KR20090119383A - System and method for providing terminology resource - Google Patents

Abstract

PURPOSE: A multilingual specialized terminology resource providing system is provided to offer the search result in which the similarity is reflected to a user by expanding the specialized terminology to the multilingual environment. CONSTITUTION: A multilingual semantic network build-up device(130) generates a translation file by consulting a keyword field of the each document stored in bibliographic information database(100). When the search word is inputted, a multilingual deduction device(150) extracts the semantic network about the search word from the multilingual semantic network build-up device. The multilingual deduction device extracts the similarity between configuration keywords based on the search word and provides the relation information with the visualization information.

Description

System and Method for providing terminology resource

 The present invention relates to a system and method for providing a multilingual terminology resource. More particularly, the present invention relates to a multilingual terminology semantic network by generating a bandword file using keyword fields of a literature database, and forming individual bandword files in a triple structure according to similarity. The present invention relates to a multilingual terminology resource providing system and a method for semantic-based automatic reasoning.

With the development of information and communication technology, semantic / conceptual characteristics are interpreted based on the lexical, syntactic, and discourse meanings of various language resources to improve the efficiency of information retrieval. Various studies are being done.

Most previous researches have focused on developing systems and environments that can bridge the gap in information retrieval between users and information retrieval systems by using external language resources such as dictionaries or thesaurus. In other words, building a knowledge base so that terms can be interpreted and studying semantic interpretation techniques are important aspects of the language resource system. However, in the case of using language resources introduced from outside, it is difficult to accurately match the user's query word with the contents of the database that is actually constructed. Therefore, an applied research is needed to match the index word extracted from the literature to the conceptual word of the thesaurus. Done.

In addition, retrieval performance experiments based on language resources, including automatic classification and auto-indexing experiments, are mainly performed at the experimental level based on refined language resources due to the limitations that are difficult to perform in a large database environment.

To improve retrieval performance, it is essential to build high quality language resources suitable for each database and service. However, in order to build specialized terminology for each field, field experts need to work directly, requiring huge human resources, budget and time.

Therefore, the terminology is limited to a few specific fields, and it is difficult to construct a wide range of language resources in various fields such as the entire science and technology field. In addition, the reality is that the terminology resources that can be built and utilized in a multi-language around Hangul or Hangul is very short.

As with dictionaries and thesauruses, hand-based constructs employ a method of explicitly declaring relationships between terminology to define semantic relationships between terms. However, the conventional language resource construction method as described above may cause a problem that the semantic relationship between terms is greatly dependent on the degree of expertise of the expert, and the problem of not being able to grasp the degree of similarity between the established terminology. This can reduce the availability of language resources.

In addition, most of the experiments related to term processing have been performed based on a limited amount of resources. Therefore, when applied to an actual system, problems regarding the size and reliability of language resources remain.

 In addition, it is known that it is almost impossible to integrate language resources constructed in various fields and reconstruct them into macro resources unless the problem of integration of language resources constructed in each field is examined in advance. In addition, considering that terminology changes are frequent dynamic resources, language resources that are automatically linked should be updated when the source data is changed.

Finally, in relation to multilingual systems, most information retrieval services currently in operation operate mainly in English and native languages. In order to search for information scattered on the Internet through these search engines, You must know the correct language representation of your country for and the language supported by the browser must be present on your system. Therefore, when such a condition is not satisfied, there is a problem in that when the user searches for the corresponding word and obtains the desired information, the access itself is impossible or an additional system is required.

The present invention has been made to solve the above-mentioned problems, and can automatically infer a semantic-based similar language resource network by automatically expanding the terminology into a multilingual environment, and automatically interpret the semantic interpretation according to the semantic similarity between the terminology. The present invention provides a multilingual terminology resource providing system and method capable of performing the search and providing a search result reflecting similarity to a user who attempts a search based on a specific term.

Another object of the present invention is to provide a multilingual terminology resource providing system for forming individual band file information into a triple data structure, which is a standard technical rule of the semantic web, and enabling semantic-based automatic inference on the formed multilingual terminology network; To provide that method.

It is still another object of the present invention to provide a multilingual terminology resource providing system and method for automatically updating a semantic network of multilingual terminology by reflecting an update of a document information database in real time.

According to an aspect of the present invention in order to achieve the above object, by generating a bandword file by referring to the keyword information database, the keyword field of each document stored in the document information database, and after making the bandword file in a triple structure, each keyword A multilingual semantic network building device for generating a semantic network by connecting to a node according to the attribute information of. When a search word is input by a user, the semantic network for the search word is extracted from the multilingual semantic network building device. There is provided a multilingual terminology resource providing system including a multilingual terminology inference device that obtains a similarity between constituent keywords based on the search word and provides the relationship as visualization information to a user.

Each document is converted into Unicode and stored in the document information database.

The multilingual semantic network building device detects whether the document information database is updated in real time and regenerates the semantic network when the update is made.

The multilingual term inference device extracts a search word input by a user and a keyword having a triple structure from the multilingual semantic network building device, and connects the extracted keyword to a node according to attribute information with the search word. To generate a similarity between the keyword keywords based on the search word in the generated semantic network and provide the relationship to the user as visualization information.

According to another aspect of the present invention, in the multilingual semantic network building apparatus for building a multilingual semantic network for documents stored in a bibliographic information database, a bandword file generation unit for generating a bandword file by referring to a keyword field of the bibliographic information database; Triple structure generation unit for generating a relationship between the band words generated by the band word file generation unit in a triple structure, and a semantic network by connecting to the node of the triple structure generated by the triple structure generation unit according to the attribute information An apparatus for constructing a multilingual semantic network for providing a multilingual terminology resource comprising a semantic network generating unit and a semantic information mapping unit for generating semantic information for each keyword in the semantic network generated by the semantic network generating unit and mapping and storing the semantic information with the corresponding keyword. Is provided.

The apparatus for constructing a multilingual semantic network further includes a document information update detection unit for requesting generation of a band word file in the band word file generation unit when the document information database is updated in real time.

The apparatus for constructing a multilingual semantic network includes a band file information database for storing a band word file generated by the band word file generator, a triple data database for storing triple structure data generated by the triple structure generator, and semantic information for each keyword. It further includes a mapped semantic network information database.

The apparatus for constructing a multilingual semantic network further includes a format conversion unit for converting and storing the document information stored in the document information database into a Unicode format.

The bandword file generator generates a bandword file by extracting a multilingual keyword pair from a keyword field of the document information database.

In addition, the bandword file generator selects a bandword file having a frequency of occurrence above a predetermined threshold determined for each domain from the generated bandword file as a valid file.

The triple structure generator generates a relationship between the band keywords generated by the band word file generator using a standard description rule of the semantic web in a triple structure, and a band word relationship with different languages is given a symmetry property, and the same In the case of a language, a triple structure is created by giving a dummy property.

In addition, the triple structure generation unit assigns a unique URI to each keyword of the generated triple structure.

The semantic network generator interprets keywords having dummy properties in the relationship between the band keywords generated by the triple structure generator as the same instance and has a symmetry property around the keywords. Create semantic networks by connecting keywords.

In addition, the semantic network generating unit stores a URI that each keyword has in a keyword that has a dummy property and is interpreted as the same instance.

The semantic information mapping unit determines the classification information for each keyword of each keyword by using the URI given by the triple structure generation unit, obtains a similar vector including the occurrence frequency and weight of the corresponding keyword in the classification information, and calculates a similar vector. Map and save.

According to another aspect of the present invention, in a multilingual terminology inference apparatus that provides information on a search query queried by a user, when the search term is input by the user, the search term is extracted from a database of the multilingual semantic network building apparatus. A search term extracting unit, a semantic network information extracting unit for extracting a semantic network in which a node having a related property is set from the database, and a semantic network extracted by the semantic network information extracting unit based on the search terms A multi-language terminology resource providing unit comprising a similarity measurer measuring a similarity between the two and a similarity measured by the similarity measurer and generating a visualization information displayed on a node in the semantic network and providing the same to the user. A terminology inference device is provided.

According to another aspect of the present invention, in a multilingual terminology inference apparatus providing information on a search term queried by a user, when the search term is input by the user, extracting the search term from a database of the multilingual semantic network construction device. A search word extracting unit, a triple structure information extracting unit extracting keywords connected to the search word in a triple structure from the database, and generating a semantic network by connecting related nodes based on the attribute information based on the extracted triple structure keyword And a semantic network information generating unit for generating semantic information for each keyword in the semantic network generated and mapping the semantic information to the corresponding keyword, and measuring similarity between nodes based on the search terms in the semantic network generated by the semantic network information generating unit. Similarity measuring unit to measure, the similarity measuring unit The multilingual terminology inference device for providing a multilingual terminology resource includes a visualization information generation unit configured to calculate location information of each node in the semantic network according to the similarity, and provide the generated visualization information to a user. Is provided.

The similarity measurer calculates similarity with a keyword in each node based on the search word.

The visualization information generator generates visualization information having an optimal semantic network using the similarity value between keywords measured by the similarity measurer and provides the same to the user.

The visualization information includes a semantic network and a similar threshold control key. When the threshold is adjusted using the pseudo threshold control key, the visualization information control unit controls the size of the semantic network based on the corresponding threshold.

According to another aspect of the present invention, in the multilingual semantic network building apparatus to build a multilingual semantic network using the documents stored in the bibliographic information database, (a) using the reference field in the bibliographic information database with reference to the keyword language file (B) generating the relationship between the generated band words in a triple structure; and (c) a keyword having a dummy property in the relationship between the generated band words in the triple structure is the same instance. Generating a semantic network by connecting keywords having a symmetry property around the keyword, and (d) generating semantic information of each keyword in the generated semantic network and mapping and storing the semantic information. A multilingual semantic network construction method for providing a multilingual terminology resource including a step is provided.

When the update of the document information database is detected, a method for constructing a multilingual semantic network for providing a multilingual terminology resource further comprising the step (a) to (d).

Step (a) is a step of extracting a keyword from a keyword field of each document stored in the document information database. When the extracted keyword is composed of two or more languages, the extracted keyword is mutually matched to generate a band word file. It includes a step.

In the step (b), a bandword file having a different language is given a symmetry property, and a bandword file having a same language is given a dummy property using a standard description rule of the semantic web. Create

In the step (d), the classification information is determined using URIs assigned to each keyword in the triple structure, and the similarity vector including occurrence frequency and weight of the corresponding keyword is obtained from the determined classification information and mapped to each keyword. To store.

According to another aspect of the present invention, in the multi-lingual term inference device to search for a query input by the user, (a) if a search word is input by the user, a keyword having a similarity with the search term is entered from the database; Extracting an included semantic network, (b) measuring similarity between each node based on the search word in the extracted semantic network, and (c) obtaining location information of each node in the semantic network according to the measured similarity. A multilingual terminology inference method for providing a multilingual terminology resource comprising calculating and generating visualization information and providing the generated visualization information to a user is provided.

According to another aspect of the present invention, in the multilingual terminology inference device to search for a query input by the user, (a) if a search word is input by the user, the database is searched to generate the search term and triple structure Extracting the generated band words, (b) generating a semantic network using the attribute information with the search word for the extracted band words, and (c) generating semantic information of each keyword in the generated semantic networks. Mapping to and (d) measuring similarity between each keyword based on the search word in the generated semantic network, and (e) calculating position information of each node in the semantic network according to the measured similarity. Generating visualization information, and providing the generated visualization information to the user multilingual for providing a multilingual terminology resource Terminology reasoning methods are provided.

In the step (b), a band word having the search word and a dummy property among the extracted band words is interpreted as an instance, and a band word having a symmetry property is connected around the search word. To create a semantic network.

In the step (c), the classification information for each domain of each keyword is determined, and a similar vector including the occurrence frequency and weight of the keyword in the classification information is obtained and mapped to each keyword.

According to the present invention, since the multi-band terminology semantic network is automatically built by clustering individual band file information automatically extracted from the literature database according to similarity, the language resource is more reliable and the language resource reflecting all the various fields can be selected. A multilingual terminology resource providing system and a method for automatically updating the semantic network of multilingual terminology can be provided by reflecting the change of information in a real database in real time.

In addition, it is possible to automatically infer a semantic-based similar language resource network by automatically expanding the terminology into a multilingual environment, automatically perform the semantic interpretation based on the semantic similarity between the terminology, and search based on a specific term. A multilingual terminology resource providing system and method capable of providing search results reflecting similarities to an attempted user may be provided.

Details of the above-described objects and technical configurations of the present invention and the effects thereof according to the present invention will be more clearly understood by the following detailed description based on the accompanying drawings.

1 is a view showing the configuration of a multi-lingual terminology resource providing system according to the present invention.

Referring to FIG. 1, the multilingual terminology resource providing system includes a document information database 100, a multilingual semantic network construction device 130, and a multilingual terminology inference device 150.

The bibliographic information database 100 stores bibliographic information on specialized fields such as domestic and international academic papers, patents, and research reports. The document information of the document information database 100 is converted into Unicode and stored. For example, the Korean code (KSC5601) is converted to UFT-8, the Japanese code (Shift-JIS) is converted to UFT-8, and the Simplified Chinese code (GB2312) is converted to UTF-8 in real time.

The apparatus for constructing a multilingual semantic network 130 generates a bandword file by referring to a keyword field of each document stored in the document information database 100, makes the bandword file into a triple structure, and then displays property information between nodes. Create semantic network by connecting nodes according to

In addition, the apparatus for constructing a multilingual semantic network 130 detects whether the document information database 100 is updated in real time and plays a role of regenerating the semantic network when the document information is updated.

A detailed description of the apparatus for constructing a multilingual semantic network 130 performing the above role will be given with reference to FIG. 2.

The multilingual terminology deduction device 150 extracts a semantic network for the search word from the multilingual semantic network building device 130 when a search word is input by the user 170, and based on the search word in the extracted semantic network. The similarity between the keywords is calculated, and the relationship is generated as visualization information and provided to the user 170.

In addition, the multilingual terminology deduction device 150 searches for a database of the multilingual semantic network building device 130 when a user inputs a search word, extracts keyword information in which the search word and triple structure are generated, and extracts the search word. The semantic network is generated by connecting the generated keywords to nodes according to the similarity with the search word. Then, the multilingual terminology deduction device 150 obtains the similarity between the configuration nodes based on the search word in the generated semantic network and provides the relationship as visualization information to the user.

A detailed description of the multilingual terminology inference apparatus 150 that performs the above role will be described with reference to FIGS. 5 and 6.

FIG. 2 is a block diagram schematically illustrating a configuration of an apparatus for constructing a multilingual semantic network according to the present invention, FIG. 3 is an exemplary diagram of a triple structure generated by the triple structure generation unit shown in FIG. 2, and FIG. 4 is a meaning illustrated in FIG. 2. An example diagram of a semantic network generated by the network generator.

Referring to FIG. 2, the apparatus for constructing a multilingual semantic network 130 may include a bibliographic information update detector 132, a bandword file generator 134 for generating a bandword file with reference to a keyword field of a bibliographic information database, and the bandword file generation. Triple structure generation unit 136 for generating the relationship between the band words generated in the unit 134 in a triple structure, and connected to the node according to the attribute information for the triple structure band words generated in the triple structure generation unit 136 means Semantic network generation unit 138 for generating a network, semantic information mapping unit 140 for generating semantic information for each keyword in the semantic network generated by the semantic network generating unit 138 and mapping and storing the semantic information with the corresponding keyword, database 142.

The document information update detecting unit 132 detects whether the document information database is updated in real time and requests the band word file generation unit 134 to generate the band word file when it is updated.

The bandword file generator 134 may refer to a keyword field of the bibliographic information database when a bandword file generation request is received from the bibliographic information update detector 132 or when a multilingual semantic network is first constructed. Create

That is, the bandword file generator 134 extracts a multilingual keyword pair from a keyword field of the document information database to generate a bandword file, and stores and assigns a URI (Uniform Resource Identifier) to each bandword file.

The bandword file generator 134 extracts a keyword from a keyword field of each document, and performs matching between band keywords when the extracted keyword is in two or more languages.

When the keyword fields in the bibliographic database are each divided into two languages, a band file is generated by mutual matching between keywords extracted from the two fields. If the band pair is not generated correctly, the matching process is invalidated.

When two or more languages are included in one keyword field in the literature database, first, the total number of keywords in the keyword field is obtained. If the number of keywords is an even number, the bandword file generator 134 divides the extracted keyword into two parts and automatically recognizes a language code so that the language structure of the two parts is different (for example, the first part is Korean, The latter part is in English), and the keyword of the first part and the keyword of the latter part are matched to generate keyword pairs to generate a keyword word file.

In this case, for example, in the keyword field 'resolve the word neutrality; Automatic tagging; Semantic classification; Pre-extraction information based tagging; Salmon air based tagging; word sense disambiguation; automatic tagging; sense classification; dictionary Information-based tagging; A case where collocation co-occurrence-based tagging 'is extracted will be described.

Since the extracted number of keywords is an even number, dividing it into two parts extracts 5 pairs. As a result of measuring the language code, the first five keywords are all Korean and the last five keywords are English.

In other words, the previous five Hangul keywords' word neutralization resolution; Automatic tagging; Semantic classification; Pre-extraction information based tagging; Salmon air based tagging and five English keywords behind 'word sense disambiguation; automatic tagging; sense classification; dictionary Information-based tagging; match collocation co-occurrence-based tagging '.

Then, 'word sense disambiguation', 'auto tagging = automatic tagging', 'meaning classification = sense classification', 'dictionary information-based tagging = dictionary information-based tagging', 'salmon air-based tagging = collocation A bandword file of co-occurrence-based tagging 'is created.

In addition, since the English keyword may be included in the Korean keyword portion, in this case, the bandword file generator 134 verifies whether the English keywords of the two portions match, and if it does not match, invalidates the matching process performed until the previous word file. Does not generate

In addition, the bandword file generator 134 selects only the bandword file having a frequency of occurrence above a predetermined threshold determined for each domain in the generated bandword file as a valid file to provide reliability of the extracted bandfile. For example, in the case of domestic journals, the threshold value of the 'Hangul-English' band file is set to 3 to generate only the data having the same pattern repeated three times or more, and in the case of Chinese journals, considering the quality problem The threshold value of the 'Chinese-English' band file is set to 10 to generate only the data having the same pattern repeated 10 times or more as triple data.

The triple structure generator 136 generates a relationship between the band words generated by the band word file generator 134 in a triple structure by using standard semantic rules of the semantic web, but a band word relationship having different languages is a symmetry property. ) And 'hss Synonym', and in case of the same language (same string value), 'has Dummy' is granted to create a triple structure.

In addition, the triple structure generation unit 136 assigns a unique URI to each keyword of the triple structure. The URI may be in the form of 'domain name.term' or 'domain name.term ID value', and the domain name may be a name or an alias of a unique database table from which the terminology is extracted.

The triple structure generated by the triple structure generator 136 for 'ship' will be described with reference to FIG. 3.

When the first, second, and third SHIPs have different URIs and the bandwords for each are stored as ship, ship, and ship, the first SHIP and ship, the second SHIP and ship, and the third SHIP and ship are symmetric, respectively. Since the property (Symmetry Property) is given, and the first, second, and third SHIP have the same string value, a dummy property is given to generate a triple structure as shown in FIG. 3.

  Here, the symmetric attribute refers to the declaration of synonyms (synonyms) between the terminology, and the dummy attribute refers to the same term.

The semantic network generating unit 138 interprets keywords having a dummy property in the relationship between the band keywords generated by the triple structure generating unit 136 as the same instance and is symmetric about the keywords. A semantic network is created by concatenating keywords having a property.

When the semantic network generating unit 138 generates the semantic network using the triple structure as shown in FIG. 3, the semantic network as shown in FIG. 4 is generated.

Referring to FIG. 4, a vessel, a ship, and a ship are connected to one 'SHIP' to create a semantic network. At this time, all URIs assigned to the first, second, and third SHIP are mapped to 'SHIP'.

The semantic information mapping unit 140 determines classification information for each keyword of each keyword by using the URI given by the triple structure generation unit 136, and includes occurrence frequency and weight of the corresponding keyword in the classification information. Obtain a similar vector, map it with each keyword, and save it.

The method of obtaining weighted similar vector for each subject field of each keyword is to measure the frequency of occurrence of various classification codes for the corresponding keyword and the frequency of occurrence of the classification code generated for keywords other than the corresponding keyword, and then measure the frequency information for various similarities. It can be calculated by applying it to the coefficient.

The similarity measures used here include Jaccard coefficients, Cosine coefficients with high frequency preference, and Log-odds ratios with low frequency preference. Various amounts of information may be applied.

In addition, in order to normalize the measured similar weights, TF * logIDF multiplied by term frequency (TF) and inverse document frequency (IDF) may be used as in Equation 1.

Here, W (t) is the weight of the occurrence term t in the literature, N is the total number of documents, TF is the term frequency and DF is the document frequency.

Similar vectors between the terminology-topics calculated by the above method are stored in the form of SHIP = {machine: 0.7, construction: 0.3} and mapped to the keywords of the semantic network. 'SHIP = {machine: 0.7, construction: 0.3}' means that SHIP has a similarity weight of 0.7 in the mechanical field and 0.3 similarity weight in the construction field.

The database 142 may include a bandword file information database 142a for storing the bandword file generated by the bandword file generator 134 and a triple data database for storing triple structure data generated by the triple structure generator 136. In operation 142b, the semantic information mapping unit 140 includes a semantic network information database 142c to which each keyword and similar vector value are mapped.

FIG. 5 is a block diagram schematically illustrating a configuration of an apparatus for multilingual terminology according to the present invention. FIG. 7 is an exemplary view showing visualization information generated by a visualization information generating unit according to the present invention and provided to a user. FIG. Is an exemplary view showing a network change before applying a similarity threshold and after applying a similarity threshold to a search word input by a user according to the present invention.

Referring to FIG. 5, when a search term is input by a user, the multilingual terminology deriving apparatus 150 may search for a search term extractor 152 that extracts the search term from a database of a multilingual semantic network building device. A semantic network information extractor 154 for extracting a semantic network including a set keyword, and a similarity measurer for measuring similarity between nodes based on the search word in the semantic network extracted by the semantic network information extractor 154. 156, and a visualization information generator 158 that displays the similarity measured by the similarity measurer 156 to a node in the semantic network and provides visualization information to the user.

The similarity measurer 156 calculates the similarity with the keyword in each node based on the search word or the similarity based on the search word in the extracted semantic network.

The similarity measurer 156 may use the similarity measure and the distance measure to calculate the similarity between keyword vectors. The similarity measurement between two keyword vectors measures frequency of occurrence of classification code information common to both keywords, classification code information that occurs only on one side, and classification code information that does not appear on either keyword. It can be calculated by applying. In this case, various measurement methods such as Euclidean distance coefficient, Pearson correlation coefficient, and cosine coefficient may be used. Equation 2 below is an example of the cosine similar coefficient formula.

The visualization information generator 158 displays visualization information displayed on each keyword extracted by the semantic network information extractor 154 according to the semantic similarity measured by the similarity measurer 156 with respect to a search word input by a user. Is generated and displayed as shown in FIG.

Referring to FIG. 7 for a visualization information providing screen provided to a user, the visualization information providing screen 700 includes a semantic network information providing region 702 and a similarity threshold adjusting region 704 in which nodes are set by mapping similarities to respective keywords. It consists of. The similarity information providing area 702 indicates similarity between subject fields and similarity between keywords for each keyword.

The similarity between the search term and the network may be dynamically adjusted by using the threshold adjustment keys in the similarity threshold adjustment region 704 to dynamically change the entire semantic network, to check the optimal term cluster change in real time, and to check the quality of the data. I can regulate it.

A network change when the threshold is adjusted using the similarity threshold adjustment key will be described with reference to FIG. 8.

Referring to FIG. 8, when the similarity threshold is 0 (800a), the keyword and network overall similarity is 0.519, but the similarity threshold is continuously increased to increase the similarity between the keyword and the network as a whole at 0.7 similar threshold 800b to 0.981. Create an optimal network that is semantically similar.

As described above, the network change after applying the similarity threshold and after applying the similarity threshold can be confirmed in real time using the similarity threshold adjusting key for the keyword searched by the user.

6 is a block diagram schematically illustrating a configuration of a multilingual terminology inference apparatus according to another embodiment of the present invention.

Referring to FIG. 6, when a search word is input by a user, the multilingual terminology deduction device 150 generates a search word extractor 152 that extracts the search word from a database of a multilingual semantic network building device, and generates the search word and a triple structure. Triple structure information extraction unit 153 for extracting the extracted keyword information, the semantic network is generated by connecting the extracted triple structure keywords to nodes according to similarity, and generating semantic information for each keyword in the generated semantic network The semantic network information generation unit 155 to map the keyword to the corresponding keyword, and the similarity measurement unit 156 measuring the similarity between nodes based on the search word in the semantic network generated by the semantic network information generation unit 155. The similarity measurer 156 displays the similarity to the nodes in the semantic network to generate visualization information for providing visualization information to the user. And a 158. The

The semantic network information generating unit 155 determines classification information for each keyword of each keyword by using URIs assigned to each keyword in the triple structure, and includes similarity including occurrence frequency and weight of the corresponding keyword in the classification information. Obtain a vector, map it with each keyword, and save it.

In this case, when the multilingual semantic network building device does not construct a semantic network for each keyword generated in a triple structure, the multilingual terminology inference device constructs the semantic network in real time with respect to the corresponding search word and provides the result to the user. can do.

9 is a flowchart illustrating a method for constructing a multilingual semantic network using a document stored in a bibliographic information database according to the present invention.

Referring to FIG. 9, if an update is detected in real time by detecting whether the document information database is updated in real time (S900), the multilingual semantic network building apparatus generates a band word file with reference to a keyword field of the corresponding document information (S902).

That is, the apparatus for constructing a multilingual semantic network extracts a keyword from a keyword field of each document stored in a document information database, and generates a band word file by performing mutual matching between band keywords when the extracted keyword is in two or more languages. .

A detailed description of the multilingual semantic network building apparatus generating the bandword file will be omitted since it has been described with reference to FIG. 2.

Then, the apparatus for constructing a multilingual semantic network makes the relationship between the generated band words in a triple structure (S904). That is, the apparatus for constructing a multilingual semantic network grants a symmetry property to a bandword file having a different language according to the standard technical rules of the semantic web, and a dummy property to a term having the same string. Create a triple structure. In this case, the apparatus for constructing a multilingual semantic network assigns a unique URI to each keyword generated in the triple structure.

Then, the apparatus for constructing a multilingual semantic network interprets a keyword having a dummy property as the same instance in the relationship between the generated triplet band words, and generates a symmetry property around the keyword. Branch to generate a semantic network by connecting the keywords (S906).

Thereafter, the apparatus for constructing a multilingual semantic network determines classification information for each keyword of each keyword using URIs assigned to each keyword, and obtains a similar vector including occurrence frequency and weight of each keyword in the classification information. Map and store the keyword (S908).

According to another embodiment of the present invention, the apparatus for constructing a multilingual semantic network may perform only up to S904 without performing S906 and S908. In this case, when a user inputs a search word, the multilingual terminology inference device performs a process of generating a semantic network for the corresponding search word in real time.

10 is a flowchart illustrating a method of searching for a query input by a user by a multilingual terminology inference apparatus according to the present invention.

Referring to FIG. 10, when a search term is input by a user (S1000), the multilingual terminology inference apparatus extracts a semantic network including a keyword having similarity to the search term from a database of a multilingual semantic network building apparatus (S1002). .

Then, the multilingual search apparatus measures similarity between each node based on the search word in the extracted semantic network (S1004), and displays the measured similarity to nodes in the semantic network and provides the same to the user (S1006). .

The user may dynamically change the entire semantic network by adjusting the similarity between the search word and the network, identify an optimal term cluster change in real time, and adjust the quality of data.

11 is a flowchart illustrating a method of searching for a query input by a user by a multilingual terminology inference apparatus according to another exemplary embodiment of the present invention.

Referring to FIG. 11, when a search term is input by a user (S1100), the multilingual terminology inference apparatus searches a database of a multilingual semantic network construction apparatus and extracts keyword information in which the search term and triple structure are generated (S1102).

Then, the multilingual term inference apparatus interprets keywords having dummy properties in the relationship between the extracted triplet band words as the same instance, and calculates a symmetry property around the keywords. Branches connect the keywords to generate a semantic network (S1104).

Then, the multilingual term inference apparatus determines classification information for each keyword of each keyword, obtains a similar vector including an occurrence frequency and a weight of the corresponding keyword in the classification information, and maps it to each keyword (S1106).

Then, the multilingual term inference device obtains the similarity between each node based on the search word in the semantic network to which the similar vector is mapped (S1108), and displays the obtained similarity to the nodes in the semantic network and provides the same to the user. (S1110).

As such, those skilled in the art will appreciate that the present invention can be implemented in other specific forms without changing the technical spirit or essential features thereof. Therefore, the above-described embodiments are to be understood as illustrative in all respects and not as restrictive. The scope of the present invention is shown by the following claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included in the scope of the present invention. do.

1 is a view showing the configuration of a multi-lingual terminology resource providing system according to the present invention.

Figure 2 is a block diagram schematically showing the configuration of a multilingual semantic network building apparatus according to the present invention.

3 is an exemplary view of a triple structure generated by the triple structure generating unit shown in FIG. 2;

4 is an exemplary diagram of a semantic network generated by the semantic network generating unit shown in FIG. 2;

5 and 6 are block diagrams schematically showing the configuration of a multilingual terminology inference apparatus according to the present invention.

7 is an exemplary screen illustrating visualization information generated by a visualization information generating unit according to the present invention and provided to a user.

8 illustrates an example of a network change before and after applying a similarity threshold to a search word input by a user according to the present invention.

9 is a flowchart illustrating a method for constructing a multilingual semantic network by using a document stored in a bibliographic information database, according to the present invention.

10 and 11 are flowcharts illustrating a method for retrieving a query input by a user by a multilingual terminology inference apparatus according to the present invention;

<Explanation of symbols for the main parts of the drawings>

100: literature information database 130: multilingual semantic network construction device

132: document information update detection unit 134: band word file generation unit

136: triple structure generator 138: semantic network generator

140: semantic information mapping unit 142: database

150: multilingual terminology inference device 152: search term extraction unit

153: triple structure information extractor 154: semantic network information extractor

155: semantic network information generation unit 156: similarity measurement unit

158: visualization information generation unit 170: user terminal

Claims (29)

Bibliographic information database; Multi-language semantic network building apparatus generating a word-language file by referring to the keyword field of each document stored in the document information database, making the word-language file into a triple structure, and connecting to nodes according to attribute information of each keyword to generate a semantic network. ; And  When a search word is input by a user, a semantic network for the search term is extracted from the multilingual semantic network building device, the similarity between components of the extracted semantic network is calculated based on the search word, and the relationship is provided to the user as visualization information. Multilingual terminology inference apparatus; Multilingual terminology resource providing system comprising a. The method of claim 1, The bilingual terminology resource providing system, wherein each document is converted into Unicode and stored in the bibliographic information database. The method of claim 1, The multilingual semantic network construction apparatus detects whether the document information database is updated in real time and, when updated, regenerates the semantic network. The method of claim 1, The multilingual term inference device extracts a search word input by a user and a keyword having a triple structure from the multilingual semantic network building device, and connects the extracted keyword to a node according to attribute information with the search word. The multi-lingual terminology resource providing system, characterized in that for generating a similarity between the keywords constituting the keyword based on the search word in the generated semantic network and providing the relationship to the user as visualization information. In the multilingual semantic network construction device for building a multilingual semantic network for documents stored in a document information database, A bandword file generation unit generating a bandword file by referring to a keyword field of the document information database; A triple structure generator for generating a relationship between the band words generated by the band word file generator in a triple structure; A semantic network generator for generating a semantic network by connecting to a node according to attribute information with respect to the keyword of the triple structure generated by the triple structure generator; and A semantic information mapping unit for generating semantic information for each keyword in the semantic network generated by the semantic network generating unit and mapping the semantic information with the corresponding keyword and storing the semantic information; Multilingual semantic network building device for providing a multilingual terminology resource comprising a. The method of claim 5, And a document information update detection unit for requesting generation of a band word file in the band word file generation unit when the document information database is updated in real time. The method of claim 5, A band file information database for storing the band word file generated by the band word file generator, a triple data database for storing triple structure data generated by the triple structure generator, and a semantic network information database to which semantic information is mapped for each keyword; Multilingual semantic network construction apparatus for providing a multilingual terminology resource further comprising. The method of claim 5, And a format conversion unit for converting and storing the document information stored in the document information database into a Unicode format. The method of claim 5, The band word file generator extracts a multi-language keyword pair from a keyword field of the bibliographic information database to generate a band word file. The method of claim 5, The bandword file generator is a multilingual semantic network construction apparatus for providing a multilingual terminology resource, characterized in that for selecting the bandword file having a frequency of occurrence more than a predetermined threshold determined for each domain in the generated bandword file. The method of claim 5, The triple structure generator generates a relationship between the band keywords generated by the band word file generator using a standard description rule of the semantic web in a triple structure, and a band word relationship with different languages is given a symmetry property, and the same In the case of a language, a multilingual semantic network constructing apparatus for providing a multilingual terminology resource, wherein a triple structure is generated by giving a dummy property. The method of claim 5, The triple structure generator is a multi-lingual semantic network for providing a multi-lingual terminology resource, characterized in that to assign a unique URI to each keyword of the generated triple structure. The method of claim 5, The semantic network generator interprets keywords having dummy properties in the relationship between the band keywords generated by the triple structure generator as the same instance and has a symmetry property around the keywords. An apparatus for constructing a multilingual semantic network for providing a multilingual terminology resource that connects keywords to generate a semantic network. The method of claim 13, The semantic network generating unit, a multilingual semantic network construction apparatus for providing a multilingual terminology resource, characterized in that the keyword that has a dummy property (Dummy Property) is interpreted as the same instance (s) stored together with the URI that each keyword has . The method of claim 5, The semantic information mapping unit determines the classification information for each keyword of each keyword by using the URI given by the triple structure generation unit, obtains a similar vector including the occurrence frequency and weight of the corresponding keyword in the classification information, and calculates a similar vector. Multilingual semantic network construction apparatus for providing multilingual terminology resources, characterized in that the mapping and storing. In the multilingual terminology inference device that provides information about a search query queried by a user, A search word extracting unit extracting the search word from a database of a multilingual semantic network building device when a search word is input by a user; A semantic network information extracting unit for extracting a semantic network in which a node having a property related to the search word is set from the database; A similarity measurement unit for measuring similarity between nodes in the semantic network extracted by the semantic network information extractor based on the search word; and A visualization information generator configured to generate visualization information displayed on the nodes in the semantic network measured by the similarity measurer and provide the same to the user; Multilingual terminology inference device for providing a multilingual terminology resource comprising a. In the multilingual terminology inference device that provides information about a search query queried by a user, A search word extracting unit extracting the search word from a database of a multilingual semantic network building device when a search word is input by a user; A triple structure information extracting unit which extracts keywords connected to the search word in a triple structure from the database; Semantic network information for generating the semantic network by connecting the extracted triple-structured keyword to relevant nodes according to the attribute information based on the search word, and generating semantic information for each keyword in the semantic network. Generation unit; A similarity measurer for measuring similarity between nodes in the semantic network generated by the semantic network information generator based on the search word; and A visualization information generation unit configured to generate visualization information by calculating position information of each node in the semantic network according to the similarity measured by the similarity measurement unit, and providing the generated visualization information to a user; Multilingual terminology inference device for providing a multilingual terminology resource comprising a. The method according to claim 16 or 17, The similarity measurer calculates a similarity with the keyword in each node based on the search word multilingual terminology inference device for providing a multilingual terminology resource, characterized in that. The method according to claim 16 or 17, The visualization information generation unit generates visualization information having an optimal semantic network by using similarity values between keywords measured by the similarity measurer and provides the user with multilingual terminology for providing a multilingual terminology resource. Device. The method according to claim 16 or 17, The visualization information includes a semantic network and a similar threshold control key, The visualization information generation unit, if the threshold is adjusted using the similar threshold control key, multilingual terminology inference device for providing a multilingual terminology resource, characterized in that for controlling the size of the semantic network based on the threshold. In the method of building a multilingual semantic network using a document stored in a bibliographic information database, (a) generating a bandword file by referring to a keyword field of the document information database; (b) generating a relationship between the generated band words in a triple structure; (c) A keyword having a dummy property in the generated triple-structured band word is interpreted as an instance, and a keyword having a symmetry property is connected to the keyword to mean it. Creating a network; and (d) generating semantic information of each keyword in the generated semantic network and mapping and storing the semantic information with the corresponding keyword; Multilingual semantic network construction method for providing a multilingual terminology resource comprising a. The method of claim 21, If the update of the document information database is detected, the multi-lingual semantic network for providing a multi-lingual terminology resource further comprising the step of (a) to (d). The method of claim 21, In step (a), Extracting a keyword from a keyword field of each document stored in the document information database; If the extracted keywords are composed of two or more languages, multi-language semantic network construction method for providing a multi-lingual terminology resource, comprising the step of generating a band-word file by mutually matching the extracted keywords. The method of claim 21, In step (b), Using a standard description rule of the semantic web, a band word file having a different language gives a symmetry property, and a band word file having a same language gives a dummy property to generate a triple structure. How to build a multilingual semantic network to provide multilingual terminology resources. The method of claim 21, In step (d), Determining classification information using URIs assigned to respective keywords in the triple structure; Obtaining a similar vector including the occurrence frequency and weight of the corresponding keyword from the determined classification information, and mapping and storing the similar vector with each keyword, the multilingual semantic network for providing a multilingual terminology resource. In the multi-lingual term inference device to search for a query input by the user, (a) extracting a semantic network including keywords having similarity with the search word from a database when a search word is input by a user; (b) measuring similarity between nodes in the extracted semantic network based on the search word; and (c) generating visualization information by calculating position information of each node in the semantic network according to the measured similarity, and providing the generated visualization information to a user; Multilingual terminology inference method for providing a multilingual terminology resource comprising a. In the multi-lingual term inference device to search for a query input by the user, (a) if a search word is input by a user, searching a database and extracting a band word in which the search word and the triple structure are generated; (b) generating a semantic network with respect to the extracted band word using attribute information with the search word; (c) generating semantic information of each keyword in the generated semantic network and mapping the semantic information with the corresponding keyword; (d) measuring similarity between each keyword based on the search word in the generated semantic network; and (e) calculating location information of each node in the semantic network according to the measured measured similarity, generating visualization information, and providing the generated visualization information to a user; Multilingual terminology inference method for providing a multilingual terminology resource comprising a. The method of claim 27, In the step (b), a band word having the search word and a dummy property among the extracted band words is interpreted as an instance, and a band word having a symmetry property is connected around the search word. Multilingual terminology inference method for providing a multilingual terminology resource, characterized in that to generate a semantic network. The method of claim 27, In the step (c), the classification information for each keyword of each keyword is determined, and a similar vector including the occurrence frequency and weight of the corresponding keyword in the classification information is obtained and mapped to each keyword. Multilingual Terminology Reasoning Method for Provisioning.

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