KR100931693B1 - How to search for keywords - Google Patents

Abstract

The present invention relates to a keyword search method for quickly and accurately searching a keyword that satisfies a user's search intention by using the collective intelligence of a search service user on the Internet, and includes a keyword to be searched when the user searches for the keyword. Search for each web document and keyword included, apply a weight to the score of each web document including the recommended keyword, and adjust the ranking list of each web document including the keyword to be searched. By generating summary information of each web document including a keyword to be searched for and providing to the user, a web document highly correlated with the keywords desired by the user can be displayed more quickly and accurately.

Keyword search, search intent, search engine, collective intelligence, index

Description

How to search for keywords {KEYWORD SEARCHING METHOD}

The present invention relates to a keyword retrieval method, and more particularly, to a keyword retrieval method for quickly and accurately retrieving a keyword satisfying a user's search intention by using collective intelligence of a search service user on the Internet.

In general, in order for a user to obtain desired information on the Internet (for example, a web site, a web document, etc.), the user accesses a search site that provides a search service through his terminal, and then provides the search site. By entering a search keyword in a search box and executing a search, a search engine of a corresponding search site searches a web site or a web document including the search keyword and provides the search result as a summary information.

In this case, if the user wants to obtain the desired information by the search keyword input in the search box provided by the search site, the search keyword that satisfies the user's search intention should be entered in the search box. By inputting an incorrect search keyword due to the neutrality and stemming error of a word, a mistake of a document author, and the like, there is a problem that the input search keyword does not sufficiently reflect the search intention of the user.

Looking at the problem caused by the first neutrality in more detail as follows.

When a user searches on the search engine with the keyword 'next', even though the actual user enters the keyword 'next' with the intention of obtaining information related to 'next communication', the existing search engine simply inputs the user. Because search results are provided only by whether or not they contain one search keyword, documents containing the keyword "next" as opposed to "previous" are mainly provided as search results, and the meaning of "corporate and internet services" 'Next' may only provide some.

In other words, other search terms that users who normally search for 'next' enter with the intention of obtaining information related to 'next communication' may include companies or 'next search', 'next media', 'next cafe', etc. Despite being 'next' as an internet service, the word 'next' may appear more in the Korean document as opposed to 'previous' when searched with the keyword 'next' in a search engine.

In another example, if a search engine performed a search with the keyword "LA", the actual user entered the keyword "LA" for the purpose of obtaining information about "US cities", The documents containing the back are mainly searched, and thus the accuracy is low.

Looking at the problem caused by the second stemming and documentation errors, for example, as follows.

If a search engine performed a search with the keyword 'Edo', the actual search engine stemmer would search for 'Edo' even though the user entered the keyword 'Edo' with the intention of obtaining information related to 'Japan'. It is possible to determine probabilisticly whether the word is used as a noun or an investigation, but because of the many errors in the writing of a web document, such as in a sentence such as 'I wasn't frustrated with polarization,' 'Edo' as an investigation More often, documents containing keywords are provided as search results, and only a few 'Edo' as a noun can prevent the stemmer from producing accurate search results.

In other words, other search terms entered by users searching for 'Edo' with the intention of obtaining information related to 'Japan' are 'Edo' as a noun, such as 'Edogawa Ranpo' and 'Edo'. Nevertheless, when the keyword "Edo" is searched in a search engine, the word "Edo" is more often used as a search in Korean documents, so it is difficult to find "Japan" related documents in the keyword search results. .

In another example, if a search engine performed a search with the keyword 'gaya', the actual user entered the keyword 'gaya' with the intention of obtaining information related to 'historic' or 'gaya cc'. It is often the case that documents containing 'gaya' as a verb are mainly searched for documents such as 'way to go' and 'how long should coma go'.

As described above, the conventional keyword search has a problem that the user's search intention is not sufficiently satisfied due to the neutrality of the Hangul word, the morphological analysis, and the error of document writing.

SUMMARY OF THE INVENTION The present invention has been made in an effort to solve the problems described above, and provides a keyword search method for quickly and accurately searching a keyword that satisfies a user's search intention by using collective intelligence of a search service user on the Internet. To provide.

In addition, the present invention allows the search engine to perform keyword search that satisfactorily satisfies the user's search intention by using the collective intelligence of the user, thereby searching only the web documents having a very high correlation with the keywords desired by the user. The purpose is to improve or improve the accuracy of the search.

In order to solve this problem, according to the present invention, when searching for a specific keyword in the search engine to analyze the user pattern (ie, the collective intelligence of the user) for the search words entered by the user to use the user's search intention It extracts related keywords that can be well reflected and organizes them into a database of suggested keywords for each search word. It analyzes the web documents to be searched in advance and then applies them to the web documents containing the suggested keywords among the web documents including the search terms. After creating an inverted index structure (i.e., data) for a keyword, it searches for suggested keywords for the search term in actual keyword search and uses only the inverted index structure to expose only relevant web documents to correlate with the keywords that the user really wants. Allows you to quickly and accurately display highly relevant web documents.

According to an aspect of the present invention, in a method for a search engine searching for a keyword input by a user, when a keyword input by the user is received, a search engine searches for a web document including the keyword, and searches for the keyword in the web document. Confirming whether or not the recommendation keyword corresponding to is included using identification information indicating whether the recommendation keyword is included in each web document including the keyword, and the web including the recommendation keyword. Adding score weights to documents, performing scoring according to whether the weights are added, matching information between the web document and the keyword or page ranking, and generating a list of a predetermined number of web documents in order of high scores; And generate summary information of the web documents included in the list to the user. It provides a keyword search method comprising the steps of.

In the keyword search method, using the collective intelligence of the user, setting the recommended keywords corresponding to the keyword to be searched and databased, and setting information on the ID of each web document including the keyword to be searched. Setting identification information indicating whether the recommendation keyword is included in each web document including the keyword to be searched, and databaseting information on the ID and identification information of each set web document. And setting information on a body of a web document corresponding to the web document ID to make a database. Here, the identification information is a flag bit for giving a score weight to a web document including the recommendation keyword among the web documents including the keyword to be searched.

The keyword searching method includes information on recommended keywords corresponding to the keyword to be searched, each web document ID and identification information including the keyword to be searched, and information about a web document body corresponding to the web document ID. It may further comprise the step of resetting periodically.

On the other hand, the step of checking whether the recommendation keyword is included, the step of retrieving the ID of each web document containing the keyword entered by the user from the database, and each web containing the keyword entered by the user Reading identification information for a document ID from the database.

The generating of the list of the predetermined number of web documents may include whether the recommendation keyword corresponding to the keyword input by the user is included in each web document including the keyword input by the user from the identification information. Checking, if the recommendation keyword is included in each web document including the keyword input by the user, adding a score weight to each web document including the recommendation keyword; Scoring each web document including whether the weight is added according to whether the weight is added, the degree of matching with the keyword input by the user, or the page ranking, and a predetermined number of web document IDs are generated in the order of the high scores. It includes a step.

Alternatively, the generating of the list of the predetermined number of web documents may include: scoring each web document including a keyword input by the user according to the degree of matching with the keyword input by the user or page ranking. Checking, from the identification information, whether or not the recommended keyword corresponding to the keyword entered by the user is included in each web document including the keyword entered by the user; and each web including the keyword entered by the user. If the recommendation keyword is included in the document, applying a weight to a score of each web document including the recommendation keyword to readjust the score of each web document including the keyword input by the user, and Generating a predetermined number of web document IDs in the order of high score. It is.

According to another aspect of the present invention, in the method for searching a keyword input by the user, using the group intelligence of the user to set the recommended keywords corresponding to the keyword to be searched by the database, the keyword to be searched by the user Setting information about an ID of each web document including a; setting identification information indicating whether the recommendation keyword is included in each web document including a keyword to be searched by a user; Database information and identification information of each web document ID, database information by setting information on the body of the web document corresponding to the web document ID, the user input when the user searches for keywords Recall each web document ID and identification information containing one keyword. Searching from the database; checking from the identification information whether a recommended keyword corresponding to the keyword entered by the user is included in each web document including the keyword entered by the user; and checking the keyword entered by the user. When the recommendation keyword is included in each web document including, adding a score weight to each web document including the recommendation keyword, whether the weight is added to each web document including the keyword input by the user. Scoring according to a matching degree or page ranking with a keyword input by a user, generating a predetermined number of web document IDs in a list in order of high score, and according to the generated web document ID list. A summary of each web document containing the keywords entered by the user. Castle to include the step of providing to the user.

As described above, according to the present invention, after a database of suggested words reflecting the user's search intention for the user's search word and a reverse index structure for the web document including the suggestion word among the web documents including the search word, a specific keyword is selected. When searching, the database and inverse index structure are used to give a weighted weight to the web document containing the suggested word among the web documents containing the keyword, so that the web document ranking list is highly correlated with the desired keywords. By adjusting the order and providing it to the user, the user can quickly and accurately display web documents that are highly correlated with the keywords he or she really wants.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like parts throughout the specification.

Throughout the specification, when a part is said to "include" a certain component, it means that it can further include other components, without excluding other components unless specifically stated otherwise. In addition, the terms “… unit”, “… unit”, “… module” described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware or software or a combination of hardware and software. Can be.

Now, a keyword search method according to an embodiment of the present invention will be described in detail with reference to the drawings.

1 is a schematic conceptual diagram of a system for keyword search according to an embodiment of the present invention.

As shown in FIG. 1, a system for keyword search according to an embodiment of the present invention includes a user terminal 110, a wired / wireless communication network 120, a search engine 130, and a database 140.

When the user inputs a search word for searching for a specific keyword, the user terminal 110 transmits the input search word to the search engine 130 through the wired / wireless communication network 120, and the search received from the search engine 130. Provide the results to the user.

The wired / wireless communication network 120 connects the user terminal 110 and the search engine 130 to each other to perform communication.

The search engine 130 searches the web documents including the search term received from the user terminal 110, and identifies whether the searched web documents include the recommended keyword corresponding to the search term received from the user terminal 110. After scoring the weights of the web documents including the recommended keyword, the web documents including the search terms are scored, and a list of IDs (IDs) of the web documents according to the scoring is generated. According to the list, summary information on the corresponding search result (ie, a web document including a search word) is generated and transmitted as a search result to the user terminal 110 through the wired / wireless communication network 120.

The search engine 130 includes a query broker 131, a searcher 132, and a summary 133.

The query broker 131 receives a search word input by the user from the user terminal 110 through the wired / wireless communication network 120 and applies the received search word to the searcher 132. The query broker 131 authorizes the summary 133 with information about the list of web document IDs authorized from the searcher 132. The query broker 131 transmits summary information of each web document authorized from the summary 133 to the user terminal 110 through the wired / wireless communication network 120 as a search result.

The searcher 132 searches the database 140 for a web document including a search word authorized from the query broker 131, checks in the database 140 whether the keyword is included in the searched web document. After weighting the score of the searched web document according to the check result, scoring the searched web document is performed, and generating a list of IDs of the web document according to the scoring to generate the ID list of the generated web document. Information about the query broker 131.

The summary 133 receives information about the list of web document IDs from the query broker 131 and reads the body content of the web document corresponding to each web document ID of the authorized web document ID list from the database 140. In response to the list of authorized web document IDs, summary information of each web document is generated and authorized to the query broker 131.

The database 140 includes a web including information on recommended keywords for reflecting the user's search intention corresponding to each search word of the user, information about an ID of a web document corresponding to each search word of the user, and a recommendation keyword corresponding to each search word of the users. Identification information on the document ID and information on the web document body corresponding to each web document ID are stored in a database. At this time, it should be understood that the database 140 may be configured as a separate memory according to its function or role.

Hereinafter, a keyword search method according to an embodiment of the present invention will be described in detail with reference to the flowchart of FIG. 2.

First of all, there is something to prepare before the user can search for a specific keyword. In order to obtain a search result that satisfies the user's search intentions more quickly and accurately, it database the suggested words corresponding to the keywords that the user can enter, and correspond to the keywords that the user can enter when indexing. An index structure by reading a suggestion, searching for a document containing a keyword that the user can enter, and adding identifying information to indicate a weighted score for the ID of the web document containing the suggestion among the found web documents. To form.

First, when a user enters a search term, a related search term set for more accurately grasping the search intention of the user is generated and stored in the database 140.

In other words, for a keyword that a user can enter for a search (hereinafter referred to as a query), the user's collective intelligence can be used to better reflect the user's search intent (ie, recommend a keyword). Keyword), and sets information on a recommendation keyword for reflecting a user's search intention corresponding to each query, and stores the set information in a database 140 (or a memory provided separately) (S201). .

Second, all the web documents that are to be searched for the query that the user can input for the search are analyzed in advance, and the analyzed data values are stored in the database 140 so that they can be used for later indexing.

In other words, by stemming on a query that a user can enter for a search, you can index a web document that contains the query, and include a keyword that matches the query among the indexed web documents. Allows you to identify whether it is a web document.

At this time, a keyword is extracted from all web documents to be searched, and information about a web document ID corresponding to each keyword is set so that the ID of each web document can be found when the keyword is given (S202). .

Then, it checks whether there is a suggestion keyword corresponding to the dissolution query in the web documents including the query that the user can enter for the search, and if the keyword is given, the keyword in each web document corresponding to the keyword. Identification information indicating whether a keyword included in the web document corresponding to each keyword is included to identify whether the keyword corresponding to the keyword is included and to give a score weight to the web document including the keyword. A flag bit is set (S203).

For example, when the recommendation keyword corresponding to the query input by the user is included in the web document including the query input by the user, the flag bit is set to '1'. On the other hand, if the recommendation keyword corresponding to the query input by the user is not included in the web document including the query input by the user, the flag bit is set to '0'.

Accordingly, after the database of the identification information for the web document ID including the information on the web document ID corresponding to each keyword set in step S202 and the recommended keyword corresponding to each keyword set in step S203, the database ( 140 (or a separate memory) (S204). In this case, the structure of the database 140 for the web document ID information corresponding to each keyword and the identification information for the web document ID including the recommendation keyword corresponding to each keyword is referred to as an inverted index structure.

Third, if the web document ID is given, information about the web document body corresponding to each web document ID is set and databased so that the body of each web document can be found, and then the database 140 (or, The memory is stored separately (S205).

Subsequently, the web document including information on the suggestion keyword for reflecting the user's search intention corresponding to each query of users, information on the ID of the web document corresponding to each query of users, and the recommendation keyword corresponding to each query of users When the identification information on the ID and the information on the web document body corresponding to each web document ID are deleted, changed, or modified, the deleted, changed or modified information is upgraded in the database 140. Alternatively, periodically repeating the above-described steps S201 to S205, the information on the recommended keyword for reflecting the user search intention corresponding to each query of the user, the information on the ID of the web document corresponding to each query of the user, the user After resetting the identification information of the web document ID including the recommended keyword corresponding to each query of the user, the information on the web document body corresponding to each web document ID, by upgrading the reset information in the database 140 In addition, it can maintain a state that can better reflect the user's search intent.

By constructing the database 140 as described above, there is an advantage that a web document suitable for a user's search intention can be searched more quickly and accurately with respect to a query composed of one term.

Then, in order to actually perform a search for a specific keyword, the user accesses the search site through the wired / wireless communication network 120 using the user terminal 110, and then inputs the specific keyword in the search window provided by the search site. You enter a query to search and select the search command.

Accordingly, the user terminal 110 generates a search command message including a query input by the user according to the search command of the user and transmits the search command message to the search site through the wired / wireless communication network 120.

Accordingly, the search engine 130 of the search site receives a search command message transmitted from the user terminal 110 through the wired / wireless communication network 120. In this case, the query broker 131 provided in the search engine 130 receives a query input by the user through the wired / wireless communication network 120 from the user terminal 110 (S206) and retrieves information on the received query. The searcher 132 provided at 130 is applied.

Then, the searcher 132 receives information about the query input by the user from the query broker 131 and performs indexing using the inverted index structure set in step S204. At this time, the searcher 132 searches the web documents including the query input by the user, identifies whether the keyword is included in the searched web documents, and scores the web documents including the suggested keyword. After the weight is given, the searched web documents are scored, and a list of IDs of each web document according to the score is generated to apply the information to the query broker 131.

In more detail, the searcher 132 receives the query input by the user from the query broker 131 and receives the ID (ie, the web corresponding to the query input by the user) of each web document including the query input by the user. The document ID) is read (that is, retrieved) from the inverted index structure of the database 140 (S207).

Accordingly, the searcher 132 reads from the inverted index structure (ie, identification information) of the database 140 whether or not it includes a recommended keyword for each web document including the query input by the user (S208). . That is, the searcher 132 reads identification information set in the database 140 (that is, identification information of an ID of a web document including a recommendation keyword corresponding to each query of users) and inputs a query input by the user. It is identified whether the recommended keyword corresponding to is included in the web document including the query input by the user (S209). For example, the searcher 132 checks whether a flag bit preset in the database 140 is set to '1'.

In the above-described step S209, if the keyword corresponding to the query input by the user is included in the web document including the query input by the user, the searcher 132 includes the keyword recommended corresponding to the query input by the user. For each ID of the web document, a score weight is further added (S210).

Accordingly, the searcher 132 scores each web document ID including the query input by the user through a degree of matching with the query input by the user, page ranking, weight application, and the like. Alternatively, the searcher 132 ranks each web document ID read in step S208 described above (S211).

Alternatively, the searcher 132 scores or ranks each web document ID read in step S208 described above through a degree of matching with a user input query, page ranking, and the like. At this time, the searcher 132 checks the identification information of the web document ID including the recommendation keyword corresponding to the query input by the user from the database 140, and the user inputs the recommendation keyword corresponding to the query input by the user. Identifies whether it is contained within the web document that contains the query.

Accordingly, when the suggestion keyword corresponding to the query input by the user is included in the web document including the query input by the user, the searcher 132 may include the web document including the suggestion keyword corresponding to the query input by the user. The scores are further given to the IDs to re-adjust or rerank the scores assigned to the respective web document IDs read in step S208.

Then, the searcher 132 selects a predetermined number (for example, 20,000) of web document IDs in order of high score and generates the list. Alternatively, the searcher 132 selects a predetermined number of web document IDs of a higher rank (for example, 20,000) to generate a list (S212), and then queries the query broker 131 for information on the list of the corresponding web document IDs. ) Is authorized.

Then, the query broker 131 receives information about the list of web document IDs from the searcher 132 and applies the summary information to the summary 133 provided in the search engine 130.

Accordingly, the summary 133 receives the information on the list of web document IDs from the query broker 131 and generates summary information on the search result of the searcher 132 (that is, each searched web document) to generate the query broker 131. Is applied.

In other words, the summary 133 receives a web document ID list from the query broker 131 and uses a web document ID of the authorized web document ID list to correspond to each web document ID from the database 140. After reading (ie, retrieving) information about the body of the document (S213), a summary information of each web document including the query entered by the user is generated according to the authorized web document ID list (S214). Then, the summary information of each generated web document is authorized to the query broker 131.

Then, the query broker 131 receives the summary information of each web document from the summary 133 and transmits it to the user terminal 110 through the wired / wireless communication network 120 as a search result (S215). Accordingly, the user terminal 110 may provide a user with a search result received from the search engine 130, thereby quickly and accurately displaying web documents highly correlated with keywords that the user really wants.

In the above-described embodiment of the present invention, a search engine may use a user's collective intelligence to search a user's input search word for a database that suggests a user's search intention and input the user's input when indexing. Stemming the search terms that can be used to index documents that contain the keyword and form an inverted index structure that indexes documents containing the suggested words among the indexed documents. After reading the words, searching the document IDs containing the search terms in the index, searching the document IDs containing the suggested words among the searched document IDs, and giving score weights to the searched document IDs. When generating scoring and ID list, and generating summary information about search results By describing and providing summary information according to the ID list, the keyword retrieval method is described so that a user can quickly and accurately display a web document highly correlated with the desired keywords.

However, embodiments of the present invention are not implemented only through the above-described apparatus and / or method, but implemented through a program for realizing a function corresponding to the configuration of the embodiment of the present invention, a recording medium on which the program is recorded, and the like. Such an implementation may be easily implemented by those skilled in the art to which the present disclosure pertains based on the description of the above-described embodiments.

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements of those skilled in the art using the basic concepts of the present invention defined in the following claims are also provided. It belongs to the scope of rights.

1 is a schematic block diagram illustrating a system for keyword search according to an embodiment of the present invention.

2 is a flowchart illustrating a keyword search method according to an exemplary embodiment of the present invention.

Claims (8)

In a way for a search engine to search for a keyword entered by a user, When receiving a keyword input by the user, the web document including the keyword is searched, and whether the recommendation keyword corresponding to the keyword is included in the web document, Confirming using identification information indicating whether the recommended keyword is included in each web document including the keyword, Score weights are added to the web document including the recommendation keyword, scores are added according to whether the weight is added, matching information between the web document and the keyword, or page ranking, and a predetermined number of points are ordered in the order of high scores. Generating a list of web documents, and Generating summary information of a web document included in the list and providing the summary information to a user; Keyword search method comprising a. The method of claim 1, Setting a database of recommended keywords corresponding to the keyword to be searched by using the collective intelligence of the user and making a database; Setting information about an ID of each web document including the keyword to be searched; Setting identification information indicating whether the recommended keyword is included in each web document including the keyword to be searched, Databaseting the information on the ID and identification information of each of the set web documents; and Setting information about a body of a web document corresponding to the web document ID and making a database; Keyword search method further comprising. The method of claim 2, The identification information, And a flag bit for giving a score weight to a web document including the recommendation keyword among the web documents including the keyword to be searched. The method of claim 2, Periodically resetting the information on the recommended keywords corresponding to the keyword to be searched, each web document ID and identification information including the keyword to be searched, and the information on the web document body corresponding to the web document ID. Keyword search method that includes more. The method of claim 2, The step of checking whether the suggested keyword is included, Retrieving the ID of each web document containing the keyword entered by the user from the database, and Reading identification information for each web document ID including a keyword entered by the user from the database Keyword search method comprising a. The method of claim 5, Generating the list of the predetermined number of web documents, Checking, from the identification information, whether or not the recommended keyword corresponding to the keyword entered by the user is included in each web document including the keyword entered by the user; If the suggested keyword is included in each web document including a keyword input by a user, adding a score weight to each web document including the recommended keyword, Scoring each web document including a keyword input by the user according to whether the weight is added, matching degree with the keyword input by the user, or page ranking; and Generating a predetermined number of web document IDs in a list in order of increasing score; Keyword search method comprising a. The method of claim 5, Generating the list of the predetermined number of web documents, Scoring each web document including a keyword input by the user according to the degree of matching with the keyword input by the user or page ranking; Checking, from the identification information, whether or not the recommended keyword corresponding to the keyword entered by the user is included in each web document including the keyword entered by the user; When the suggestion keyword is included in each web document including the keyword input by the user, each web document including the keyword input by the user is applied by applying a weight to the score of each web document including the recommendation keyword. To rescale the score, and Generating a predetermined number of web document IDs in a list in order of increasing the readjusted scores; Keyword search method comprising a. In a method for searching a keyword entered by a user, Using the group intelligence of the user to set and database the recommended keywords corresponding to the keyword to be searched by the user, Setting information about the ID of each web document that contains a keyword to be searched by the user, Setting identification information indicating whether the recommended keyword is included in each web document including a keyword to be searched by a user, Databaseting the information on the ID and identification information of each of the set web documents; Setting information about a body of a web document corresponding to the web document ID and making a database; Retrieving each web document ID and identification information including the keyword entered by the user from the database when the user searches for the keyword, Checking, from the identification information, whether or not the recommended keyword corresponding to the keyword entered by the user is included in each web document including the keyword entered by the user; If the recommendation keyword is included in each web document including a keyword input by a user, adding a score weight to each web document including the recommendation keyword; Scoring each web document including a keyword input by the user according to whether the weight is added, matching degree with the keyword input by the user, or page ranking; Generating a predetermined number of web document IDs in a list in order of increasing score; and Generating summary information of each web document including a keyword input by the user according to the generated web document ID list and providing the summary information to the user; Keyword search method comprising a.

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