• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.47-55
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• 2021

Analysis of research trends in specific subject areas is performed by examining related topics and subject changes by using topic modeling techniques through keyword extraction for most of the literature information (paper, patents, etc.). Unlike existing research methods, this paper extracts topics related to the research topic using the LDA topic modeling technique for the project information of national R&D projects provided by the National Science and Technology Knowledge Information Service (NTIS) in the field of artificial intelligence. By analyzing these topics, this study aims to analyze research topics and investment directions for national R&D projects. NTIS provides a vast amount of national R&D information, from information on tasks carried out through national R&D projects to research results (thesis, patents, etc.) generated through research. In this paper, the search results were confirmed by performing artificial intelligence keywords and related classification searches in NTIS integrated search, and basic data was constructed by downloading the latest three-year project information. Using the LDA topic modeling library provided by Python, related topics and keywords were extracted and analyzed for basic data (research goals, research content, expected effects, keywords, etc.) to derive insights on the direction of research investment.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1219-1229
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• 1999

일반적으로 AND, OR, NOT과 같은 연산자를 사용하는 불리언 질의는 사용자의 검색의도를 정확하게 표현할 수 있기 때문에 검색 전문가들은 불리언 질의를 사용하여 높은 검색성능을 얻는다고 알려져 있지만, 일반 사용자는 자신이 원하는 정보를 불리언 형태로 표현하는데 익숙하지 않다. 본 논문에서는 검색성능의 향상과 사용자 편의성을 동시에 만족하기 위하여 사용자의 자연어 질의를 확장 불리언 질의로 자동 변환하는 방법론을 제안한다. 먼저 자연어 질의를 범주문법에 기반한 구문분석을 수행하여 구문트리를 생성하고 연산자 및 키워드 정보를 추출하여 구문트리를 간략화한다. 다음으로 간략화된 구문트리로부터 명사구를 합성하고 키워드들에 대한 가중치를 부여한 후 불리언 질의를 생성하여 검색을 수행한다. 또한 구문분석의 오류로 인한 검색성능 저하를 최소화하기 위하여 상위 N개 구문트리에 대해 각각 불리언 질의를 생성하여 검색하는 N-BEST average 방법을 제안하였다. 정보검색 실험용 데이타 모음인 KTSET2.0으로 실험한 결과 제안된 방법은 수동으로 추출한 불리언 질의보다 8% 더 우수한 성능을 보였고, 기존의 벡터공간 모델에 기반한 자연어질의 시스템에 비해 23% 성능향상을 보였다. Abstract There have been a considerable evidence that trained users can achieve a good search effectiveness through a boolean query because a structural boolean query containing operators such as AND, OR, and NOT can make a more accurate representation of user's information need. However, it is not easy for ordinary users to construct a boolean query using appropriate boolean operators. In this paper, we propose a boolean query formulation method that automatically transforms a user's natural language query into a extended boolean query for both effectiveness and user convenience. First, a user's natural language query is syntactically analyzed using KCCG(Korean Combinatory Categorial Grammar) parser and resulting syntactic trees are structurally simplified using a tree-simplifying mechanism in order to catch the logical relationships between keywords. Next, in a simplified tree, plausible noun phrases are identified and added into the same tree as new additional keywords. Finally, a simplified syntactic tree is automatically converted into a boolean query using some mapping rules and linguistic heuristics. We also propose an N-BEST average method that uses top N syntactic trees to compensate for bad effects of single incorrect top syntactic tree. In experiments using KTSET2.0, we showed that a proposed method outperformed a traditional vector space model by 23%, and surprisingly manually constructed boolean queries by 8%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3677-3688
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• 2011

The patent information retrieval system can serve a variety of purposes. In general, the patent information is retrieved using limited key words. To identify earlier technology and priority rights repeated effort is needed. This study proposes a method of content-based retrieval using text mining. Using the proposed algorithm, each of the documents is invested with characteristic value. The characteristic values are used to compare similarities between query documents and database documents. Text analysis is composed of 3 steps: stop-word, keyword analysis and weighted value calculation. In the test results, the general retrieval and the proposed algorithm were compared by using accuracy measurements. As the study arranges the result documents as similarities of the query documents, the surfer can improve the efficiency by reviewing the similar documents first. Also because of being able to input the full-text of patent documents, the users unacquainted with surfing can use it easily and quickly. It can reduce the amount of displayed missing data through the use of content based retrieval instead of keyword based retrieval for extending the scope of the search.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.247-256
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• 2008

This research is to develop product retrieval system through simplified communication by applying intelligent agent technology based on automatically created domain ontology to present solution on problems with e-commerce system which searches in the web documents with a simple keyword. Ontology development extracts representative term based on classification information of international product classification code(UNSPSC) and jewelry websites that is applied to analogy relationship thesaurus to establish standardized ontology. The intelligent agent technology is applied to retrieval stage to support efficiency of information collection for users by designing and developing e-commerce system supported with semantic web. Moreover, it designs user profile to personalized search environment and provide personalized retrieval agent and retrieval environment with inference function to make available with fast information collection and accurate information search.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.630-636
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• 2004

According to the increase of audio and video data utilization, the presentation of multimedia data contents and the work of retrieving, storing and manipulating a multimedia data have been the focus of recent work. The display for multimedia data should retrieve and access the contents easily that users want to present. This study is about the design and implementation of a system to retrieve multimedia data based on the contents of documentation or the caption information of a multimedia data for retrieving documentation including multimedia data. It intends to develop an filtering step to retrieve all of keyword within the caption information of multimedia data and text of a documentation. Also, the system is designed to retrieve a large amount of data quickly using an inverted file structure available for B+ tree.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.126-128
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• 1998

본 논문에서 구현하고자 하는 웹기반 사용자별 에이전트는 웹을 이용해 정보를 검색하는 사용자들에 대한 사용자 관심도를 사용자의 웹검색 행위를 감시하는 모니터 에이전트에 사용자가 직접 기술하게 하고 이를 별도의 학습서버를 두어 사용자별 프로파일을 만들어 이를 사용자가 확인 및 편집할 수 있게 하였다. 서버에서의 학습 과정은 웹 브라우저를 통하여 수집된 정보를 바탕으로 사용자가 관심을 가지는 웹 문서의 일반적인 내용에 대한 관심 정확도를 높이는 일련의 단어 정제 과정을 통하여 최적의 관심 키워드를 추출하는 작업으로 이루어지며 이는 표현 모델인 사용자 프로파일을 구축하여, 관심 문서를 검색하는데 적절한 정보를 제시하는 것을 목적으로 한다. 이 시스템에서 적용되는 학습 방식은 사용자의 웹 문서 관심도에 의존하므로 웹 문서에 나타나는 텍스트들을 대상으로 C4.5 학습 시스템을 적용한다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.406-408
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• 2002

컴퓨터 기술의 발전과 네트워크의 급속한 확산으로 사회전반에 걸쳐 특허, 기업뿐 아니라 교육 현장의 효율화를 지원하기 위한 분야에서도 웹이 응용되고 있다. 교육 현장에서 작성되어지고 있는 문서 중 학습 지도안 작성은 교육 정보의 체계적인 제공이 미흡하고, 많은 시간과 노력이 요구되는 활동이므로 교수 개인이 모든 교수 활동에 필요한 지도안을 작성하는데는 어려움이 있다. 이를 위해, 웹에서 정보를 공유하여 문서의 재사용성을 높일 수 있는 시스템이 필요하게 되었다. 웹에서 표준화된 XML을 이용하여 문서의 생성과 검색, 그리고 재사용이 가능하도록 제공함으로써 교수자의 다양한 요구사항을 융통성 있게 수용할 수 있다. 본 논문에서는 학습지도안 시스템을 분석하여 공통DTD(Document Type Definition)를 생성하고 공통 DTD를 통해 표준화된 XML 문서를 제공한다. 좀더 효율적인 수업을 위해 학습지도안 작성이 용이하도록 학습지도안 작성용 에디터를 제공하며, 또한 XML DOM(Document Object Model)을 이용하여 검색기에서는 구조기반, 패싯, 키워드 검색 방법을 제시하고, 등록기에서는 DOM을 이용하여 해당 데이터를 추출하고 DB에 등록한다. 이는 문서의 재사용성을 높일 수 있다. 따라서, XML을 학교 현장에서 이용함으로써 웹에서 정보의 공유를 원활히 하고, 문서 작성의 효율성을 높이고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.816-818
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• 2015

본 논문에서는 질의유형을 통한 검색기반 질의응답 시스템을 구현하기 위한 설계방법을 제안한다. 이를 위해 위키피디아 문서의 링크 데이터를 이용하여 색인 대상문서와 데이터베이스를 구축하는 색인 모델과 2-포아송 모델을 이용하여 얻은 문서들을 색인 데이터베이스를 통해 필터링하여 정답 후보문장을 추출하는 검색모델, 키워드 패턴 매칭 기반 질의유형 분류 모델을 설계하였다.

• Journal of Korean Library and Information Science Society
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• v.34 no.2
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• pp.233-253
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• 2003

Knowledge organization is the way we humans understand the world. There are two types of information organization mechanisms studied in information retrieval: namely classification md clustering. Classification organizes entities by pigeonholing them into predefined categories, whereas clustering organizes information by grouping similar or related entities together. The system of the Internet information resources extracts a keyword from the words which appear in the web document and draws up a reverse file. Term clustering based on grouping related terms, however, did not prove overly successful and was mostly abandoned in cases of documents used different languages each other or door-way-pages composed of only an anchor text. This study examines infometric analysis and clustering possibility of web documents based on co-link topology of web pages.

• Journal of Internet Computing and Services
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• v.16 no.4
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• pp.39-50
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• 2015

In information retrieval process through search engine, some users want to retrieve several documents that are corresponding with specific time period situation. For example, if user wants to search a document that contains the situation before 'Japanese invasions of Korea era', he may use the keyword 'Japanese invasions of Korea' by using searching query. Then, search engine gives all of documents about 'Japanese invasions of Korea' disregarding time period in order. It makes user to do an additional work. In addition, a large percentage of cases which is related to historical documents have different time period between generation date of a document and record time of contents. If time period in document contents can be extracted, it may facilitate effective information for retrieval and various applications. Consequently, we pursue a research extracting time period of Joseon era's historical documents by using historic literature for Joseon era in order to deduct the time period corresponding with document content in this paper. We define historical objects based on historic literature that was collected from web and confirm a possibility of extracting time period of web document by machine learning techniques. In addition to the machine learning techniques, we propose and apply the similarity filtering based on the comparison between the historical objects. Finally, we'll evaluate the result of temporal indexing accuracy and improvement.