KR20200125412A - Method and apparatus for personalizng travel tribute language - Google Patents

Abstract

The present invention relates to a method for personalizing a travel attribute language and a device thereof. According to the present invention, the method for personalizing a travel attribute language comprises the steps of: generating a median attribute set including median attribute keywords; adding or deleting a median attribute keyword to or from the median attribute set; calculating a first higher attribute keyword-object correlation level; providing an object to an interface; receiving a second higher attribute-median attribute correlation level; and correcting a first higher attribute-median attribute correlation level. According to the present invention, a personalized travel attribute language can be generated.

Description

Method and device for personalizing travel attribute language {METHOD AND APPARATUS FOR PERSONALIZNG TRAVEL TRIBUTE LANGUAGE}

At least some embodiments of the present specification relate to a method and apparatus for personalizing a travel attribute language.

According to a conventional search method, a user can search and find a desired web document by entering a search keyword in a search window. For example, the user may search for information on the travel destination “Rome” by entering the travel destination “Rome” in the search box. However, if the user cannot remember the travel destination he is looking for, another method of providing information is required. For example, the user may attempt to search by entering a movie title related to a travel destination he/she is looking for, an actor who appeared in the movie, or a director or producer of the movie as a keyword. Travel information sites and travel review sites may provide information on movies about the destination along with travel information, so if you're not lucky, users can search for the destination they want by using the movie title, actor, director, or producer as keywords. Maybe.

However, furthermore, if information is provided based on informal language, for example, emotional language, rather than formal information, the conventional search method cannot be used. For example, the response provided by conventional search engines to search terms such as "romantic destinations" or "fantastic destinations" is to search for documents written by someone including the keywords "romantic destinations" or "fantastic destinations". It will only be. However, the informal language needs a different approach from formal information such as summer travel destinations and winter travel destinations. Even if someone doesn't include the keywords "romantic destinations" or "fantastic destinations", there may actually be destinations that many people find "romantic" or "fantastic".

Furthermore, by using attribute keywords based on the emotional language input from the user, that is, the keywords "romantic travel destination" or "fantastic travel destination", the user's own "romantic travel destination" or "fantastic travel destination" It is possible to create a personalized movie attribute language for "in travel" or "fantastic travel".

Further, for other fields other than travel destinations, a different approach may be required to request for information provision using an unstructured language.

1. Korean Patent Registration No. 10-0943962 "A method of providing an item search service based on emotion, a database construction method, and a search server" (Announcement date: 2010. 02. 26.)

An object of the present specification is to provide a method and apparatus for personalizing travel attribute language.

A travel attribute language personalization method according to an embodiment of the present specification includes a terminal and an information providing device that is connected to the terminal through a communication network and provides a plurality of upper attribute keywords and intermediate attribute keywords to the terminal. A method for personalizing a travel attribute language by a device, wherein when the information providing device selects a specific high-level attribute keyword from among the plurality of high-level attribute keywords through the terminal, the high-level attribute keyword selected by the information providing device 　-　 median attribute keyword Generating a median attribute set including a median attribute keyword having a 　1 　 high-order attribute-median attribute association degree equal to or greater than a reference value, based on the 　1 　 high-order attribute-median attribute association degree corresponding to the pair; Providing an interface for adding or deleting an intermediate attribute keyword to the intermediate attribute set together with the upper attribute keyword by the information providing device, and adding or deleting an intermediate attribute keyword to the intermediate attribute set according to a user input; Calculating, by the information providing device, a 　1　 high-order attribute keyword-object association degree corresponding to the upper attribute keyword and an object pair selected based on the 　1　 middle attribute keyword-object association degree; Providing, by the information providing device, an object corresponding to the 　1　 high-level attribute keyword-object correlation to the interface; An interface including the median attribute set is provided to the terminal by the information providing device, and receiving a second 　2　 high-level attribute-median attribute association degree for each of the median attribute keywords selected in the interface through the terminal; Correcting the 　1　 high-level attribute-median attribute association degree by reflecting the 　2　 high-level attribute-median attribute association degree by the information providing device; Displaying, by the information providing device, an intermediate attribute keyword of the intermediate attribute set to be distinguished from other intermediate attribute keywords; And displaying, by the information providing device, median attribute keywords other than the median attribute set according to a range to which an average similarity to the median attribute keywords of the median attribute set belongs to each other; Create

The travel attribute language personalization device according to an embodiment of the present specification is a travel attribute language personalization device including a terminal and an information providing device that is connected to the terminal through a communication network and provides a plurality of high-level attribute keywords and intermediate attribute keywords to the terminal As a device, the information providing device stores a first 　1　higher attribute-median attribute association degree corresponding to an upper attribute keyword 　-　 medium attribute keyword pair, and a first intermediate attribute keyword-object association degree corresponding to the intermediate attribute keyword and object pair A storage unit; On the basis of the 　1　upper attribute-median attribute association degree, a median attribute set including the median attribute keyword having the 　1　1st attribute-median attribute association degree equal to or greater than a reference value is generated, and the intermediate attribute together with the upper attribute keyword A control unit that provides an interface for adding or deleting an intermediate attribute keyword from the set; And a communication unit that receives the addition or deletion of an intermediate attribute keyword to the intermediate attribute set according to a user input through the interface, wherein the information providing device includes the information providing device through the terminal. If a specific high-order attribute keyword is selected from among 　, the first 　1 　 high-order attribute corresponding to the selected high-order attribute keyword 　-　 median attribute keyword pair, based on the relation degree of the median attribute, 　 the first 　1 　 high-order attribute- It creates a median property set including median property keywords with a degree of median property relevance, and provides an interface for adding or deleting median property keywords to the median property set together with the upper property keywords, and 　the median property according to user input Add or delete an intermediate attribute keyword in the attribute set, calculate the first 　1　higher attribute keyword-object correlation corresponding to the upper attribute keyword and object pair selected based on the first 　1　median attribute keyword-object correlation, and the second 1　Provides an object corresponding to the high-level attribute keyword-object association degree as the interface, creates a high-level attribute filter including a plurality of preset high-order attribute keywords, provides an interface including the high-level attribute filter, and attribute set Provides an interface including, and receives the second 　2　higher attribute-median attribute association degree for each of the middle attribute keywords selected through the interface, and reflects the inputted 　2　higher attribute-median attribute association degree to the first 　1 A personalized travel attribute language is created by correcting the high-level attribute-median attribute association.

According to an embodiment of the present specification, a method and apparatus for personalizing travel attribute language may be provided.

1 is a network configuration diagram of an information providing system using a travel attribute language according to an embodiment of the present specification.
2 is a block diagram of a terminal 200 according to an embodiment of the present specification.
3 is a block diagram of an information providing apparatus 300 according to an embodiment of the present specification.
4 is a flowchart of a process of providing information through an information providing interface according to an embodiment of the present specification.
5 is a detailed flowchart of step 910 according to an embodiment of the present specification.
6 is a detailed flowchart of step 510 according to an embodiment of the present specification.
7 is a detailed flowchart of step 530 according to an embodiment of the present specification.
8 is a detailed flowchart of step 910 according to another embodiment of the present specification.
9 is a flowchart of a method for personalizing a travel attribute language according to an embodiment of the present specification.
10 is an example of a stored object-keyword association diagram according to an embodiment of the present specification.
11 is a detailed flowchart of step 940 according to an embodiment of the present specification.
12 is an example of an interface page including an attribute filter according to another embodiment of the present specification.
13 is an example of a portion of an interface page including an attribute filter according to an embodiment of the present specification.
14 and 15 are examples of an interface page including a second attribute filter according to an embodiment of the present specification.
16 is an example of an interface page including a result preview unit according to an embodiment of the present specification.
17 is an example of an interface page including an attribute filter according to another embodiment of the present specification.
18 is an example of an interface page including a weight adjuster according to an embodiment of the present specification.

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

In describing the embodiments, descriptions of technical contents that are well known in the technical field to which the present specification pertains and are not directly related to the present specification will be omitted. This is to more clearly convey the gist of the present specification by omitting unnecessary description.

For the same reason, some components in the accompanying drawings are exaggerated, omitted, or schematically illustrated. In addition, the size of each component does not fully reflect the actual size. The same reference numerals are assigned to the same or corresponding components in each drawing.

Hereinafter, embodiments of the present specification will be described with reference to the drawings.

According to some embodiments of the present specification, a reserved word may mean a character string that may be expressed or defined through information on a degree of association with other keywords, or its characteristics, usage methods, and properties may be expressed and defined. However, other methods, for example, reserved words defined/expressed according to manual input by an administrator may be applied to the present invention. The detailed configuration of the correlation information will be described later. The reserved word may also be referred to as a keytalk ^TM in the sense that it becomes a key of talk.

1 is a network configuration diagram of an information providing system using a travel attribute language according to an embodiment of the present specification.

Referring to FIG. 1, an information providing system according to an embodiment of the present specification may include a terminal 200, an information providing apparatus 300, and a communication network 150.

The terminal 200 may be implemented as an electronic device or similar device capable of performing communication, receiving user input, and outputting a screen, for example, a smart phone, PDA, tablet PC, notebook computer, laptop computer, personal computer, etc. I can.

The terminal 200 may be a manager terminal 200-1 or a customer terminal 200-2.

The manager terminal 200-1 is, for example, a terminal used by a manager providing an information service.

The customer terminal 200-2 is a terminal used by a customer receiving an information service.

The information providing apparatus 300 may be implemented as, for example, a workstation, a server, a general-purpose computer, an electronic device capable of performing other communication, or a similar device.

As shown in FIG. 1, the terminal 200 and the information providing apparatus 300 are connected through a communication network 150 and may communicate with each other through the communication network 150. In addition, the manager terminal 200-1 may access the information providing device 300 through an interface directly provided by the information providing device 300.

When the manager terminal 200-1 accesses the information providing device 300 through an interface directly provided by the information providing device 300, the information providing device 300 includes a configuration of a web server or an application server. In this case, the configuration of the web server/application server included in the information providing device 300 may be referred to as an interface module. The interface module may serve as a web server/application server to be described later. The web server/application server may input information or transmit a request message to the connected terminal through an interface, and may receive information and/or a request message transmitted from the connected terminal.

The communication network 150 is, for example, LTE (Long Term Evolution), LTE-A (LTE-Advanced), WI-FI, LAN (Local Area Network), WAN (Wide Area Network), CDMA (Code Division Multiple Access), TDMA (Time Division Multiple Access), WiBro (Wireless Broadband), GSM (Global System for Mobile Communications) and other past, current development, or may be implemented using at least some of the communication methods that are available in the future. Hereinafter, for convenience, the terminal 200 and the information providing device 300 directly communicate with each other without referring to the communication network 150.

In the case of providing interfaces for both the manager terminal 200-1 and the customer terminal 200-2, the information providing device 300 provides object recommendation and travel attribute language personalization when a pre-registered user (administrator) approaches. An interface is provided, and when other general users (customers) access, an interface for inquiring limited information such as object search and inquiry can be provided.

The information providing device 300 may perform a user authentication or terminal authentication procedure to provide such a differentiated interface. For example, the information providing device 300 identifies whether the connected terminal is a manager terminal or a customer terminal through a user authentication process. Alternatively, the information providing device 300 may register as a manager terminal through terminal authentication of the connected terminal. Since the user authentication or terminal authentication procedure between the information providing device 300 and the terminal 200 is already a practical technique, a detailed description thereof will be omitted.

Detailed operations and configurations of the terminal 200 and the information providing apparatus 300 will be described later with reference to FIGS. 2 to 8.

2 is a block diagram of a terminal 200 according to an embodiment of the present specification.

Referring to FIG. 2, a terminal 200 according to an exemplary embodiment of the present specification may include an input unit 210, a display unit 220, a communication unit 230, a storage unit 240, and a control unit 250.

The input unit 210 converts a user's input operation into an input signal and transmits it to the control unit 250. The input unit 210 may be implemented as, for example, a keyboard, a mouse, a touch sensor on a touch screen, a touch pad, a keypad, a voice input, and other input processing devices that are possible in the present, in the past, or in the future. The input unit 210 may receive, for example, a user's information request input and transmit it to the control unit 250.

The display unit 220 outputs a screen according to the control of the controller 250. The display unit 220 may be implemented as, for example, an LCD (liquid crystal display), an LED (light emitting diode), an OLED (organic light emitting diode), a projector, and other display devices that are possible in the present, in the past, or in the future. The display unit 220 may display, for example, an interface page for providing information or an information providing result page. Depending on the embodiment, the display unit 220 may be used instead of the display unit 220 instead of the display unit 220, but instead of the display unit 220, a component using a voice output, vibration, or other method capable of transmitting information to the user.

The communication unit 230 exchanges data with the information providing device 300 and/or other external devices. The communication unit 230 transmits the data received from the information providing device 300 to the control unit 250. In addition, the communication unit 230 transmits data to the information providing device 300 under the control of the controller 250. The communication technology used by the communication unit 230 may vary depending on the type of communication network 150 or other circumstances.

The storage unit 240 stores data under the control of the controller 250 and transmits the requested data to the controller 250.

The controller 250 controls the overall operation of the terminal 200 and each component. In particular, the controller 250 transmits an information provision request and other data to the information provision device 300 according to the information input from the input unit 210 as described later, and according to the page information received from the information provision device 300. The result page and/or the interface page are displayed through the display unit 220.

The operation performed by the control unit 250 may be distributedly processed by several physically separated computing devices. Some of the operations performed by the controller 250 are performed by the first server and other operations are performed by the second server. In this case, the control unit 250 may be implemented as a total number of physically separated computing devices.

The storage unit 240 may be implemented as a total of physically separated storage devices.

When the controller 250 or the storage unit 240 is implemented as a total of several devices that are physically separated, communication between several devices may be required. Here, for the sake of simplicity, description will be made on the assumption that the storage unit 240 or the control unit 250 is implemented as one object.

When the terminal 200 transmits and receives data, it may be expressed that the communication unit 230 transmits and receives data according to the control of the controller 250 according to the viewpoint, or that the controller 250 controls the communication unit 230 to transmit and receive data. You can also express it.

Detailed operations of each component of the terminal 200 will be described later with reference to FIGS. 4 to 8.

3 is a block diagram of an information providing apparatus 300 according to an embodiment of the present specification.

Referring to FIG. 3, the information providing apparatus 300 according to an embodiment of the present specification may include a communication unit 310, a control unit 320, and a storage unit 330.

The communication unit 310 exchanges data with the terminal 200 and/or other external devices. The communication unit 310 transmits the data received from the terminal 200 to the control unit 320. In addition, the communication unit 310 transmits data to the terminal 200 under the control of the controller 320. The communication technology used by the communication unit 310 may vary depending on the type of communication network 150 or other circumstances.

The storage unit 330 stores data under the control of the controller 320 and transmits the data requested from the controller 320 to the controller 320.

The controller 320 controls the overall operation of the information providing device 300 and each component. In particular, as will be described later, when the controller 320 receives an interface page request, an information provision result page request, and other data through the communication unit 310, the controller 320 retrieves necessary data from the storage unit 330 ( load) Generates page information and transmits the page information to the terminal 200 through the communication unit 310.

When the information providing device 300 transmits and receives data, it may be expressed that the communication unit 310 transmits and receives data according to the control of the controller 320 depending on the viewpoint, and the controller 320 controls the communication unit 310 to transmit data. It can also be expressed as sending and receiving.

Detailed operations of each component of the information providing apparatus 300 will be described later with reference to FIGS. 4 to 8.

According to another embodiment, instead of a page for visually providing information, data for providing information may be transmitted/received by voice or other methods.

4 is a flowchart of a process of providing information through an information providing interface according to an embodiment of the present specification.

In step 410, the control unit 320 of the information providing device 300 generates interface page information. The interface page information is information necessary to create an interface page. The interface page is a page for inducing a user's input, receiving a user's input, and transmitting the information to the information providing device 300. For example, the interface page information may be in the form of an HTML document or other markup language document. In another embodiment, the terminal 200 has the form information of the interface page in advance, and only a matter corresponding to the content may be transmitted from the information providing device 300 to the terminal 200. Hereinafter, for convenience, it is assumed that interface page information or other page information is delivered in an HTML document format. However, the scope of the rights of the present specification is not limited thereto.

In step 420, the communication unit 310 of the information providing device 300 transmits the interface page information to the terminal 200.

In step 430, the controller 250 of the terminal 200 constructs an interface page using the interface page information. For example, the controller 250 may drive a web browser to analyze an HTML document and configure an interface page in the form of a web page. A separate application may be used instead of a web browser.

In step 440, the display unit 220 of the terminal 200 displays an interface page to the user 400. The interface page may include, for example, an interface through which the user 400 requests information provision, inputs and/or selects a keyword for information provision, and sets for other information provision.

In step 450, the input unit 210 of the terminal 200 receives the selection input of the user 400 inputted through the interface page and transmits it to the control unit 250.

In step 460, the communication unit 230 of the terminal 200 transmits input information for identifying a user's selection input to the information providing device 300 under the control of the controller 250.

In step 470, the control unit 320 of the information providing apparatus 300 generates result page information by using a user's input (eg, keyword and/or other information provision setting). A preparation process for generating result page information and a process of generating result page information will be described later with reference to FIGS. 5 to 11. The result page information may be configured in, for example, an HTML document format and/or an image format.

In step 480, the communication unit 310 of the information providing device 300 transmits the result page information to the terminal 200.

In step 490, the controller 250 of the terminal 200 constructs a result page using the result page information received by the communication unit 230. For example, the controller 250 may construct a result page by analyzing result page information in HTML format.

In step 495, the display unit 220 of the terminal 200 provides a result page to the user.

In the embodiment of FIG. 4, it is assumed that a page in a visual form is provided to the user, but it is also possible to provide an interface or result information through voice. In this case, an audio output unit may be used instead of the display unit 220. Instead of the visual/audible method, another type of interface method that is currently possible or will be possible in the future may be used in the relationship with the user 400. In this case, the information providing apparatus 300 may provide the terminal 200 with information converted in a different manner instead of page information to fit the interface method.

In the embodiment after FIG. 5, the user 400 wants to be provided with information on an object of a specific field of interest that the user 400 is interested in. However, the scope of the rights of the present specification is not limited thereto.

The area of interest (item of interest) can be, for example, a type of object. For example, if the field of interest is'travel destination', objects corresponding to the field of interest may include'Rome','Paris','Istanble', and'Jungfrau'. In addition, for example, if the field of interest is'great man', objects corresponding to the field of interest may include'King Sejong','Lee Sun-shin','Sim Dang', and the like. In addition, for example, if the field of interest is'movie', objects corresponding to the field of interest may include'Man-in**','Spider*','Shinde**', and the like. In addition, for example, if the field of interest is'broadcasting program', the object corresponding to the field of interest may include'infinite **','** of the jungle','** of the throne', and the like.

In the following embodiments, a document is collected to evaluate the relationship (relevance/weight, etc.) between keywords. Collected documents may all be evaluated as having equal value, or newer documents may be evaluated as having higher value. That is, the association between the age of the document at the time of evaluation and the keywords appearing in the document may have a negative correlation.

Even in the process after FIG. 5 to be described later, the value may be evaluated differently according to the freshness of the document. For example, a case where two keywords appear together in a document 1 day after the evaluation point can be evaluated with a 10 times higher association than a case where two keywords appear together in a document 10 days after the evaluation point. The age of a document may be evaluated in units of seconds/minutes/hours, or in units of days/months/years. The control unit 320 divides a partial relevance value by the document evaluated before the age of the document is reflected and divides the partial relevance value by the age of the document to set a partial relevance to which the document age is reflected, and accumulates the partial relevance between the two keywords. You can set the degree of association.

The creation time of a document to check the age of a document can be determined using, for example, the posting time and/or metadata included in the document, or through periodic crawling, when a new document not found in the previous crawl is found. In this case, it may be determined that a new document was added at the time of a new crawl.

5 is a flow chart illustrating a method of storing an object-keyword association as a preprocessing process for personalization of a travel attribute language according to an embodiment of the present specification.

5, in step 510, the controller 320 determines a representative attribute keyword candidate set from the first set of documents. The control unit 320 may collect, for example, keywords frequently appearing in documents corresponding to the field of interest among the first set of documents as a representative attribute keyword candidate set.

6 is a detailed flowchart of step 510 according to an embodiment of the present specification.

The control unit 320 selects keywords appearing in a document, such as an object keyword indicating an object item belonging to a specific field, and keywords appearing in a document, such as a field keyword indicating a specific field, as a first attribute keyword candidate set and a second attribute keyword candidate. Can be set as a set.

For example, if the field of interest to provide information provision service is a celebrity, the field keyword may include'celebrity','celebrity','movie actress','star','celebrity','celeb', and the like. The field keyword may be set by an administrator or recommended and set by the controller 320. After acquiring some field keywords, the controller 320 may recommend/set a similar keyword, which has been analyzed to have a degree of association with the field keywords or higher, as an additional field keyword.

If the field of interest is celebrity, the object keyword may be an individual person belonging to the field of interest. That is, each person corresponding to a celebrity in the field of interest may be an object keyword.

To describe the relationship between the field keyword and the object keyword, for example, the field keyword may correspond to the attribute or type of the object keyword. If the field keyword indicates a set, the object keyword may indicate elements belonging to the set.

Object keywords may be set by an administrator or may be selected in a similar manner to field keywords. According to another embodiment, the controller 320 may analyze the context of the collected documents and select keywords that are determined to be elements belonging to the set indicated by the field keyword as object keywords.

Popular object keywords and non-popular object keywords can be classified according to the amount of search/collection of the corresponding object keywords. The controller 320 may search/collect a document including each object keyword, set an object keyword whose collection amount is greater than or equal to a specific threshold value as a popular object keyword, and set the remaining object keywords as an unpopular object keyword.

Popular field keywords and non-popular field keywords may be classified according to the amount of search/collection of keywords in the field. The controller 320 may search/collect a document including each field keyword, set a field keyword whose collection amount is greater than or equal to a specific threshold value as a popular field keyword, and set the remaining field keywords as an unpopular field keyword. However, a threshold value for distinguishing a popular object keyword from a non-popular object keyword and a threshold value for distinguishing a popular field keyword and a non-popular field keyword may be different. Hereinafter, for convenience, the popular object keywords and popular field keywords are collectively referred to as popular field object keywords. Also, for convenience, unpopular object keywords and non-popular field keywords are collectively referred to as unpopular field object keywords.

In a modified embodiment, only the popular field keyword or the popular object keyword may be used instead of the popular field object keyword. In a modified embodiment, only an unpopular field keyword or an unpopular object keyword may be used instead of the unpopular field object keyword.

In step 610, the controller 320 sets keywords that appear together in the same document as the popular field object keywords as the first attribute keyword candidate set.

The controller 320 may search/collect documents including popular field object keywords, and set keywords included in the collected documents as a first attribute keyword candidate set. According to another embodiment, the controller 320 may exclude a field keyword and an object keyword from among keywords included in the collected document from the first attribute keyword candidate set. In addition, the controller 320 may exclude a preset meaningless keyword, for example, a survey/article, etc. from the first attribute keyword candidate set. According to another embodiment, the controller 320 may include a keyword registered in a preset dictionary among keywords included in the collected document in the first attribute keyword candidate set.

According to another embodiment, the controller 320 searches/collects a document containing a keyword of a popular field object, and searches keywords arranged within a preset distance from a keyword of a popular field object or a sentence containing the keyword in the collected document. It may be included in the first attribute keyword candidate set. According to another embodiment, the controller 320 searches for/collects a document containing a keyword of a popular field object, analyzes a context, and selects keywords used for formulating/descripting a keyword of a popular field object as a first attribute keyword candidate. It can also be included in the set.

The distance between keywords or between a keyword and a sentence is, for example, the number of two keywords or sentences placed between a keyword and a sentence, the number of words placed between two keywords or a keyword and a sentence, between two keywords or a keyword and a sentence. It may be determined based on one or more of the number of positioned words, two keywords, or the number of characters between a keyword and a sentence.

The controller 320 may first perform morpheme analysis for keyword analysis.

In step 620, the controller 320 sets keywords that appear together in the same document as the non-popular field object keywords as the second attribute keyword candidate set.

The controller 320 may search/collect a document including an unpopular field object keyword, and set keywords included in the collected document as a second attribute keyword candidate set. According to another embodiment, the controller 320 may exclude a field keyword and an object keyword from among keywords included in the collected document from the second attribute keyword candidate set. In addition, the controller 320 may exclude preset meaningless keywords, for example, survey/article, etc. from the second attribute keyword candidate set. According to another embodiment, the controller 320 may include a keyword registered in a preset dictionary among keywords included in the collected document in the second attribute keyword candidate set.

According to another embodiment, the control unit 320 searches/collects a document containing an unpopular field object keyword, and searches keywords arranged within a preset distance from the unpopular field object keyword or a sentence containing the keyword in the collected document. It may be included in the second attribute keyword candidate set. According to another embodiment, the control unit 320 searches for/collects a document containing an unpopular field object keyword, analyzes a context, and selects keywords used for formulating/descripting the unpopular field object keyword as a second attribute keyword candidate. It can also be included in the set.

The distance between keywords or between a keyword and a sentence is, for example, the number of two keywords or sentences placed between a keyword and a sentence, the number of words placed between two keywords or a keyword and a sentence, between two keywords or a keyword and a sentence. It may be determined based on one or more of the number of positioned words, two keywords, or the number of characters between a keyword and a sentence.

The controller 320 may first perform morpheme analysis for keyword analysis.

In step 630, the controller 320 may set keywords belonging to both the first attribute keyword candidate set and the second attribute keyword candidate set as the representative attribute keyword candidate set. That is, keywords that are used as expressions for modifying popular field object keywords and also used as expressions for non-popular field object keywords may be collected in the representative attribute keyword candidate set.

According to another embodiment, in step 510, the controller 320 may include keywords that appear together with object keywords and/or field keywords in the representative attribute keyword candidate set regardless of whether they are popular or unpopular.

Returning to FIG. 5, in step 520, the controller 320 determines two or more sub-keywords associated with each representative attribute keyword included in the representative attribute keyword candidate set from the second set of documents.

The second set document used for extracting the lower keyword in step 520 and the first set document used for extracting the representative attribute keyword candidate set in step 510 may be different document sets or may be the same document set. For example, the first set of documents may be a set including all collectable documents, and the second set of documents may be a set including only documents in which a specific field of interest to provide an information providing service is used as a main keyword. . The control unit 320 may analyze collectible documents and analyze whether each document is a document used as a major keyword in a specific field of interest to provide an information providing service based on keywords that appear frequently. According to another embodiment, both the first set of documents and the second set of documents may be a set including all collectable related documents. According to another embodiment, the first set of documents may be a set including all of the collectable related documents, and the second set of documents may be a set including only documents related to a specific field of interest for which the information providing service is to be provided. According to another embodiment, the second set of documents may be a set including all of the collectable related documents, and the first set of documents may be a set including only documents related to a specific field of interest for which an information providing service is to be provided.

For step 520, the control unit 320, for example, in order to generate a set including only documents related to a specific field of interest to provide an information providing service, documents including a field keyword indicating the field of interest itself and/ Alternatively, a set including only documents related to a specific interest may be generated by collecting documents including object keywords belonging to a corresponding interest field, and extracting documents in which the weight of the field keyword/object keyword is greater than or equal to a preset value. The weight of the field keyword/object keyword can be determined based on the frequency, location, and context of the field keyword/object keyword. For example, a document in which a field keyword/object keyword frequently appears, a field keyword/object keyword is used as a title of a corresponding document, or displayed in large letters or a font for emphasis may be classified as a document related to a specific field of interest.

In step 520, the controller 320 analyzes at least a part of the second set of documents, extracts a preset number of sub-keywords with the highest relevance to each representative attribute keyword, and extracts two or more sub-keywords associated with each representative attribute keyword. You can extract keywords.

The controller 320 may set a degree of association between the representative attribute keyword and the lower keyword in consideration of the frequency at which the lower keyword appears in the same or similar context as the representative attribute keyword, for example. For example, it can be seen that words appearing around keyword A in a specific sentence may appear around words related to keyword A in other documents.

"I went on a trip with a big heart, but because it was July, the weather was too hot and I suffered."

"I went on a trip with a big heart, but because it was July, the weather was too humid, so I suffered."

Looking at the above two sentences, the word "because it's hot" has been replaced by the word "because it's wet" in the same context. The controller 320 may infer that “hot” and “wet” are words related to each other.

"I went on a trip with a big heart, but because it was July, the weather was too hot and I suffered."

"I went on vacation with a big heart, but because it was July, it was too hot and I suffered."

Similarly, the control unit 320 may infer that “travel” and “vacation” are related words through the above two sentences.

"I went on a trip with a big heart, but because it was July, the weather was too hot and I suffered."

"I went on a trip with a big heart, but because it was August, the weather was too hot and I suffered."

Similarly, the controller 320 may infer that “July” and “August” are related words through the above two sentences.

The control unit 320 indicates that "hot" and "wet" are related words, "July" and "August" are related words, and "travel" and "vacation" are related words through the previously collected documents. It can be saved. Assume that the following sentences are collected.

"I went on vacation with a big heart, but because it was July, the weather was too humid, so I suffered."

"I went on a trip with a big heart, but it was hard because the weather was too hot because it was August."

If the two sentences are not the same context, but know that hot" and "wet" are related words, "July" and "August" are related words, and "travel" and "vacation" are related words, the controller 320 ) Through the above sentence, you can learn that "I suffered" and "I had a hard time" are also related words.

Keyword pairs with a high frequency appearing in the same/similar context may be determined to have a high correlation with each other. In addition, the higher the similarity between the context in which the two keywords appear, the higher the correlation between the two keywords can be determined. The control unit 320 performs learning using the collected documents to set the degree of association between keywords, and sets the degree of relevance of keywords appearing in the sentence by using the relationship between the set keywords and the context of the sentence. The accuracy of judging the relationship between liver can also be improved.

As similar learning methods, NNLM (Neural Net Language Model), RNNLM (Recurrent Neural Net Language Model), word2vec, skipgram, and CBOW (Continuous Bag-of-Words) methods are known. In particular, when word2vec is used, word2vec learns using documents and associates each keyword with a vector, and the similarity between the two keywords can be determined by calculating the cosine similarity of the two vectors.

In this manner or a similar manner, the controller 320 may analyze at least a part of the second set of documents and extract sub-keywords having the highest correlation with each representative attribute keyword by a preset number.

In step 530, the controller 320 may determine an association weight corresponding to each pair of representative attribute keywords and lower keywords in the representative attribute keyword candidate set from the second set of documents.

7 is a detailed flowchart of step 530 according to an embodiment of the present specification.

In step 710, the controller 320 may analyze at least a part of the second set of documents and set a degree of correlation between the lower keywords. For example, it is assumed that those collected as related sub-keywords for the representative attribute keyword A1 are 50 sub-keywords of B1 ₁ to B1 ₅₀ . In this case, the controller 320 may set the degree of correlation between the two sub-keywords by using the frequency at which the two sub-keywords appear together in the same document for these 50 sub-keywords. B1 is also interconnected between the _first B1 and B1 ₂ and B1 is determined in accordance with the _first frequency to the _second appearing in the same document. According to another embodiment, B1 ₁ and B1 ₂ The distance between the addition to the frequency appearing in the same document that affects the degree interrelated, B1 ₁ and B1 if the _two appeared in the same document both keywords B1 ₁ and B1 distance between _two (or a statement that both keywords appear The closer the) is, the higher the degree of correlation can be recognized. In a similar way, the degree of correlation between sub-keywords can be established. The distance between keywords or between a keyword and a sentence is, for example, the number of two keywords or sentences placed between a keyword and a sentence, the number of words placed between two keywords or a keyword and a sentence, between two keywords or a keyword and a sentence. It may be determined based on one or more of the number of words positioned, two keywords, or the number of characters positioned between a keyword and a sentence.

In step 720, the controller 320 may set an association weight between each representative attribute keyword and the lower keyword based on the degree of correlation between the lower keywords. The control unit 320, for example, for a sub-keyword set corresponding to each representative attribute keyword, a correlation degree between a specific sub-keyword in the sub-keyword set and another sub-keyword in the sub-keyword set, and the specific sub-keyword and the The association weight between the specific lower keyword and the representative attribute keyword may be set so that the association weight between the representative attribute keywords has a positive correlation with each other.

For example, as the correlation between the sub-keyword B1 ₁ of the representative attribute keyword A1 and the other sub-keywords B1 ₂ to B1 ₅₀ of A1 is higher, the association weight between A1 and B1 ₁ may be set higher. For example, an arithmetic mean (or sum) of correlations between B1 ₁ and other sub-keywords of A1 (B1 ₂ to B1 ₅₀ ) may be an association weight between B1 ₁ and A1. Instead of a simple arithmetic mean, a geometric mean/harmonized mean may be used. A cutting average that is averaged out of the correlations between the sub-keywords B1 ₁ and other sub-keywords of A1 (B1 ₂ to B1 ₅₀ ) may be used, excluding the two highest (example) and the lowest two (example). have. A median may be used instead of the arithmetic mean of the correlation.

According to some embodiments, "B1 ₁ and B1 _{2, which} are used to calculate the association weight of B1 ₁ with respect to A1, are "The frequency that appears in the same document" simply means that B1 ₁ and B1 ₂ It does not depend on the number of documents appearing together (or appearing in the same sentence or in close proximity), but B1 ₁ and B1 ₂ The number of documents appearing together (or appearing in the same sentence, or appearing in close proximity) can be obtained by dividing the number of documents in which B1 ₁ appears and/or the number of documents in which B1 ₂ appears. In a similar way, "B1 ₁ and B1 ₂ "The frequency of appearance in the same document" means that B1 ₁ and B1 ₂ Appeared to as (to appear or are in the same sentence, or close to the emergence of) correlation of the number and the notes of the document to the number and the positive correlation between the B1 ₁ appeared number of documents and / or to have B1 ₂ appeared in the document It can be set to have a relationship. It is simply a kind of normalization to prevent a commonly used word from having a high association weight to the representative attribute keyword A1.

Returning to FIG. 5, in step 540, the controller 320 may set a degree of sub-relation between the object and the sub-keyword from the first set of documents.

Among the first set of documents, a document such as an object keyword representing an object item (for example, "Taylor Swift"), or sub-keywords frequently appearing in the same sentence or adjacent sentence may be determined to be related to the corresponding object. The controller 320 may collect documents in which an object keyword of a corresponding object item appears, and set a sub-relationship between the sub-keyword and the object keyword according to the frequency of appearances together in the documents. In particular, when the lower keyword appears in the same sentence as the object keyword, the control unit 320 may set the association between the lower keyword and the object to be higher than when the lower keyword appears in a sentence different from the object keyword.

The controller 320 may set a higher degree of association between the lower keyword and the object of the corresponding object keyword as the sentence in which the lower keyword appears is closer to the sentence in which the object keyword appears. The proximity of two sentences is, for example, one of the number of sentences between two sentences, the number of words between two sentences, the number of words between two sentences, and the number of characters between two sentences. It may be determined based on more than one.

The controller 320 may set a higher degree of association between the lower keyword and the object of the corresponding object keyword as the position where the lower keyword appears is closer to the position where the object keyword appears. The proximity between the sub-keyword and the object keyword is, for example, the number of sentences between the sub-keyword and the object keyword, the number of words between the sub-keyword and the object keyword, and the number of words between the sub-keyword and the object keyword. It may be determined based on any one or more of the number and the number of characters positioned between the lower keyword and the object keyword.

In step 550, the controller 320 may set an object-keyword association degree between the object and each of the representative attribute keywords by using the sub-relationship in step 540 and the association weight in step 530.

For example, the object-keyword association between object C and the representative attribute keyword A1 is determined by using the sub-keywords of C and A1 (for example, B1 ₁ to B1 ₅₀ ) and the association weight of each sub-keyword. Can be set. For example, the object-keyword association degree between the object C and the representative attribute keyword A1 may be set higher as the lower degree of association between the object C and B1 ₁ to B1 ₅₀ is higher.

In addition, in relation to A1, if the sub-keyword with a higher association weight has a high sub-relationship with object C, the sub-keyword with a lower association weight has a higher sub-keyword between object C and the representative attribute keyword A1 than when the sub-keyword is higher. The object-keyword association degree of may be set higher. For example, in the case of Table ₁ , the sub-relationship of the one with higher association weight (B1 ₁ ) than in the case of Table 2 is higher, so that in the case of Table 1, the object between object C and the representative attribute keyword A1- Keyword relevance may be set high.

Associated weight with A1 Degree of association with C B1 ₁ 0.5 0.5 B1 ₂ 0.2 0.2

Associated weight with A1 Degree of association with C B1 ₁ 0.2 0.5 B1 ₂ 0.5 0.2

According to an embodiment, the object-keyword association degree between the object C and the representative attribute keyword A1 may be obtained as the sum of the product of the association weight corresponding to each sub-keyword and the sub-relationship (or using this total). In the case of Table 1, 0.5×0.5+0.2×0.2=0.29, and in the case of Table 2, 0.2×0.5+0.5×0.2=0.20, so the case of Table 1 is between the object C and the representative attribute keyword A1 than the case of Table 2. The object-keyword association degree of may be set to be high. The above-described method of calculating the object-keyword association is only exemplary, and if the sub-relationship with C in step 540 and the association weight with A1 in step 530 are positively correlated with the object-keyword association between C and A1. Other methods may be used.

Thereafter, when the communication unit 310 receives a request to provide information related to a specific representative attribute keyword, the control unit 320 may provide a result item through the communication unit 310 based on the object-keyword association degree extracted in step 550. For example, when receiving a request to provide information including one of the representative attribute keywords, the control unit 320 may provide information on the object items in the order of the highest object-keyword association in the relationship with the corresponding representative attribute keyword. have.

In another embodiment, when receiving an information provision request including two or more representative attribute keywords and weights corresponding thereto, the controller 320 associates object-keywords with representative attribute keywords included in the information provision request for each object item. Information on object items may be provided in the order of the highest sum (or average) of values multiplied by weights (or similarly weighted) to degrees.

8 is a flowchart of a process of providing information according to another embodiment of the present specification.

The example of FIG. 8 further includes two steps 523 and 526 between steps 520 and 530 in addition to the same processes as the example of FIG. 5. Here, redundant description is avoided, and only steps 523 and 526 are described.

In step 523, the controller 320 determines whether each of the sub-keywords extracted in step 520 corresponds to an emotion language (emotional language). To this end, the storage unit 330 or an external server may have a dictionary of appraisal words. The appraised word dictionary is a tool for determining whether a certain word (keyword) is an appraised word, and may hold a list of appraised words, for example. A keyword included in the list of appraised words may be regarded as an appraised word, and a keyword not included in the appraised word list may be determined to be not an appraised word. However, this judgment is based on dictionary meaning, and may not reflect the popular use of words that change with the times. Therefore, the control unit 320 does not determine whether the representative attribute keyword itself is an appraised word, but determines whether to use the representative attribute keyword based on whether the subkeywords related to the representative attribute keyword are appraised words.

In another embodiment, the controller 320 may add another word registered as an appraised word in the appraised word dictionary and learned to have a high correlation (with a pre-set value or more) with a predetermined number or more of words to the appraised word dictionary.

In step 526, the controller 320 may leave only a preset number of representative attribute keywords in the representative attribute keyword candidate set in the order in which the emotional language ratio (or number) of the associated lower keyword is high, and remove the remainder. Through this process, it is possible to prevent keywords far from emotional language from being treated like emotional language.

9 is a flowchart illustrating a process of personalizing a travel attribute language according to an embodiment of the present specification.

In step 910, the control unit 320 stores in the storage unit 330 a degree of relation between the object and the intermediate attribute keyword-object corresponding to the object and the intermediate attribute keyword pair.

10 is an example of a stored first median attribute keyword-object association diagram according to an embodiment of the present specification.

In the example of FIG. 10, there are m objects (i ₁ to i _m ) and n median attribute keywords (k ₁ to k _n ).

For example, the first median property keyword-object association degree of the object i ₅ and the median property keyword k ₃ is w _5,3 .

The process of step 910 may be performed according to, for example, some of the embodiments of FIGS. 5 to 8, a process similar thereto, or a process corresponding thereto. According to another embodiment, the process of step 910 may be performed by an input of an administrator or may be performed by receiving a first median attribute keyword-object association degree determined in an external system through a network or a storage medium.

Next, in step 920, the control unit 320 stores in the storage unit 330 a degree of association between the upper attribute keyword and the intermediate attribute keyword corresponding to the pair of the upper attribute keyword and the intermediate attribute keyword.

The process of step 920 may be performed, for example, by an input of an administrator or by receiving a basic reserved word-keyword association degree determined in an external system through a network or a storage medium. According to another embodiment, the process of step 920 may be performed in a manner similar to the process of FIGS. 5 to 8 by analyzing collectible documents such as the Internet, SNS, and news. In addition, the process of step 920 includes a process of reflecting the user's feedback, as described later.

In step 930, the communication unit 310 receives and acquires an interest item from the terminal 200, and transmits the received interest item to the control unit 320.

The received interest item is an interest item received by the terminal 200 from a search user.

In step 940, the control unit 320 establishes a correlation between the upper attribute keyword and the middle attribute keyword according to the manager input.

11 is a detailed flowchart of step 940 according to an embodiment of the present specification.

Referring to FIG. 11, in step 941, the controller 320 extracts a plurality of high-level attribute keywords for the interest item and provides an interface including the high-order attribute keywords to the terminal.

In step 942, the controller 320 receives one or more higher-order attribute keywords selected from the terminal as reserved words through the interface.

Here, the reserved word is an upper attribute keyword received from a search user (administrator or customer) among a plurality of higher attribute keywords included in the attribute set.

In step 943, the control unit 320 extracts the median attribute keyword associated with the reserved word by using the previously stored first higher attribute-median attribute correlation, and includes the median attribute keyword associated with the reserved word and the median attribute keywords similar to the median attribute keyword. A median attribute keyword selection/adjustment interface is provided to the terminal 200 as a second attribute filter. Through this interface, a user can additionally select an intermediate attribute keyword to be set to be associated with a reserved word, or remove/delete an intermediate attribute keyword set to be associated with a reserved word as unrelated.

In step 944, the control unit 320 receives the second 　2　 high-order attribute-median attribute correlation for each of the one or more intermediate attribute keywords selected as being associated with the reserved word from the terminal through the interface.

For example, when inputting the 　2　 high-level attribute-median attribute association degree is selected from among a plurality of intermediate attribute keywords included in the interface according to a user's input, the selected intermediate attribute keyword is selected from the plurality of intermediate attribute keywords. This can be done by automatic movement to the front of the attribute keyword array. The controller 320 may assign a second high-order attribute-median attribute association degree according to an arrangement order of the intermediate attribute keywords, for example. That is, the faster the arrangement order, the higher the correlation between the second higher-order attribute and the intermediate attribute may be corrected.

In another variation on the input of the 　2　 high-level attribute-median attribute association degree, it may be performed by rearranging the order of a plurality of second attribute keywords included in the interface. The control unit 320 may, for example, assign a degree of relation of the second 　 upper attribute-median attribute according to the rearrangement order. That is, the faster the rearrangement order is, the higher the correlation between the second upper-level attribute and the intermediate attribute may be corrected.

In another variation, the degree of association between the second 　 high-level attribute and the intermediate attribute may be directly input through the interface.

The 　1　higher attribute-median attribute association degree is corrected by reflecting the 　2　higher attribute-median attribute association degree to the previously stored 　1　higher attribute-median attribute association degree. The correction of the 　1　 high-order attribute-median attribute association degree will be described in detail with reference to step 990 described later.

Returning to FIG. 9, in step 950, the control unit 320 includes the first 　1　median attribute keyword-object association and the 　1　higher attribute corresponding to the upper attribute keyword and the object pair selected based on the 　2　higher attribute-median attribute association degree. Calculate attribute keyword-object association.

In operation 960, the controller 320 may provide an object item according to a reception reserved word and a first higher attribute keyword-object association degree corresponding to the selected higher attribute keyword. For example, if the first higher-order attribute keyword-object correlation corresponding to the reception reserved word C ₂ is as shown in Table 3 below, the controller 320 may provide the object items in the order of Table 4.

Object item Reserved word-object association with received reserved word i ₁ 0.23 i ₂ 0.33 i ₃ 0.99 i ₄ 0.84

order Object item Reserved word-object association with received reserved word One i ₃ 0.99 2 i ₄ 0.84 3 i ₂ 0.33 4 i ₁ 0.23

That is, the control unit 320 may provide the object items in the order of the highest correlation between the first higher keyword and the object corresponding to the reception reserved word. The terminal 200 receiving the object item may provide information on the object i ₃ to the user through the display unit 220. The terminal 200 may also provide information on other object items in a lower order as necessary. The terminal 200 may provide information on the object i ₃ to the user through a speaker instead of the display unit 220 by voice.

If a change of the interest item is input through the interface in step 970, the process returns to step 930. If the change of the interest item is not input, the process proceeds to step 980.

In step 980, when a selection change of a higher-order attribute keyword (reserved word) is input through the interface, the process returns to step 940. If a change in the higher-order attribute keyword (reserved word) is not input, the process proceeds to step 990.

In step 990, the 　1　 high-order attribute-median attribute association degree is corrected by reflecting the 　2　 high-order attribute-median attribute association degree selected in step 950.

The first higher attribute-median attribute association degree may be reset according to the input second higher attribute-median attribute association degree.

By repetition of this process, the 2　 high-level attribute-median attribute association selected by the user is reflected in the database.

12 to 18 are examples of interface pages including attribute filters according to an embodiment of the present specification.

Here, the attribute filter may be referred to as an attribute filter in the sense that it acts as a filter representing the attribute desired by the user.

Referring to FIG. 12, an interface page I-100 including an attribute filter includes a first attribute filter unit I-120, a second attribute filter unit I-130, and a result preview unit I-140. It may include.

The first attribute filter unit I-120 provides a higher attribute keyword for an interest item selected by a user as a first attribute filter.

The attribute filter displayed on the first attribute filter unit I-120 may be composed of reserved words calculated as a reserved word-object association degree.

The user may select one or more upper attribute keywords from among a plurality of higher attribute keywords provided in the first attribute filter.

For example, when'broadcasting' is selected as an interest item by the user, the information providing device 300 may have previously stored'good','various','prepared','best person','interesting' for'broadcasting'. ', etc. may be provided as a first attribute filter, and a higher attribute keyword among keywords included in the first attribute filter may be selected from the user through the terminal 200.

The selected high-level attribute keyword is displayed to be distinguishable from other high-level attribute keywords that are not selected.

Meanwhile, the first attribute filter unit I-120 may further include an interest item display unit I-110.

The interest item display unit I-110 displays the interest item selected by the user.

The user can change the interest item through the interest item display unit I-110.

For example, when the user selects the interest item display unit I-110, an interface for selecting the interest item is provided, and the user can change the interest item by inputting the interest item or selecting from a plurality of interest item lists.

It goes without saying that when the interest item is changed, the first attribute filter is also changed.

For example, if the interest item is'Travel', the first attribute filter is'Classic','Good for Gourmet Travel','Romantic','Stars','Beautiful Sunset','Healing. Good','Colorful','The sky is blue','More than expected','Good for family travel','Good for drinking tea','Clean','Satisfying','Exciting','Thrilling' ','mysterious','impressive','good for free travel','exciting','pleasant', etc. can be included.

In addition, for example, when the interest item is'movie', the first attribute filter is'excellent workmanship','good image quality,''exciting','philosophical','inspiring','good OST','masterpiece In','strong','strong' eyes','probable','specular','with a great scene','calm','masterpiece','sweet','individual', ' The story may include solid','the best','thinking about life', and'recommending'.

The second attribute filter unit I-130 displays an attribute set of the median attribute keyword as a second attribute filter.

The second attribute filter includes a plurality of median attribute keywords (attribute sets) selected based on a preset degree of association with an upper attribute keyword selected by the user through the first attribute filter unit I-120. Accordingly, when the upper attribute keyword is changed through the first attribute filter unit I-120, the attribute set included in the second attribute filter unit I-130 is also changed.

13 is an example of a first attribute filter unit I-120 and a second attribute filter unit I-130 included in the interface page of FIG. 12.

The control unit 320 generates an attribute set including a plurality of intermediate attribute keywords based on a predetermined high-level attribute-median attribute association with respect to the upper attribute keyword selected in the first attribute filter, and includes the generated attribute set. Provides an interface. Through the second attribute filter unit I-130, a degree of similarity corresponding to a pair of upper attribute keyword-median attribute keyword for the middle attribute keyword may be input from the user.

The second attribute filter unit I-130 of FIG. 13 is an example of an interface.

In the interface, a plurality of intermediate attribute keywords associated with the upper attribute keywords are arranged.

13 is an example of a second attribute filter when'best person' is selected as the upper attribute keyword through the first attribute filter, and the representative median attribute keyword'is best' stored in association with the selected upper travel attribute language'best person' Is displayed first, and is similar to the representative middle-ranking attribute keyword'is the best','It is a legend,''It is a history','It is great','It is awesome','It is great','It is fantastic','It is amazing' ,'Perfect','Good','Cool','Unforgettable','It's God's Hand','Exciting','Insane','Strong','Sense','Beautiful', ' Attractive', ..., etc. are arranged in order. The degree of similarity between'the best' and another keyword may be determined by referring to, for example, the frequency at which two keywords appear simultaneously in the same document, and the frequency at which two keywords appear simultaneously within a certain distance within the same sentence. For example, using a word-to-vector (W2V; Word2vec) related to the item of interest or a technique of similar function, the relative distance between two keywords is determined, and the closer the relative distance between the two keywords is, the more similar (higher similarity). Can be handled.

The representative median attribute keyword may be displayed differently from other median attribute keywords. For example, the representative median attribute keyword'best' may be displayed in yellow, and other median attribute keywords may be displayed in black. Median attribute keywords other than the representative median attribute keywords may display at least one of the representative median attribute keywords and the brightness/saturation/color of the background or text color differently.

14 and 15 are examples of an interface page including a second attribute filter according to an embodiment of the present specification.

As shown in FIG. 14, the farther away from the representative median attribute keyword (the more similar it is), the lighter the background may be displayed. For example, the font color, background color, font, font thickness, and frame around the text according to the similarity of each median property keyword that does not belong to the major median property keyword and the similarity to the major median property keyword(s) Different shapes, etc. can be displayed to be distinguished from each other. In addition, a method of displaying the median property keywords more similar to the representative median property keywords may be applied further ahead (upper).

The arrangement order of the attribute sets displayed on the second attribute filter unit I-130 may be changed by the user.

For example, when an arbitrary median travel property language is selected from the arranged median property keywords, the terminal 200 may transmit input information obtained by converting a user's input to the information providing device 300.

The information providing apparatus 300 rearranges the order of the median attribute keywords of the second attribute filter according to the input information received from the terminal 200.

For example, the median attribute keyword selected by the user is preferentially placed. Preferentially placed means that the selected median attribute keyword is displayed more visually by the user than the unselected median attribute keyword. For example, it is placed first in the array of intermediate attribute keywords. As shown in FIG. 15, when'unique' (P) is selected by the user in the second attribute filter displayed on the second attribute filter unit I-130, the second attribute filter illustrated in FIG. 15 'It is' (P) is placed before'It is the best'. In addition, a certain number of keywords having a high similarity to the selected median property keywords may be displayed in priority after the selected median property keywords and/or displayed in a distinct color based on the median property keywords selected as being associated with the upper property keywords. have.

According to another example, when the user changes and inputs the arrangement position of the median attribute keywords arranged in the second attribute filter unit I-130, the terminal 200 transmits the related input information to the information providing device 300, and , The control unit 320 of the information providing device 300 rearranges the median attribute keywords of the second attribute filter unit I-130 according to input information received from the terminal 200.

When the information providing device 300 receives and stores the user information from the terminal, the rearranged second attribute filter is stored in connection with the user information, so that the rearranged'reserved word' is rearranged for the same user. A second attribute filter can be provided.

16 is an example of an interface page including a result preview unit according to an embodiment of the present specification.

As shown in FIG. 16, the result preview unit I-140 provides information on one or more objects searched based on the selected travel attribute language. That is, object information retrieved according to a user's selection through the first attribute filter unit I-120 and the second attribute filter unit I-130 is provided through the result preview unit I-140.

The result preview unit I-140 may display an image and an individual item name (eg, travel destination/travel destination photo) of the object retrieved based on the selected travel attribute language. When there are a plurality of searched objects, the objects can be displayed in the order of high relevance.

When the searched object is, for example, a travel destination, a recommended travel destination, a best travel destination, a corresponding travel destination picture, a corresponding travel destination video, a corresponding destination clothing, a corresponding destination travel map, a corresponding destination tourist map, and a price comparison of a corresponding destination airline ticket may be displayed.

When an arbitrary object is selected among a plurality of objects, detailed information on the object may be provided.

If the searched object is, for example, travel destinations, if a destination is selected, the destination picture, the destination video, the destination travel story, the destination attire, the destination travel map, the destination map of the destination, and the price comparison of the destination ticket are displayed in detail. Can be.

Through the result preview, the user can check the object item to be searched according to the virtual situation in advance. Accordingly, when an object item that is not suitable for the virtual context is searched, it is possible to re-search by changing the settings for the virtual context, thereby providing a result suitable for the virtual context that the user thinks.

In addition, when the object item displayed in the result preview is determined as the final result, the travel attribute language and weight selected to recommend the result of the object item may be stored.

At this time, in the case of a user who has passed the user authentication procedure, the information providing device stores the travel attribute language and weight search information together with user log information, and the next time the same user searches the travel attribute language, the stored travel attribute language and weight information I can display it.

For example, after a user authenticated user selects'the best person' through the first attribute filter unit (I-120) and places'unique' at the front through the second attribute filter unit (I-130) , It is assumed that a search result in which the weight of'is unique' is set to 1 is stored through the weight control unit I-135. When the same user selects the'best person' through the first attribute filter unit I-120, the second attribute filter unit I-130 in which'is unique' is placed first, automatically A weight adjustment unit I-135 in which the weight is set to 1 may be provided.

17 is an example of an interface page including an attribute filter according to another embodiment of the present specification, and FIG. 18 is an example of an interface page including a weight adjustment unit I-135 according to an embodiment of the present specification to be.

The interface page (I-200) includes an item display unit (I-110), a first attribute filter unit (I-120), a second attribute filter unit (I-130), a weight control unit (I-135), and a result preview. It may include a part (I-140).

In FIG. 17, the same reference numerals as in FIG. 12 are the same components, so the repeated description will be omitted, and only the differential component weight adjusting unit I-135 will be described.

The weight adjustment unit I-135 provides a weight adjustment interface that can be adjusted by a user for each median attribute keyword displayed on the second attribute filter unit I-130. The user selects the weight of the travel attribute language accordingly.

The weight may be selected from 0.1 to 5, for example. These numbers are only examples, and are not limited thereto.

The selected weight affects the relationship between the upper attribute keyword and the medium attribute keyword corresponding to the upper attribute keyword and the intermediate attribute keyword pair. The degree of relevance affects the preview of the results and the actual results.

According to the method for personalizing a travel attribute language according to an embodiment of the present specification, it is possible to recommend an object item suitable for a virtual context considered by a user.

At this time, it will be appreciated that each block of the flowchart diagrams and combinations of the flowchart diagrams may be executed by computer program instructions. Since these computer program instructions can be mounted on the processor of a general purpose computer, special purpose computer or other programmable data processing equipment, the instructions executed by the processor of the computer or other programmable data processing equipment are described in the flowchart block(s). It creates a means to perform functions. These computer program instructions can also be stored in computer-usable or computer-readable memory that can be directed to a computer or other programmable data processing equipment to implement a function in a particular way, so that the computer-usable or computer-readable memory It is also possible to produce an article of manufacture containing instruction means for performing the functions described in the flowchart block(s). Computer program instructions can also be mounted on a computer or other programmable data processing equipment, so that a series of operating steps are performed on a computer or other programmable data processing equipment to create a computer-executable process to create a computer or other programmable data processing equipment. It is also possible for instructions to perform processing equipment to provide steps for executing the functions described in the flowchart block(s).

In addition, each block may represent a module, segment, or part of code that contains one or more executable instructions for executing the specified logical function(s). In addition, it should be noted that in some alternative execution examples, functions mentioned in blocks may occur out of order. For example, two blocks shown in succession may in fact be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order depending on the corresponding function.

In this case, the term'~ unit' used in the present embodiment refers to software or hardware components such as FPGA or ASIC, and'~ unit' performs certain roles. However,'~ part' is not 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,'~ unit' refers to components such as software components, object-oriented software components, class components and task components, processes, functions, properties, and procedures. , Subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, database, data structures, tables, arrays, and variables. The components and functions provided in the'~ units' may be combined into a smaller number of elements and'~ units', or may be further divided into additional elements and'~ units'. In addition, components and'~ units' may be implemented to play one or more CPUs in a device or a security multimedia card.

Those of ordinary skill in the art to which the present specification pertains will appreciate that the present specification may be implemented in other specific forms without changing the technical spirit or essential features thereof. Therefore, it should be understood that the embodiments described above are illustrative and non-limiting in all respects. The scope of the present specification is indicated by the scope of the claims to be described later rather than the detailed description, and all changes or modified forms derived from the meaning and scope of the claims and the concept of equivalents thereof are included in the scope of the present specification. Must be interpreted.

Meanwhile, in the present specification and drawings, preferred embodiments of the present specification have been disclosed, and although specific terms are used, these are merely used in a general meaning to easily describe the technical content of the present specification and to aid understanding of the invention. It is not intended to limit the scope of the specification. In addition to the embodiments disclosed herein, it is obvious to those of ordinary skill in the art that other modified examples based on the technical idea of the present specification may be implemented.

150: communication network 200: terminal
200-1: administrator terminal 200-2: customer terminal
210: input unit 220: display unit
230: communication unit 240: storage unit
250: control unit 300: information providing device

Claims (13)

A travel attribute language personalization method by a travel attribute language personalization device comprising a terminal and an information providing device connected to the terminal through a communication network and providing a plurality of upper attribute keywords and intermediate attribute keywords to the terminal,
When the information providing device selects a specific high-order attribute keyword from among the plurality of high-order attribute keywords through the terminal, the selected high-order attribute keyword-first high-order attribute corresponding to the middle attribute keyword pair by the information providing device Generating a median property set including a median property keyword having a degree of relationship between the first higher level property and the median property level greater than or equal to a reference value, based on the property association level;
Providing an interface for adding or deleting an intermediate attribute keyword from the intermediate attribute set together with the upper attribute keyword by the information providing device, and adding or deleting an intermediate attribute keyword from the intermediate attribute set according to a user input;
Calculating, by the information providing device, a first higher attribute keyword-object association degree corresponding to the upper attribute keyword and object pair selected based on a first intermediate attribute keyword-object association degree;
Providing, by the information providing device, an object corresponding to the first higher attribute keyword-object correlation to the interface;
An interface including the intermediate attribute set is provided to the terminal by the information providing device, and receiving a second higher attribute-median attribute association degree for each of the intermediate attribute keywords selected from the interface through the terminal;
Correcting the first higher attribute-median attribute association degree by reflecting the second higher attribute-median attribute association degree by the information providing device;
Displaying, by the information providing device, an intermediate attribute keyword of the intermediate attribute set to be distinguished from other intermediate attribute keywords; And
Displaying, by the information providing device, median attribute keywords other than the median property set according to a range to which an average similarity between the median property keywords of the median property set belongs to each other; and displaying a personalized travel property language, including: How to personalize travel attribute language to create. The method of claim 1,
The step of receiving the second high-level attribute-median attribute association degree,
Receiving a change in the arrangement order of the median property keywords included in the median property set from the interface; And
And changing the second upper attribute-median attribute association degree with a predetermined degree of association in response to the change in the arrangement order. The method of claim 1,
Prior to the step of generating the median attribute set,
Generating an upper attribute filter including a plurality of preset higher attribute keywords; And
Providing an interface including the upper attribute filter, and receiving a selection of an arbitrary higher attribute keyword from the interface; travel attribute language personalization method further comprising. The method of claim 3,
Prior to the step of generating the upper attribute filter,
Providing an interface including a plurality of preset interest items, and receiving a selection of an interest item from the interface; And
Resetting the upper attribute keyword associated with the interest item to the higher attribute keyword; Travel attribute language personalization method further comprising. The method of claim 1, prior to the step of generating the median attribute set,
The first intermediate attribute keyword-object association based on a first intermediate attribute-lower attribute association degree corresponding to an intermediate attribute keyword and a lower attribute keyword pair, and a first lower attribute-object association degree corresponding to the lower attribute keyword and object pair Storing the degree; Travel attribute language personalization method further comprising a. The method of claim 5,
The step of calculating a first higher attribute keyword-object association degree corresponding to the upper attribute keyword and the object pair may include multiplying the first higher attribute keyword-object association degree by the first higher attribute keyword-object association degree, A travel attribute language personalization method for calculating the first higher attribute keyword-object association degree corresponding to an upper attribute keyword and an object pair. A travel attribute language personalization device comprising a terminal and an information providing device connected to the terminal through a communication network and providing a plurality of high-level attribute keywords and intermediate attribute keywords to the terminal,
The information providing device,
An upper attribute keyword-a storage unit for storing a first upper attribute-median attribute association degree corresponding to the intermediate attribute keyword pair and a first intermediate attribute keyword-object association degree corresponding to the intermediate attribute keyword and object pair;
Based on the first higher attribute-median attribute association degree, a median attribute set including a median attribute keyword having the upper first attribute-median attribute association degree greater than or equal to a reference value is generated, and a median attribute together with the upper attribute keyword A control unit that provides an interface for adding or deleting an intermediate attribute keyword from the set; And
Including; a communication unit for receiving the addition or deletion of an intermediate attribute keyword to the intermediate attribute set according to a user input through the interface,
When the information providing device selects a specific high-order attribute keyword from among the plurality of high-order attribute keywords through the terminal, the information providing device includes a first corresponding to the selected high-order attribute keyword-median attribute keyword pair 1 A median attribute set including a median attribute keyword having a degree of association of the first upper property-median property greater than or equal to a reference value is generated, based on a degree of association between the upper attribute and the median attribute,
Provide an interface for adding or deleting an intermediate attribute keyword to the intermediate attribute set together with the upper attribute keyword, and adding or deleting an intermediate attribute keyword to the intermediate attribute set according to a user input,
Calculate a first high-level attribute keyword-object association degree corresponding to the selected upper attribute keyword and object pair based on the first median attribute keyword-object association degree,
Providing an object corresponding to the first high-level attribute keyword-object correlation to the interface,
Generating a high-level attribute filter including a plurality of preset high-level attribute keywords, and providing an interface including the high-level attribute filter,
Provides an interface including an attribute set, receives a second upper attribute-median attribute association degree for each of the selected intermediate attribute keywords through the interface, and reflects the input second higher attribute-median attribute association A travel attribute language personalization device for generating a personalized travel attribute language by correcting a first high-level attribute-median attribute association degree. The method of claim 7,
The interface displays a median attribute keyword of the median property set to be distinguished from other median property keywords, and a median property keyword other than the median property set according to an average similarity to the median property keywords of the median property set belongs. Travel attribute language personalization device that displays distinct from each other. The method of claim 7,
The communication unit receives a change in the arrangement order of the median property keywords included in the median property set through the interface,
The information providing device changes the second higher attribute-median attribute association degree with a predetermined degree of association in response to the change in the arrangement order. The method of claim 7,
The communication unit is a travel attribute language personalization device that receives an arbitrary high-order attribute keyword from the interface. The method of claim 10,
The information providing device provides an interface including a plurality of preset interest items, and resets a higher attribute keyword associated with the interest item input from the interface to the higher attribute keyword. The method of claim 7,
The information providing device is based on a first intermediate attribute-lower attribute association degree corresponding to an intermediate attribute keyword and a lower attribute keyword pair, and a first lower attribute-object association degree corresponding to the lower attribute keyword and object pair. Travel attribute language personalization device that calculates attribute keyword-object association. The method of claim 12,
The information providing device calculates the first higher attribute keyword-object correlation corresponding to the upper attribute keyword and the object pair by multiplying the first higher attribute-median attribute association degree by the first intermediate attribute keyword-object correlation degree Language personalization device for travel properties.

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