a plurality of contents. The ranking determination unit 420 may determine a ranking of each of a plurality of contents according to the finally calculated ranking score. Therefore, the score of the content having the ranking factors 'recency' and/or 'list-type information' may be higher than the score of the content without 'recency' and 'list-type information', and may be ranked higher among search results. can Here, the ranking determiner 420 may assign different weights according to the degree of association of each of the plurality of contents with respect to the ranking factor. For example, in the case of the 'recency' ranking factor, different weights may be assigned according to the degree of recency. That is, the weight associated with 'recency' assigned to the ranking score of content uploaded one hour ago may be greater than the weight associated with 'recency' assigned to the ranking score of content uploaded one day ago.

The content providing unit 430 provides the user terminal with at least one or more contents among a plurality of contents, and outputs at least one or more contents among the plurality of contents related to the search query based on the ranking determined by the ranking determination unit 420. can do. That is, the content providing unit 430 may arrange and output the content to the user terminal in order of high ranking among the plurality of content. Accordingly, the user may be preferentially provided with content corresponding to the intention of the query among a plurality of content related to the search query.

Tables 1 to 3 described above each show an example of a correspondence relationship between 'inquiry intent-keyword', 'query intent-query pattern type', and 'query pattern type-ranking factor', but is not limited thereto. Accordingly, this correspondence can be newly added or expanded through a search query or content analysis. For example, 'query intent' and 'keyword' may be expanded as new query intent classifications and new keywords are added, respectively. Also, as described above, the query pattern type may be expressed as a 4-digit binary number, but is not limited thereto. For example, depending on the total number of query pattern types, it can be expressed as a binary number with different digits.

5 is a detailed block diagram of a processor 334 of an information processing system according to another embodiment of the present disclosure. As shown, the processor 334 may include a query pattern type determiner 410 according to query intent classification, a ranking determiner 420, a content provider 430, and a content DB 440. In addition, the processor 334 may further include a content labeling unit 510, a snippet extraction unit 520, and a snippet providing unit 530. The query pattern type determining unit 410, the ranking determining unit 420, the content providing unit 430, and the content DB 440 according to the query intention classification of the processor 334 are the processor 334 shown in FIG. Since it includes the same or similar configuration or function as the corresponding component, duplicate descriptions will be omitted below.

The content labeling unit 510 may label query pattern types of a plurality of contents stored in the content DB 450 . In one embodiment, the content labeling unit 510 is based on at least one of text, text structure (eg, table structure, ranking structure, list structure, etc.), attached file, and image included in each of a plurality of contents. Each of the plurality of contents may be labeled with the determined query pattern type. For example, the content labeling unit 510 may analyze text and list structures included in a plurality of contents, and label content having list-type information among the plurality of contents with a query pattern type of '0x0100'.

In one embodiment, when labeling a query pattern type based on attachments included in a plurality of pieces of content, the content labeling unit 510 may perform an attachment file extension name, an attached file title, a creation date of the attached file, and the attached file. A query pattern type may be determined and labeled by analyzing the included information. For example, in the case of content to which a file having an extension of '.mp3' is attached, a corresponding query pattern type such as 'voice information' or 'multimedia information' may be labeled. In another embodiment, when labeling a query pattern type based on images included in a plurality of contents, the content labeling unit 510 analyzes text information, image information, etc. included in the images to determine the query pattern type; can be labeled. For example, in the case of content to which a 'musical score' image is attached, a query pattern type corresponding to 'musical score information', 'music information', or 'multimedia information' may be labeled.

The task of labeling query pattern types of the plurality of contents may be executed before a search result for a search query or content extraction is executed. Also, the task of labeling the query pattern types of the plurality of contents may be performed by an automatic labeling technique using a stochastic statistical model, an artificial neural network model, or the like configured to determine a query pattern type for each of the plurality of contents. Alternatively, the content labeling unit 510 may label query pattern types of a plurality of content according to information input to the information processing system by a human operator directly performing a labeling task. The content labeling unit 510 may store the labeled query pattern types in the content DB 440 in association with a plurality of content.

Then, with respect to the search query input from the user, the ranking determiner 420 may determine a ranking of each of the plurality of contents related to the search query based on the query pattern type of the plurality of contents and one or more ranking factors. For example, the ranking determining unit 420 may determine the ranking of each of the plurality of contents so that the contents labeled with the query pattern type corresponding to the ranking factor rank higher among the plurality of contents. That is, when the ranking factor is 'list-type information', the ranking determiner 420 may determine the ranking of each of the plurality of contents such that contents having list-type information labeled with '0x0100' in advance are ranked higher.

The snippet extractor 520 may extract at least one or more snippets from each of a plurality of contents. In one embodiment, the snippet extractor 520 may extract at least one snippet from each of the plurality of contents by analyzing at least one of text, text structure, attached file, and image included in each of the plurality of contents. there is. For example, the snippet extractor 520 extracts one or more snippets associated with a query pattern type of each of a plurality of contents determined based on at least one of text, text structure, attached file, and image included in each of a plurality of contents. can be extracted. Here, the snippet extractor 520 may extract, as a snippet associated with the corresponding query pattern type, a portion on which a query pattern type is labeled, among the texts of each of the plurality of contents. The snippet extractor 520 may store the extracted snippet in the content DB 440 in association with a plurality of content.

The snippet providing unit 530 may output a snippet of at least one or more contents among a plurality of contents related to the search query based on the determined ranking through the user terminal. In an embodiment, the snippet providing unit 530 may output a snippet associated with one or more query pattern types (ie, a query pattern type of a search query) from among one or more snippets through a user terminal. For example, when the query pattern type determiner 410 according to the query intent classification determines the query pattern type of the search query as '0x0001' corresponding to the 'viewpoint trend' of the query intent extracted from the search query, the snippet The study 530 may output a snippet associated with '0x0001' through the user terminal.

In an embodiment, the snippet providing unit 530 may output at least some of the one or more snippets through the user terminal according to preset priorities for one or more query pattern types. For example, when the query pattern type determining unit 410 according to the query intent classification determines the query pattern type of the search query as '0X0101' by merging '0x0001' and '0x0100', the snippet providing unit 530 can output a snippet related to '0x0100', which is prioritized according to a preset priority, through a user terminal.

In one embodiment, the snippet providing unit 530 may emphasize and output a partial region associated with one or more query pattern types in the snippet. For example, the snippet providing unit 530 may emphasize and output a partial region associated with one or more query pattern types in the snippet through at least one of bold text processing and background processing.

6 is a flowchart illustrating a method 600 of providing a search result reflecting a query intention according to an embodiment of the present disclosure. In one embodiment, the method 600 of providing a search result reflecting the query intent may be performed by a processor (eg, at least one processor of a user terminal and/or an information processing system). As shown, the search result providing method 600 may be initiated when a processor receives a search query from a user terminal (S610).

Thereafter, the processor may determine one or more query pattern types for the search query based on one or more query intentions extracted from the search query (S620). In an embodiment, the processor may extract one or more query intents through one or more keywords included in the search query and determine one or more query pattern types for the one or more query intents. In another embodiment, the processor may extract one or more query intents from a search query via natural language processing (eg, Natural Language Understanding, etc.) and determine one or more query pattern types for the one or more query intents. there is. Here, one or more query pattern types are represented by one or more bits, and the one or more bits may be pre-matched with one or more ranking factors that are weighted factors in determining the ranking of a plurality of contents.

Thereafter, the processor may determine a ranking of each of a plurality of contents related to the search query based on one or more query pattern types (S630). In one embodiment, the processor calculates a ranking score of each of a plurality of contents associated with the search query based on one or more ranking factors, and ranks each of a plurality of contents associated with the search query based on the ranking score of each of the plurality of contents. can decide In another embodiment, the processor may determine a ranking of each of the plurality of contents for the search query based on the query pattern type of the plurality of contents and one or more ranking factors. To this end, the processor may label query pattern types of a plurality of contents in advance. For example, the determined query pattern type may be labeled based on at least one of text, text structure, attached file, and image included in a plurality of contents. When new content is uploaded to the content DB, the processor may label the query pattern type of the corresponding content in real time. Alternatively, the processor may label query pattern types of new content stored in the content DB at regular intervals. In one embodiment, the processor may output at least one or more contents of a plurality of contents related to the search query through the user terminal based on the determined ranking.

The processor may extract at least one or more snippets from each of a plurality of contents. For example, the processor may pre-extract at least one or more snippets from each of a plurality of contents and store them in the contents DB. Alternatively, when a search query is received, the processor may extract at least one or more snippets from each of a plurality of contents associated with the search query in real time. In an embodiment, the processor may extract at least one or more snippets from each of the plurality of contents by analyzing at least one of text, text structure, attached file, and image included in each of the plurality of contents. For example, the processor may extract one or more snippets associated with the query pattern type of each of the plurality of contents determined based on at least one of text, text structure, attached file, and image included in each of the plurality of contents.

Based on the determined ranking, the processor may output a snippet of at least one or more contents among a plurality of contents related to the search query through the user terminal. In one embodiment, the processor may output a snippet associated with one or more query pattern types among one or more snippets through a user terminal. In another embodiment, the processor may output at least some of the one or more snippets through the user terminal according to preset priorities for one or more query pattern types.

In one embodiment, the processor may emphasize and output a partial region associated with one or more query pattern types in the snippet. For example, the processor may emphasize and output a partial region associated with one or more query pattern types in the snippet through at least one of boldface processing and background processing. Alternatively, the processor may emphasize and output some regions of the snippet related to one or more query pattern types by arranging them in a list form. In another embodiment, the processor may output a snippet in which at least one of an attached file and an image among a plurality of contents related to the search query is highlighted.

7 is a diagram illustrating an example of providing search results reflecting the query intention of a search query according to an embodiment of the present disclosure. The processor may receive a search query from a user terminal and determine one or more query pattern types for the search query based on one or more query intents extracted from the search query. In one embodiment, the processor may extract one or more keywords corresponding to one or more query intents from the search query and determine one or more query pattern types corresponding to the one or more keywords. The processor may calculate a ranking score of each of the plurality of contents associated with the search query based on a ranking factor corresponding to the determined query pattern type, and determine a ranking of each of the plurality of contents based on the ranking score of each of the plurality of contents. Here, the ranking factor may correspond to a factor for assigning a weight in determining the ranking of each of a plurality of contents. The processor may output one or more contents among a plurality of contents to the user terminal based on the ranking determined in this way. For example, a plurality of contents may be output to the user terminal after being arranged in order from the contents having a higher ranking. That is, content corresponding to a higher ranking may be output with priority over content corresponding to a lower ranking.

As shown, the processor may receive the search query 'today's fortune' input to the search word input unit 702 on the screen of the user terminal. Then, the processor extracts the keyword 'today' corresponding to the query intent 'time point trend' from the received 'today's horoscope' and sets the query pattern type to '0x0001' corresponding to the keyword 'today'. can decide The processor calculates a ranking score of each of a plurality of contents related to the search query 'today's fortune' based on the ranking factor 'recency' corresponding to the determined query pattern type '0x0001', and based on the ranking score of each of the plurality of contents It is possible to determine the ranking of each of the plurality of contents. In one embodiment, the processor calculates the ranking score by assigning a weight to the ranking score of each of the plurality of contents according to the 'newness' of the content, and determines the ranking of each of the plurality of contents based on the calculated ranking score. . In this case, the processor may assign different weights to each of the plurality of contents according to the degree of 'refreshment' of the contents. That is, the processor may assign a higher weight to content with high 'recency' rather than content with relatively low 'recency'.

As shown, the first content 'today's horoscope (September 16) constellation horoscope' (710) uploaded an hour ago with a very high 'recency', and the second content 'today's horoscope on the 16th day of September (Wednesday) )' (720) and the third content 'lunch yum yum, shift optician + today's horoscope' (730) uploaded 3 hours ago are relatively out-of-date content (for example, content uploaded a day ago or a month ago) (not shown) may be ranked higher and preferentially output. In addition, the first content 710 and the second content 720 uploaded 1 hour ago are ranked higher than the third content 730 uploaded 3 hours ago, so the first content 710 and the second content 720 ), the third content 730 may be arranged in order and displayed on the screen 700 .

8 is a diagram illustrating an example of providing search results reflecting the query intention of a search query according to another embodiment of the present disclosure. The processor may label query pattern types of a plurality of contents in advance. In an embodiment, the determined query pattern type may be labeled based on at least one of text, text structure, attached file, and image included in the plurality of contents. For example, a query pattern type may be labeled by analyzing text included in a plurality of contents and a structure in which the texts are arranged. That is, the processor may label the query pattern type '0x0100' corresponding to 'list-type information' with respect to content in which texts are listed in a list-type structure or configuration (layout). The first content 'list of 5 favorite restaurants in Busan' (810) and the second content 'list of 14 best restaurants in Busan to visit in the summer, Seomyeon, Yeonsan-dong, Haeundae' (820) displayed on the screen 800 of FIG. Since it includes a list, that is, 'list-type information', '0x0100' may be labeled by a processor in advance and stored in the contents DB.

Based on the query pattern type of the plurality of contents labeled in advance and the ranking factor determined by the search query, the processor may determine a ranking of each of the plurality of contents related to the search query. For example, the processor may determine the ranking of each of the plurality of contents so that the contents labeled with the query pattern type corresponding to the ranking factor rank higher among the plurality of contents. As shown, the processor may receive a search query 'list of restaurants in Busan' input to the search word input unit 802 of the screen 800 of the user terminal. Thereafter, the processor may analyze the intention of 'item recommendation' in the received 'list of restaurants in Busan' and determine the intention of the search query as the query pattern type '0x0100'. Here, the processor calculates ranking scores for each of the plurality of contents related to the search query 'list of restaurants in Busan' based on the ranking factor 'list information' corresponding to the query pattern type '0x0100' and the query pattern type of the plurality of contents. And, based on the calculated ranking score, it is possible to determine the ranking of each of the plurality of contents. That is, the processor may add a weight to the ranking scores of the first content 810 and the second content 820 including 'list-type information' labeled with '0x0100' in advance, and accordingly, the first content 810 ) and the second content 820 may be ranked higher among a plurality of content and may be preferentially output.

The processor may extract at least one or more snippets from each of a plurality of contents in advance. In an embodiment, the processor may extract at least one or more snippets from each of the plurality of contents by analyzing at least one of text, text structure, attached file, and image included in each of the plurality of contents. For example, the processor may extract one or more snippets associated with the query pattern type of each of the plurality of contents determined based on at least one of text, text structure, attached file, and image included in each of the plurality of contents. Here, one or more snippets associated with the query pattern type of each of the plurality of contents may be a part from which the query pattern type is labeled among the main body of each of the plurality of contents.

The processor determines the query pattern type '0x0100' of each of the plurality of contents determined based on at least one of text, text structure, attached file, and image included in each of the first content 810 and the second content 820 of FIG. 8 . You can extract one or more snippets associated with . That is, when labeling the query pattern types of the first content 810 and the second content 820, the 'list-type information' that is the basis for labeling the query pattern type '0x0100' in the body of each content is included. can be extracted as a snippet related to '0x0100'. Similarly, when the first content 810 and/or the second content 820 are labeled with a query pattern type of '0x0010' other than '0x0100', the other query pattern type '0x0010' is labeled. The part can be extracted as a snippet related to the query pattern type '0x0010'. Accordingly, the processor may extract a plurality of different snippets for each query pattern type for one content.

Based on the determined ranking, the processor may output a snippet of at least one or more contents among a plurality of contents related to the search query through the user terminal. In one embodiment, the processor may output a snippet associated with one or more query pattern types (ie, a query pattern type of a search query) among one or more snippets through a user terminal. For example, among the snippets of the first content 810 and the second content 820, a 'list' that is a snippet associated with the query pattern type '0x0100' of the search query 'Best restaurants in Busan' input to the search word input unit 802 The part including 'type information' may be output through the user terminal.

In the case of extracting and outputting snippets uniformly through keyword matching with a search query as in the prior art, the part containing the keywords simply 'Busan', 'restaurant', and 'list' in the body of the content (e.g., the body , etc.) is output as a snippet, whereas, according to the embodiments of the present disclosure, the part actually including the 'restaurant list' (ie, list-type information) is output as a snippet, so that the user has the intention to query the contents. A part corresponding to may be provided as a snippet.

9 is a diagram illustrating an example of providing search results reflecting the query intention of a search query according to another embodiment of the present disclosure. The processor may label the determined query pattern type based on at least one of text, text structure, attached file, and image included in the plurality of contents. In one embodiment, when the processor labels a query pattern type based on attachments included in a plurality of contents, the processor may include an extension name of the attached file, a title of the attached file, a creation date of the attached file, and content included in the attached file. etc. may be analyzed to determine a query pattern type, and the determined query pattern type may be labeled for content including a corresponding attached file. In another embodiment, when labeling a query pattern type based on images included in a plurality of contents, the processor determines the query pattern type by analyzing text information, image information, etc. included in the images, and Content may be labeled with the determined query pattern type.

The first content 'Let's play this U-love poem with a guitar (including guitar chord score, easy version)' 910 output on the screen 900 may include an attached file. In this case, the processor sets the query pattern type of the first content 910 to 'music score information' or 'score information' based on the extension '. It can be labeled as '0x1000', a query pattern type corresponding to 'multimedia information' and the like. On the other hand, the second content '[Melody] E-U-love poem sheet music' 920 output on the screen 900 may include an image. In this case, the processor analyzes the image of the second content 920 and recognizes text such as 'love poem', 'lyricist', and 'author', and image information such as 'note', 'musical sheet', and 'musical score image'. Based on , the query pattern type of the second content 920 may be labeled as '0x1000' corresponding to 'musical score information' or 'multimedia information'.

As shown, the processor may receive the search query 'music for when you love EU' input to the search word input unit 902 of the screen 900 of the user terminal. Thereafter, the processor may extract the keyword 'musical score' from the received 'musical score for two U love poems' and determine the query pattern type '0x1000' corresponding to the keyword 'musical score' as the query pattern type. Here, the processor calculates a ranking score for each of the plurality of contents based on the ranking factor 'musical score information' or 'multimedia information' corresponding to the query pattern type of the plurality of contents and the query pattern type '0x1000' of the search query, A ranking of each of a plurality of contents may be determined. That is, the processor may add a weight to the ranking scores of the first content 910 and the second content 920 labeled with '0x1000', and accordingly, the first content 910 and the second content 920 may be plural. It can be ranked at the top of the contents of and can be output preferentially.

10 is a diagram illustrating an example of providing different snippets according to the query intent of a search query according to an embodiment of the present disclosure. In an embodiment, the processor may extract at least one or more snippets from each of the plurality of contents by analyzing at least one of text, text structure, attached file, and image included in each of the plurality of contents. For example, the processor may extract one or more snippets associated with the query pattern type of each of the plurality of contents determined based on at least one of text, text structure, attached file, and image included in each of the plurality of contents. Here, one or more snippets associated with the query pattern type of each of the plurality of contents may be a part from which the corresponding query pattern type is labeled among the main body of each of the plurality of contents.

For example, the processor analyzes at least one of text, text structure, attached file, and image included in the contents 'A car release information (release date, price)' (1014, 1034), and provides information to the corresponding contents (1014, 1034). A query pattern type '0x10000' corresponding to 'time information' and a query pattern type '0x00010' corresponding to 'price information' may be labeled. In this case, the processor may extract a snippet associated with the query pattern type '0x10000' and a snippet associated with the query pattern type '0x00010' from the content, respectively. That is, in the body of the contents 1014 and 1034, the part '...the release date of A car is September 15, after the 2020 Motor Show (May 29)' including 'time information' is queried... The snippet (1016) associated with the pattern type '0x10000' is extracted, and the '... minimum price mid-40 million won to maximum 60 million won...' part containing 'price information' is converted to the query pattern type '0x00010' Each can be extracted as a snippet 1036 associated with.

The processor may output, through the user terminal, a snippet associated with one or more query pattern types (ie, a query pattern type of a search query) among one or more snippets. For example, when the processor receives the search query 'A release date' input to the search word input unit 1012 of the first screen 1010, the search query 'A release date' among snippets of the content 1014 The snippet 1016 associated with the pattern type '0x10000' can be output through the user terminal. On the other hand, when the processor receives the search query 'A-order price' input to the search word input unit 1032 of the second screen 1030, the query pattern type of the search query 'A-order price' among snippets of the content 1034 The snippet 1036 associated with '0x00010' can be output through the user terminal. Therefore, as shown in the first screen 1010 and the second screen 1030, the search result for the search query 'A-th release date' and the search query for 'A-th price' are the same content (1014, Even if 1034 is output, different snippets 1016 and 1036 may be output, respectively.

11 is a diagram illustrating an example of providing snippets 1110, 1120, and 1130 in which a region associated with a query intent of a search query is highlighted according to an embodiment of the present disclosure. The processor may emphasize and output a partial region related to one or more query pattern types in the snippet. That is, for the user's readability, a part of the snippet suitable for the user's query intention (eg, a region including target information that the user wants to be provided) may be highlighted and output to the user terminal. For example, the processor may emphasize and output a partial region associated with one or more query pattern types in the snippet through at least one of boldface processing and background processing.

As shown, the snippet 1110 of the first content includes '100,000 won' and 'price' fields associated with a query pattern type of the search query 'dermatology price' (ie, a query pattern type corresponding to the keyword 'price'). Through this bold text processing, it can be displayed on the screen 1100 with emphasis. In addition, the snippet 1120 of the second content is displayed on the screen 1100 after the area 'in the middle of 200,000 won when proceeding to the 4th round' associated with the query pattern type of the search query 'dermatology price' is highlighted through background processing. can In addition, in the snippet 1130 of the third content, the '33,000 won in A dermatology 1 year within 2 months' area associated with the query pattern type of the search query 'dermatology price' is background processed and the '33,000 won' area is boldfaced. It can be highlighted through and displayed on the screen 1100. Accordingly, the user may be provided with a readable snippet in which a region corresponding to the query intent is highlighted.

11 shows a boldface processing method or a background processing method as a snippet emphasis processing method, but is not limited thereto, and various emphasis processing methods may be used to improve user readability. For example, an emphasizing processing method of arranging and outputting text included in content in a list form may be used. In addition, although FIG. 11 illustrates an example of outputting a snippet in which the text of the content is emphasized, the snippet in which the text of the content is emphasized is shown, but the snippet in which the attached file, image, etc. included in the content is emphasized may be output.

The above-described search result providing method reflecting the intention of the query may be provided as a computer program stored in a computer readable recording medium to be executed by a computer. The medium may continuously store programs executable by a computer or temporarily store them 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.

The methods, acts or techniques of this disclosure may be implemented by various means. For example, these techniques may be implemented in hardware, firmware, software, or combinations thereof. Those skilled in the art will appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchange of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design requirements imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementations should not be interpreted as causing a departure from the scope of the present disclosure.

In a hardware implementation, the processing units used to perform the techniques may include one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs) ), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, and other electronic units designed to perform the functions described in this disclosure. , a computer, or a combination thereof.

Accordingly, the various illustrative logical blocks, modules, and circuits described in connection with this disclosure may be incorporated into a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or may be implemented or performed in any combination of those designed to perform the functions described in A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, eg, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other configuration.

In firmware and/or software implementation, the techniques include random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), PROM ( on a computer readable medium, such as programmable read-only memory (EPROM), erasable programmable read-only memory (EPROM), electrically erasable PROM (EEPROM), flash memory, compact disc (CD), magnetic or optical data storage device, or the like. It can also be implemented as stored instructions. Instructions may be executable by one or more processors and may cause the processor(s) to perform certain aspects of the functionality described in this disclosure.

Although the embodiments described above have been described as utilizing aspects of the presently-disclosed subject matter in one or more stand-alone computer systems, the disclosure is not limited thereto and may be implemented in conjunction with any computing environment, such as a network or distributed computing environment. . Further, aspects of the subject matter in this disclosure may be implemented in a plurality of processing chips or devices, and storage may be similarly affected across multiple devices. These devices may include PCs, network servers, and portable devices.

Although the present disclosure has been described in relation to some embodiments in this specification, various modifications and changes may be made without departing from the scope of the present disclosure that can be understood by those skilled in the art. Moreover, such modifications and variations are intended to fall within the scope of the claims appended hereto.

100: user
110: user terminal
120: screen

Claims (20)

A search result providing method reflecting the intention of a search query performed by at least one processor,
Receiving a search query from a user terminal;
determining one or more query pattern types for the search query based on one or more query intents extracted from the search query; and
Determining a ranking of each of a plurality of contents associated with the search query based on the one or more query pattern types.
including,
The one or more query pattern types are pre-matched with one or more ranking factors that are weighted factors in determining the ranking of the plurality of contents,
Determining a ranking of each of a plurality of contents related to the search query based on the one or more query pattern types,
Calculating a ranking score by assigning different weights to each of the plurality of contents associated with the search query according to the degree of correlation between each of the plurality of contents associated with the search query and the one or more ranking factors based on the one or more ranking factors ; and
Determining a ranking of each of the plurality of contents related to the search query based on the ranking score of each of the plurality of contents.
A method of providing search results reflecting the intent of a query, comprising: According to claim 1,
Determining one or more query pattern types for the search query based on one or more query intents extracted from the search query,
extracting one or more query intentions from the search query through one or more keywords included in the search query; and
A method of providing search results reflecting query intentions, comprising determining one or more query pattern types for the one or more query intentions. According to claim 1,
Determining one or more query pattern types for the search query based on one or more query intents extracted from the search query,
extracting one or more query intents from the search query through natural language processing; and
A method of providing search results reflecting query intentions, comprising determining one or more query pattern types for the one or more query intentions. A search result providing method reflecting the intention of a search query performed by at least one processor,
Receiving a search query from a user terminal;
determining one or more query pattern types for the search query based on one or more query intents extracted from the search query; and
Determining a ranking of each of a plurality of contents associated with the search query based on the one or more query pattern types.
including,
The one or more query pattern types are pre-matched with one or more ranking factors that are weighted factors in determining the ranking of the plurality of contents,
The one or more query pattern types include a query pattern type in which a plurality of query intents are merged;
The method of providing a search result reflecting the query intention, wherein the query pattern type in which the plurality of query intentions are merged is matched in advance with a plurality of ranking factors, which are factors that give weight in determining the ranking of the plurality of contents. delete According to claim 1,
The step of calculating the ranking score,
and determining a ranking of each of the plurality of contents for the search query based on the query pattern type of the plurality of contents and the one or more ranking factors. According to claim 6,
The method further comprising labeling the determined query pattern type based on at least one of text, text structure, attached file, and image included in the plurality of contents. According to claim 1,
The method of providing a search result reflecting a query intention, further comprising outputting at least one or more contents of a plurality of contents related to the search query based on the determined ranking through the user terminal. According to claim 1,
The method of providing a search result reflecting a query intent, further comprising extracting at least one or more snippets from each of the plurality of contents. According to claim 9,
Extracting at least one or more snippets from each of the plurality of contents,
A method of providing a search result reflecting a query intent, comprising extracting at least one or more snippets from each of the plurality of contents by analyzing at least one of text, text structure, attached file, and image included in each of the plurality of contents. . According to claim 10,
The step of extracting at least one or more snippets from each of the plurality of contents by analyzing at least one of text, text structure, attached file, and image included in each of the plurality of contents,
Extracting one or more snippets associated with a query pattern type of each of the plurality of contents determined based on at least one of text, text structure, attached file, and image included in each of the plurality of contents, How search results are presented. According to claim 1,
The method further comprising outputting a snippet of at least one or more contents among a plurality of contents related to the search query based on the determined ranking through the user terminal. According to claim 12,
Further comprising extracting one or more snippets associated with a query pattern type of each of the plurality of contents,
Outputting, through the user terminal, a snippet of at least one or more contents among a plurality of contents related to the search query based on the determined ranking,
and outputting a snippet associated with the one or more query pattern types among the one or more snippets through the user terminal. According to claim 13,
The step of outputting a snippet associated with the one or more query pattern types among the one or more snippets through the user terminal,
and outputting at least some of the one or more snippets through the user terminal according to preset priorities for the one or more query pattern types. According to claim 12,
Outputting, through the user terminal, a snippet of at least one or more contents among a plurality of contents related to the search query based on the determined ranking,
and emphasizing and outputting a part of the snippet associated with the one or more query pattern types. According to claim 15,
The step of emphasizing and outputting a partial area associated with the one or more query pattern types in the snippet,
and emphasizing and outputting a partial region associated with the one or more query pattern types in the snippet through at least one of boldface processing and background processing. A computer program stored in a computer-readable recording medium to execute a search result providing method reflecting the query intention according to any one of claims 1 to 4 and 6 to 16 in a computer. As a search result providing system reflecting the intention of a search query,
communication module;
Memory; and
at least one processor connected to the memory and configured to execute at least one computer readable program contained in the memory
including,
The at least one program receives a search query from a user terminal, determines one or more query pattern types for the search query based on one or more query intents extracted from the search query, and determines the one or more query pattern types. Includes instructions for determining a ranking of each of a plurality of contents associated with the search query based on the
The one or more query pattern types are pre-matched with one or more ranking factors that are weighted factors in determining the ranking of the plurality of contents.
Determining the ranking of each of the plurality of contents associated with the search query based on the one or more query pattern types,
Calculating a ranking score by assigning different weights to each of the plurality of contents associated with the search query according to the degree of correlation between each of the plurality of contents associated with the search query and the one or more ranking factors based on the one or more ranking factors;
and determining a ranking of each of the plurality of contents related to the search query based on the ranking score of each of the plurality of contents. According to claim 18,
Wherein the at least one program includes commands for labeling query pattern types of the plurality of contents. According to claim 18,
Wherein the at least one program includes instructions for extracting at least one or more snippets for each of the plurality of contents.

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