Abstract:
A method of evaluating a value of reference information and an apparatus for evaluating a value of reference information are disclosed. According to an embodiment of the present invention, the method includes calculating similarity values of reference relationships between the subject document and each of neighbor documents, respectively, and summing the calculated similarity values to calculate a first sum, multiplying each of the similarity values of reference relationships between the subject document and each of the neighbor documents by a corresponding value of reference information of the first reference document for each of the neighbor documents, and summing the multiplied values to calculate a second sum, and evaluating a value of reference information using a ratio of the first and second sums.
Abstract:
A method for providing information about a main knowledge stream is disclosed. According to an embodiment of the present invention, the method includes obtaining reference links representing reference relationships among reference documents in each of a plurality of documents stored in a database, determining one or more basic paths connecting the reference links, calculating probability values of the reference links by overlapping the determined basic paths, determining a first document among the documents and an input reference link associated with the first document, and performing a Markov chain model using a probability value of the input reference link, and calculating information about the main knowledge stream associated with the first document using the result obtained by performing the Markov chain model.
Abstract:
The present invention relates to an apparatus and method for determining a stage using a technology lifecycle, and the stage determination apparatus including a storage and a processor comprises: a bibliographic database for integrating heterogeneous resources; a feature set creation module for calculating feature values of predefined features by searching the bibliographic database, and creating a feature set of each technology using the calculated feature values, for technologies positioned on a technology lifecycle; an answer feature set creation module for calculating a common feature value of feature sets of technologies belonging to the same stage in the technology lifecycle and creating an answer feature set of each stage; a stage determination module for, if a specific technology is inputted, acquiring feature values and creating a feature set for predefined features by searching the bibliographic database for the specific technology, comparing a corresponding feature value contained in the feature set of the specific technology with a feature value according to a feature selection flow set in a previously constructed decision tree according to the feature selection flow set in the decision tree, and determining a stage having a feature value finally selected according to the feature selection flow of the decision tree as a stage where the specific technology belongs to in the technology lifecycle. Therefore, according to the present invention, although a specific technology does not exist in the technology lifecycle, a stage where the specific technology lifecycle belongs to in the technology lifecycle can be determined using various kinds of bibliographic databases.
Abstract:
The present invention relates to an apparatus and method for visualizing technology transition, and the technology transition visualization apparatus including a storage and a processor comprises: a bibliographic database for integrating heterogeneous resources; a technology information database for storing information on a representative stage, a current stage, a next stage, and a year-specific stage included in a technology lifecycle of each technology; an interface module for receiving a specific technology from a user; a feature set creation module for calculating feature values of predefined features by searching the bibliographic database and creating a feature set for each technology using the calculated feature values, for technologies positioned on a technology lifecycle; an answer feature set creation module for calculating a common feature value of feature sets of technologies belonging to the same stage in the technology lifecycle and creating an answer feature set of each stage; a stage determination module for, if a specific technology is inputted through the interface module, acquiring feature-related information for the specific technology by searching the bibliographic database, creating a representative feature set and a year-specific feature set of the specific technology using the acquired feature-related information, determining a representative stage or a year-specific stage where the specific technology belongs to in the technology lifecycle by comparing the representative feature set or the year-specific feature set with the answer feature set, and estimating development speed of the specific technology using the year-specific stage; a visualization module for visualizing the technology lifecycle which shows the representative stage of the specific technology; and a year-specific stage acquisition module for, if the specific technology is selected from the visualized technology lifecycle, acquiring a current stage, a year-specific stage and an estimated next stage of the specific technology from the technology information database and visualizing the acquired stages through the visualization module. Therefore, according to the present invention, development speed of a specific technology in the future, as well as a current stage and a year-specific stage of the technology in a technology lifecycle, can be estimated using various kinds of bibliographic databases.
Abstract:
The present invention relates to a framework for the semi-automatic construction of test collections used in extracting relationships between technical terms, and provides a framework for the semi-automatic construction of test collections used in extracting relationships between technical terms, wherein a practical test collection is constructed by systematically processing technical terms present in texts and associative relationships between the same on the basis of a language resource, and by going beyond the existing approach for constructing small-scale test collections based on limited texts and objects and instead making effective use of a large-scale academic database, and of specialist dictionaries in various fields and up-to-date machine-learning algorithms. The present invention provides the advantages that efforts on the part of constructors can be minimised and variations in results which occur due to the dispositions of constructors can be reduced by automating tasks which are standardised and time-consuming.
Abstract:
The present invention relates to an efficient reasoning system and method using a view in a DBMS-based RDF triple store. The DBMS-based reasoning system includes a triple input unit (110) for receiving a Resource Description Framework (RDF) triple. A triple examination unit (120) examines whether the received triple conforms to RDFS subsumption relation entailment rules or Web Ontology Language (OWL) inverse relation rules. A view creation unit (140) creates a table view when the received triple conforms to the RDFS subsumption relation entailment rules or the OWL inverse relation rules as a result of the examination. A triple storage unit (130) stores the received triple. The DBMS-based triple store can efficiently perform reasoning based on rule rdfs7 or rdfs9, which is included in the RDFS subsumption relation entailment rules, and the OWL inverse relation rules.
Abstract:
A system and method for hybrid Rete reasoning based on memory and DBMS are disclosed. The system for hybrid Rete reasoning based on memory and DBMS includes a reasoning rule type classification means (120) for classifying an input reasoning rule as one of one or more types. A network generation means (130) generates a network depending on the classified reasoning rule type. A network execution means (140) derives extended triples by applying a predetermined triple to the generated network.
Abstract:
Disclosed herein is a multi -entity-centric integrated search system and method. The multi-entity-centric integrated search system includes an entity information acquisition server for receiving and analyzing a query term and determining entities and types of entities, and an integrated search result provision server for configuring an integrated search results page using results acquired from unit service calling units, such as an external API calling unit, a search engine calling unit, and an inference engine calling unit, and presenting integrated search results. The present invention is advantageous in that precise search results can be shown more rapidly, satisfaction with search results for a query term in which multiple entities coexist can be improved, the ambiguity of query terms is overcome, and an open platform capable of operating in conjunction with various types of web services is provided.
Abstract:
The present invention relates to a method and system for providing a related technology service, and the method of providing a related technology service by a related technology service providing apparatus includes the steps of (a) acquiring conduct agents of a specific technology; (b) acquiring key research technologies of each acquired conduct agent; and (c) obtaining a research relation between each key research technology and the specific technology. According to the present invention, a research relation between a specific technology of conduct agents which study the specific technology targeting the specific technology and key research technologies can be provided.
Abstract:
The present disclosure relates to a semantic parse tree kernel-based processing system and method of automatically extracting a semantic correlation between scientific and technological core entities. The method includes parsing syntaxes, part-of-speech information, and base chunk information on input sentences; extracting a relation of the syntaxes of the input sentences by performing a parse tree pruning based on the parsed syntaxes, part-of-speech information, and base chunk information; and extracting a similarity of the syntaxes of the input sentences by calculating a syntactic similarity, a lexical semantic similarity, and a semantic parse tree kernel of the syntaxes of the input sentences based on the extracted relations of the syntaxes of the input sentences, thereby more accurately calculating the similarity between two sentences.