KR102142986B1 - Learning based search results visualization method and device - Google Patents

Abstract

The present invention relates to a method and apparatus for displaying a search result extracted by a search engine in response to a keyword input by a user. The user's search history is learned and the expression format preferred by the user in relation to the keyword input by the user By displaying components preferentially, the time required for the user to additionally check the detailed contents of the search result can be shortened.

Description

Method and device for displaying search results based on learning {LEARNING BASED SEARCH RESULTS VISUALIZATION METHOD AND DEVICE}

The present invention relates to a method and apparatus for displaying a search result found by a search engine in response to a keyword input by a user, and more specifically, a component included in the search result by learning the user's past keyword search history It relates to a method and apparatus for displaying them according to the priority of the expression format.

The Internet refers to a network that interconnects numerous computers by networking clients requesting services and servers providing services, and it is no exaggeration to say that modern people are living in a flood of information due to the development of the Internet.

Users use a computer connected to the Internet to search for data in various expression formats such as desired documents, images, videos, and sound sources from a server that provides Internet search services.

On the other hand, the server providing the Internet search service analyzes the contents of the web page by using a search robot (program) that collects various information by roaming the web page on the Internet by itself and classifies the information contained in the web page. It collects classified and analyzed information along with URLs, builds a database, and continuously updates it.

Therefore, when a user operates a web browser on his computer connected to the Internet and enters a keyword and executes a search, the server providing the Internet search service searches the database established through the search robot and matches the keyword entered by the user. The search results are displayed in the order of matching similarity by extracting the information.

Components included in the search results have various expression formats, such as text, images, news, video, audio, and source code, and users search again to find information of their desired expression format among search results matched with keywords. You must go through the process of additionally confirming the results.

Due to the process of additionally checking the search results, it may take a considerable amount of time to obtain the information the user wants. In many cases, the search results are insufficient, attempting a new keyword search, and an additional verification process for new search results. The time it takes for it becomes longer.

The present invention improves the shortcomings of the above-described conventional search result display method and reduces the time required for the search, allowing the user to learn the keywords and search process that the user searches, and through such learning, the search results in the expression format desired by the user It is an object of the present invention to provide a method and apparatus for displaying a search result that can preferentially display.

In order to solve the above problems, a method for displaying search results based on learning according to an embodiment of the present invention includes receiving a list of search results output by a search engine according to a keyword input by a user, and including in the search result list. And determining a priority for a representation format of the component, and prioritizing a component of a representation format having a higher priority.

According to another embodiment of the present invention, the step of determining the priority is characterized in determining the priority for the representation format of the component according to the number of past confirmations and reuse times of the components.

According to another embodiment of the present invention, a priority for a representation format of a component is determined according to a size of a value obtained by multiplying the number of reuse times by the weight and the number of confirmations.

According to another embodiment of the present invention, based on the user's search history for each component, the user's ID, the search keyword, the expression format of each component included in the search result, and the number of confirmations and reuse times for each component are learned. It characterized in that it further comprises the step of recording in the information table.

According to another embodiment of the present invention, when the user is a new user, the priority of the component expression format is determined according to a default value.

According to another embodiment of the present invention, the expression format is characterized by including at least two of a headline, a URL, an image, a video, and a source code.

A search result display device based on learning according to another embodiment of the present invention is a monitoring unit that monitors which component a user selects from a search result list output by a search engine according to a keyword input by the user, and monitors the monitoring unit. A learning unit that creates a learning information table based on the learning information table, an expression format determination unit that determines the priority of the expression format of components included in the search result list according to the learning information table, and a search according to the priority determined by the expression format determination unit And a display unit that displays components included in the result list.

According to another embodiment of the present invention, the learning information table includes a user ID, a keyword entered by the user, a component searched for a keyword search result, an expression format of each component, the number of confirmations of each component, the number of reuse of each component, etc. It features.

According to another embodiment of the present invention, the expression format determination unit is based on the number of confirmations of each component recorded in the learning information table and the number of reuse of each component, based on the component included in the search result related to the keyword inputted by the user. It is characterized in that it determines the priority of the expression format for Korea.

According to another embodiment of the present invention, the representation format determination unit is characterized in determining the priority for the representation format of the component according to a value obtained by multiplying the number of reuse times by the weight and the number of verifications.

According to another embodiment of the present invention, when the user is a new user, the expression format determination unit determines a priority for the expression format of a component according to a default value.

According to another embodiment of the present invention, the expression format is characterized by including at least two of a headline, a URL, an image, a video, and a source code.

According to various embodiments proposed by the present invention, the present invention allows the user to learn the search history such as the keyword searched for by the user and the search process performed by the user, thereby prioritizing the component of the expression format desired by the user from the search result provided by the search engine. By making it possible to reduce the time required for searching.

1 is a structural diagram illustrating an entire keyword search system including a search result display device according to an embodiment of the present invention.
2 shows a learning information table created according to an embodiment of the present invention.
3 is a flowchart of a method for displaying search results based on learning according to an embodiment of the present invention.
4 illustrates an example of displaying a search result based on a default value and displaying a search result according to an expression format priority based on learning, according to an embodiment of the present invention.

Advantages and features of the embodiments disclosed in the present specification, and a method of achieving them will become apparent with reference to the embodiments described later together with the accompanying drawings. However, the embodiments to be proposed in the present disclosure are not limited to the embodiments disclosed below, but may be implemented in a variety of different forms, and only these embodiments are examples to those of ordinary skill in the art. It is only provided to fully inform the categories of the subjects.

The terms used in the present specification will be briefly described, and the disclosed embodiments will be described in detail.

Terms used in the present specification have selected general terms that are currently widely used as possible while considering the functions of the disclosed embodiments, but this may vary according to the intention or precedent of a technician engaged in a related field, the emergence of new technologies, and the like. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the detailed description of the corresponding specification. Therefore, the terms used in the present disclosure should be defined based on the meaning of the term and the overall contents of the present specification, not a simple name of the term.

In this specification, expressions in the singular include plural expressions, unless the context clearly specifies that they are singular.

When a certain part of the specification "includes" a certain component, this means that other components may be further included instead of excluding other components unless otherwise specified. In addition, the term "part" as used in the specification means a hardware component such as software, FPGA, or ASIC, and "part" performs certain roles. However, "part" is not meant to be limited to software or hardware. The "unit" may be configured to be in an addressable storage medium or may be configured to reproduce one or more processors. Thus, as an example, "part" refers to components such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, Includes subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, database, data structures, tables, arrays and variables. The functionality provided within components and "parts" may be combined into a smaller number of components and "parts" or further separated into additional components and "parts".

Hereinafter, exemplary embodiments will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art may easily implement the present invention. In addition, in the drawings, parts not related to the description are omitted in order to clearly describe the present invention.

1 is a structural diagram showing a whole keyword search system including a search result display device according to the present invention.

According to FIG. 1, the entire keyword search system includes a user query generator 160, a search engine 170, a component database 180, and a search result display device 100 based on learning, and a search result display device based on learning. 100 is composed of a monitoring unit 110, a learning unit 120, an expression format determination unit 130, and a display unit 140.

Referring to FIG. 1, when a user inputs a keyword for search through a computer connected to the Internet, the user query generator 160 generates a query using the keyword input by the user, and the search engine ( 170).

The search engine 170 extracts a component matching a keyword from a component database in which information collected by the search robot is stored, and transmits it as a search result to the search result display device 100 based on learning.

Components stored in the component database are formed in various expression formats such as documents, images, videos, audio, and source files. In the conventional search result display apparatus, the component transmitted by the search engine 170 as a search result is displayed as it is, and the user goes through a process of additionally checking the displayed components to find the desired information from the displayed search result.

On the other hand, the search result display apparatus 100 based on learning according to an embodiment of the present invention learns the user's search history, instead of outputting the search result received from the search engine 170 as it is, and according to the learning result. By determining the priority of the expression format and displaying components of the expression format having a higher priority, it is possible to shorten the time required for the user to additionally check the search result.

The monitoring unit 110 included in the learning-based search result display device 100 monitors the user's search process. In other words, among the search results extracted by the search engine in response to the keyword entered by the user, what component the user has checked (viewed) and what component the user has reused (downloaded) is monitored.

On the other hand, the learning unit 120 creates a learning information table 125 by learning the user's search history as monitored by the monitoring unit 110.

2 is a block diagram showing a learning information table according to an embodiment of the present invention.

According to FIG. 2, the learning information table 125 includes a keyword used by a user for a search in the past for each user ID, a component extracted by a search engine corresponding to each keyword, a component ID for each component, an expression format, and a user checks the component ( It stores a counter that cumulatively records the number of times viewed) and the number of times the user reused (downloaded) components.

For example, a user has used the keyword "German Shepherd" (search keyword 2) in the past to search, and as a result, the search engine has documented information about the characteristics of the German Shepherd species (Component 1), Assume that search results such as image information (component 2) and video information about German Shepherd (component 3) are extracted.

For the search result extracted by the search engine, the user checks component 2, that is, image information three times, downloads (reuses) component 1, that is, document information on the characteristics of the species, and reads component 3, that is, video information once. If so, the learning unit 120 creates a learning information table 125 based on the user's search history.

On the other hand, the expression format determination unit 130 determines which components of the expression format to preferentially display among the search results corresponding to the search keyword 2 (German Shepherd) based on the counter recorded in the learning information table 125. . Specifically, the priority is determined according to the size of a value obtained by multiplying the number of reuses recorded in the counter by the weight and adding the number of checks.

In the case of the German Shepherd search described above, when a weight of 10 is applied, the counter value of component 1 is 20, the counter value of component 2 is 3, and the counter value of component 3 is 1.

Therefore, the expression format determination unit 130 displays the search results in the order of (20) the expression format of component 1, the document format, the expression format of component 2, the image format, and video format, the expression format of component 3. Determine the order of presentation.

The display unit 140 displays the search results according to the priority of the expression format determined by the expression format determination unit 130. That is, for a search using the keyword "German Shepherd", the search results are displayed by listing the components in the order of document, image, and video.

For reference, the weight of 10 for the number of reuses is based on statistics that users download (reuse) about once for 10 checks (views) in the process of checking the details of search results.

The expression format is not limited to a document, an image, a video, and the like, and may include at least two or more various expression formats such as a headline, a URL, an image, a video, and a source code.

The above has been described using a user with a search history as an example, but in the case of a new user who does not have a search history, since the learning information table 125 is in a blank state, the expression format determination unit 130 is the expression format according to the default value. Can determine the priority of For example, search results may be arranged and displayed in the order of expression types such as images, documents, and videos according to a predetermined default value.

If the expression format priority value is defined as VFV (Visualization Format Value), and each expression format is F _i , the set of F _i can be expressed as follows when the expression format is Headline, URL, Image, Souce_Code.

F _i = {Headline|URL|Image|Souce_Code}

In the above formula, F ₁ is Headline, F ₂ is URL, F ₃ is Image, and F ₄ is Source_Code. And the priority value for each expression format can be expressed as the following equation.

VFV(F _i ) = (RC _i * W) + (CC _i )

In the above equation, RC _i is the reuse count value for each representation format and CC _i is the confirmation count value for each representation format. In addition, W is a weight value, and a value of 10 is used in the above example, but it may be adjusted to a different value according to the statistical result.

If VFV(C ₁ ) is the _first to be displayed among the expression formats, the value can be expressed as the following equation.

VFV(C ₁ ) = Max[VFV(F _i )] (i=1, 2, 3, 4, ...)

And when j means the order in which the expression types such as Headline and URL are listed, in other words, the expression types are listed in the order of VFV(C ₁ ), VFV(C ₂ ), VFV(C ₃ ), VFV(C ₄ ). In this case, VFV(C _j ) can be expressed as the following equation.

VFV(C _j ) = Max[{VFV(F _i )}-VFV(C _j-1 )] (i=1, 2, 3, 4, ...) (j=2, 3, 4, .. .)

3 is a flowchart illustrating a method of displaying search results based on learning according to an embodiment of the present invention.

First, when a user inputs a keyword in step 300, it is determined in step 310 whether the user is a new user or a user having a search history. If it is determined that the user is a new user, in step 320, the priority of the expression format is determined according to the default value, and the search results are displayed according to the priority order of the determined expression format.

In step 330, it is determined whether to learn the user's search history, and if not, it ends. On the other hand, if it is determined to learn the user's search history, in step 331, the user ID and keyword are stored in the learning information table.

In step 332, it is monitored whether the user selects a component included in the search result, and if the component is not selected, it is determined that the desired component does not exist in the search result corresponding to the input keyword, and a new keyword is input. Go to 300.

If the user selects a component included in the search result, the component ID and expression format of the component selected in step 333 are stored in the learning information table.

In step 334, it monitors whether the user downloads (reuses) the selected component, and if it is reused, the number of reuse is increased by one in the counter field on the learning information table.

If the user has not downloaded the selected component, this is simply the user browsing the selected component, so the number of checks is increased by one in the counter field on the learning information table. Thereafter, the process moves to step 332 to monitor whether the user additionally selects a component, and repeats the above-described process according to the selection.

On the other hand, if the user has a search history in step 310, a request is made in step 340 to calculate a priority value for an expression format by referring to the learning information table.

After checking the user ID in step 341, and checking the keyword input by the user in step 342, the learning information table is searched in step 343 to extract learning information corresponding to the user ID and the keyword.

In step 344, the priority of the expression format is determined from the counter value among learning information corresponding to the user ID and the keyword. Since the method of determining the priority from the counter value including the number of checks and the number of reuse has been described above, a description of the specific method is omitted here.

In step 345, the search results are listed and displayed according to the priority of the determined expression format.

4 shows an example of displaying a search result according to an expression type priority based on a default value and a search result according to an expression type priority based on learning.

In the left display screen of FIG. 4, when the expression format priority according to the default value is in the order of headline, URL, image, and source code, the search result extracted by the search engine corresponding to the keyword entered by a new user is a component in the headline format. They are marked first.

Meanwhile, as a result of learning the user's search history according to the present invention, the right display screen of FIG. 4 learns that the user wants a component in the source code format for a predetermined keyword, and accordingly, the components in the source code format are first listed. It is indicated by.

A search result display device based on learning according to another embodiment of the present invention includes at least one processor, and the at least one processor receives a list of search results output by a search engine according to a keyword input by a user, and a list of search results It determines the priority for the representation format of the components included in the component, and controls the display to display the components of the representation format with a higher priority.

Another embodiment of the present invention may be implemented as a program for causing a computer to perform the number recognition method according to the present invention and may be provided as a recording medium storing the program in a readable nonvolatile memory.

Search result display device based on 100 learning
110 monitoring unit
120 learning units
130 Expression format determination unit
140 display unit
160 User Query Generator
170 Search Engine
180 component database

Claims (22)

In a search result display method in a search result display device including a learning unit, an expression format determination unit, and a display unit,
The learning unit receives a list of search results output by a search engine according to a keyword input by a user;
The expression format determining unit determining a priority for the expression format of the components included in the search result list; And
The display unit includes the step of preferentially displaying components of a representation format having a high priority,
In the step of determining the priority, the expression type determination unit determines the priority of the expression type of the component according to the number of past confirmations and reuse of the components by the user. Display method. delete The method of claim 1,
The method of displaying a search result based on learning, wherein the expression format determination unit determines a priority for a representation format of a component according to a size of a value obtained by multiplying the number of reuse times by a weight and the number of confirmations. The method of claim 1 or 3,
The learning unit records the user's ID, the search keyword, the expression format of each component included in the search result, and the number of confirmations and reuse times for each component in the learning information table based on the user's search history for each component. Learning-based search results display method, characterized in that it further comprises a step. The method of claim 1,
The expression format determination unit, when the user is a new user, determines a priority for the expression format of a component according to a default value. The method of claim 1,
The expression format includes at least two of a headline, a URL, an image, a video, and a source code. A monitoring unit that monitors which component the user selects from the search result list output by the search engine according to the keyword input by the user;
A learning unit for creating a learning information table based on the monitoring of the monitoring unit;
A representation format determination unit that determines a priority for representation formats of components included in a search result list according to the learning information table; And
And a display unit for displaying components included in the search result list according to the priority determined by the expression format determination unit,
The learning information table displays a search result based on learning, characterized in that it includes a user ID, a keyword input by the user, a component searched as a result of a keyword search, an expression format of each component, the number of confirmations of each component, and the number of reuse of each component. Device. delete The method of claim 7,
The expression format determination unit determines the priority of the expression format for the component included in the search result related to the keyword input by the user, based on the number of confirmations of each component recorded in the learning information table and the number of reuse of each component. Learning-based search result display device, characterized in that to determine. The method of claim 9,
The expression format determination unit determines a priority for a representation format of a component according to a size of a value obtained by multiplying the number of reuse times by a weight and the number of confirmations. The method of claim 7,
The expression format determination unit, when the user is a new user, determines a priority for the expression format of a component according to a default value. The method of claim 7,
The expression format includes at least two of a headline, a URL, an image, a video, and a source code. In the learning-based search result display device comprising at least one processor, the at least one processor
Receive a list of search results output by the search engine according to the keyword entered by the user,
Determine the priority for the expression format of the components included in the search result list,
Controls to preferentially display components of high-priority expression formats on the display,
The one or more processors determine a priority for a representation format of a component according to a number of past confirmations and reuse times of the components by the user. delete The method of claim 13,
The at least one processor determines a priority for a representation format of a component according to a value obtained by multiplying the number of reuse times by a weight and the number of checks. The method of claim 13 or 15,
The at least one processor records the user's ID, the search keyword, the expression format of each component included in the search result, and the number of confirmations and reuse times for each component in the learning information table based on the user's search history for each component. Learning-based search result display device, characterized in that. The method of claim 13,
The at least one processor, when the user is a new user, determines a priority for an expression format of a component according to a default value. The method of claim 13,
The expression format includes at least two of a headline, a URL, an image, a video, and a source code. A computer-readable nonvolatile recording medium recording a program for executing a learning-based search result display method on a computer, the program comprising:
Receiving a list of search results output by a search engine according to a keyword input by a user;
Determining a priority for a representation format of a component included in the search result list; And
Steps to prioritize the components of the presentation format with high priority are executed,
The step of determining the priority comprises determining a priority for a representation format of a component according to a number of past confirmations and reuse times of the components by the user. delete The method of claim 19,
And determining a priority for a representation format of a component according to a value obtained by multiplying the number of reuse times by a weight and the number of checks. The method of claim 19 or 21, wherein the program is
Based on the user's search history for each component, an additional step of recording the user's ID, the search keyword, the expression format of each component included in the search result, and the number of confirmations and reuse times for each component in the learning information table. Computer-readable nonvolatile recording medium, characterized in that to execute.

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