• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.63-71
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• 2011

The current Web portal sites provide significant keywords with high popularity or importance; specifically, user-friendly services such as tag clouds and associated word search are provided. However, in general, since news articles are classified only with their date and categories, it is not easy for users to find other articles related to some articles while reading news articles classified with categories. And the conventional associated keyword service has not satisfied users sufficiently because it depends only upon user queries. This paper proposes a way of searching news articles by utilizing the keywords tightly associated with users' queries. Basically, the proposed method discovers a set of keyword association patterns by using the association rule mining technique that extracts association patterns for keywords by focusing upon sentences containing some keywords. The method enables users to navigate the space of associated keywords hidden in large news articles.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.373-382
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• 2017

As the number of scientific and technical contents increases, services that support efficient search of scientific and technical contents are required. When an author's affiliation is used as a keyword, not only the contents produced by the affiliation can be searched, but also the identification rate of the search result using the author and the term as keyword can be improved. Because of the ambiguity and vagueness of the data used as a search keyword, the search result may include false negative or false positive. However, the previous research on the control through identification of the search keyword is mainly focused on the author data and terminology data. In this paper, we propose the algorithm to identify affiliations and experiment with show the experiment with scientific and technological contents held by the Korea Institute of Science and Technology Information.

• Journal of Korean Library and Information Science Society
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• v.41 no.1
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• pp.149-165
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• 2010

In this research, we analyze about the general service provided by Society of Korean journal articles of science and technology. Personalized retrieval services which are suitable to the articles service were developed based on this. That is, there are personalized retrieval system based on user's keyword, authors navigation system, automatic topic recommendation system based on author's keyword, and similar user automatic recommendation system. In this research, personalized service methods being suitable to the articles service of Society tries to be considered through the user survey.

• Journal of KIISE:Software and Applications
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• v.35 no.7
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• pp.405-416
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• 2008

To overcome the limitation of keyword-based integrated search, this study shows entity-centric integrated search method using URI scheme. Our system generates entity pages in ways of analyzing user's keyword and instances matched with it, selecting optimal entity type, and calling unit services simultaneously. Topic information extracted from articles is propagated to persons, institutions, and locations by reasoning for providing topic-centric information. With comparative experiments based on search results and usability tests, we proved that this approach is superior to keyword-based integrated search served by CiteSeer and Google Scholar.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.754-765
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• 2006

In XML keyword search, a search result is defined as a set of the smallest elements (i.e., least common ancestors) containing all query keywords and a granularity of indexing is an XML element instead of a document. Under the conventional index structure, all least common ancestors produced by the combination of the elements, each of which contains a query keyword, are considered as a search result. In this paper, to avoid unnecessary operations of producing the least common ancestors and reduce query process time, we describe a way to construct a partitioned index composed of several partitions and produce a search result by merging those partitions if necessary. When a search result is restricted to be composed of the least common ancestors whose depths are higher than a given minimum depth, under the proposed partitioned index structure, search systems can reduce the query process time by considering only combinations of the elements belonging to the same partition. Even though the minimum depth is not given or unknown, search systems can obtain a search result with the partitioned index, which requires the same query process time to obtain the search result with non-partitioned index. Our experiment was conducted with the XML documents provided by the DBLP site and INEX2003, and the partitioned index could reduce a substantial amount of query processing time when the minimum depth is given.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.1
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• pp.87-97
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• 2005

A secure index search protocol let us search the index of encrypted documents using the trapdoor for a keyword. It enables an untrusted server to learn nothing more than the search result about the documents without revealing the keyword. A lot of secure search protocols have been suggested but they only considered the search between a single-user and a server. In real organizations such as government offices or enterprises where exist many hierarchical departments, the search system for groups is arisen more often. In this paper, we construct secure index search protocols for hierarchical group settings without re-encryption of the old encrypted documents when group keys are re-keyed newly.

• Annual Conference on Human and Language Technology
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• 2011.10a
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• pp.79-82
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• 2011

본 논문은 다양한 주제 분야의 연구 성과물을 제공하는 학술DB에서 주제어(Keyword) 정보를 바탕으로 SNA(Social Network Analysis)기법을 적용해 검색어와 연관도가 높은 연관검색어를 제공하는 것을 그 목적으로 한다. 이를 위해 주제어들 간의 가중치(Weight)를 계산한 뒤 Ego Network 분석을 통해 검색어와 연관된 연관주제어를 추출하고 이를 기존 학술DB에서 제공한 연관검색어와 비교 정리하였다. 그리고 정리된 결과를 연관규칙 마이닝기법, 유사계수를 적용해 연관도측면에서 비교 평가하였다.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.67-79
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• 2007

As the Web technologies and wired/wireless network are improved and various new multimedia services are introduced recently, need for searching multimedia including video data has been much increasing, The previous approaches for multimedia retrieval, however, do not make use of the relationships among semantic concepts contained in multimedia contents in an efficient way and provide only restricted search results, This paper proposes a multimedia retrieval system exploiting semantic relevancy of multimedia contents based on a domain ontology, We show the effectiveness of the proposed system by experiments on a prototype system we have developed. The proposed multimedia retrieval system can extend a given search keyword based on the relationships among the semantic concepts in the ontology and can find a wide range of multimedia contents having semantic relevancy to the input keyword. It also presents the results categorized by the semantic meaning and relevancy to the keyword derived from the ontology. Independency of domain ontology with respect to metadata on the multimedia contents is preserved in the proposed system architecture.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.209-220
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• 2017

As a semantic data is widely used in various applications such as Knowledge Bases and Semantic Web, needs for effective search over a large amount of RDF data have been increasing. Previous keyword search methods based on distinct root semantics only retrieve a set of answer trees having different root nodes. Thus, they often find answer trees with similar meanings or low query relevance together while those with the same root node cannot be retrieved together even if they have different meanings and high query relevance. We propose a new method to find diverse and relevant answers to the query by permitting duplication of root nodes among them. We present an efficient query processing algorithm using path indexes to find top-k answers given a maximum amount of root duplication a set of answer trees can have. We show by experiments using a real dataset that the proposed approach can produce effective answer trees which are less redundant in their content nodes and more relevant to the query than the previous method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.504-505
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• 2017

Existing morpheme analyzers classify the words used in writing documents. A system for extracting sentences and paragraphs based on a morpheme analyzer is being developed. However, there are very few systems that compress documents and extract important paragraphs. The algorithm proposed in this paper calculates the weights of the keyword written in the document and extracts the paragraphs containing the keyword. Users can reduce the time to understand the document by reading the paragraphs containing the keyword without reading the entire document. In addition, since the number of extracted paragraphs differs according to the number of keyword used in the search, the user can search various patterns compared to the existing system.