• Journal of Internet Computing and Services
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• v.6 no.2
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• pp.99-115
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• 2005

Extensible Markup Language (XML) is an Internet standard that is used to express and convert data, In order to find the necessary information out of XML documents, you need a search system for XML documents, In this research, we have developed a search system that can find documents that matches the structure and content of a given XML document, making the best use of XML structure, Search metrics take account of the similarity in tag names, tag values, and the structure of tags, After a search, the system displays the ranked results in the order of aggregate similarity, Three methods of query are provided: keyword search which is conventional; search with tag names and their values; and search with XML documents, These three methods enable users to choose the method that best suits their preference, resulting in the increase of the usefulness of the system.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.541-543
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• 2002

멀티미디어 관련 기술이 발전하고 인터넷 사용이 보편화되면서 모바일 단말기 상에서 비디오 데이터를 검색하려는 요구가 증가하고 있다. 그러나 모바일 단말기의 경우 낮은CPU 처리율이나 대역폭, 배터리 용량 등의 제약으로 인해 비디오를 그대로 검색하기에는 어려움이 많다. 최근 들어 비디오 데이터의 요약을 통해 모바일 환경의 제약점을 극복하고 효율적으로 비디오를 검색하기 위한 연구가 활발히 진행되고 있다. 본 논문에서는 기존의 단편적인 비디오 데이터 요약 기술에서 벗어나 요약된 비디오 데이터에 특징이나 중요도를 MPEG-7을 이용해서 주석 처리하여 사용자에게 보다 효과적인 검색 환경을 제공하고자 한다. 이러한 요약 방법은 모바일 환경에서 사용자의 우선 순위나 요구하는 특징에 적합한 동영상을 볼 수 있고 비디오의 전송시 모바일 장비의 성능에 따라 차별적으로 요약 정보를 제공함으로써 모바일 환경의 제약을 상당히 완화시킨다.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.63-73
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• 2011

In general, conventional search engines provide the same search results for the same queries of users, and however such techniques do not consider users' characteristics. To overcome this problem, we need a new way of personalized search which returns customized search results according to users' preference. In this paper, we propose a concept network profile-based personalized web search system in which the concept network is developed for accumulating users' characteristics. The concept network-based user profile is used to expand initial search queries to achieve personalized search. The concept network is a network structure of concepts where each concept is generated whenever each query is submitted, and it can be defined as a set of keywords extracted from the selected documents. Furthermore, we have improved the concept networks by augmenting intent keywords of each concept with a set of classification tags, called folksonomy, assigned to each document. For an additional personalized search technique, we propose a new re-ranking method that analayzes the degree of overlapped search results.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.51-55
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• 2016

본 논문에서는 임상 의사 결정 지원을 위한 UMLS와 위키피디아를 이용하여 지식 정보를 추출하고 질병중심 문서 클러스터와 단어 의미 표현을 이용하여 질의 확장 및 문서를 재순위화하는 방법을 제안한다. 질의로는 해당 환자가 겪고 있는 증상들이 주어진다. UMLS와 위키피디아를 사용하여 병명과 병과 관련된 증상, 검사 방법, 치료 방법 정보를 추출하고 의학 인과 관계를 구축한다. 또한, 위키피디아에 나타나는 의학 용어들에 대하여 단어의 효율적인 의미 추정 기법을 이용하여 질병 어휘의 의미 표현 벡터를 구축하고 임상 인과 관계를 이용하여 질병 중심 문서 클러스터를 구축한다. 추출한 의학 정보를 이용하여 질의와 관련된 병명을 추출한다. 이후 질의와 관련된 병명과 단어 의미 표현을 이용하여 확장 질의를 선택한다. 또한, 질병 중심 문서 클러스터를 이용하여 문서 재순위화를 진행한다. 제안 방법의 유효성을 검증하기 위해 TREC Clinical Decision Support(CDS) 2014, 2015 테스트 컬렉션에 대해 비교 평가한다.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.83-88
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• 2016

Subtopic mining is the extraction and ranking of possible subtopics, which disambiguate and specify the search intentions of an input query in terms of relevance, popularity, and diversity. This paper describes the limitations of previous studies on the utilization of web resources, and proposes a subtopic mining method with a two-level hierarchy based on hierarchical search intentions and web resources, in order to overcome these limitations. Considering the characteristics of resources provided by the official subtopic mining task, we extract various second-level subtopics reflecting hierarchical search intentions from web documents, and expand and re-rank them using other provided resources. Terms in subtopics with wider search intentions are used to generate first-level subtopics. Our method performed better than state-of-the-art methods in almost every aspect.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.161-169
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• 2015

Realtime search words of typical portal sites appear every few seconds in descending order by search frequency in order to show issues increasing rapidly in interest. However, the characteristics of realtime search words reordering within too short a time cause problems that they go over the key issues of the day. This paper proposes a method for deriving a key issue through association analysis of realtime search words. The proposed method first makes scores of realtime search words depending on the ranking and the relative interest, and derives the top 10 search words through descriptive statistics for groups. Then, it extracts association rules depending on 'support' and 'confidence', and chooses the key issue based on the results as a graph visualizing them. The results of experiments show that the key issue through association rules is more meaningful than the first realtime search word.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.690-696
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• 2016

Search engines that rely on morphological matching of user query and web document content do not support individual interests. This research proposes a personalized web search scheme that returns the results that reflect the users' query intent and personal preferences. The performance of the personalized search depends on using an effective user profiling strategy to accurately capture the users' personal interests. In this study, the user profiles are the databases of topic words and customized weights based on the recent user queries and the frequency of topic words in click history. To determine the precise meaning of ambiguous queries and topic words, this strategy uses WordNet to calculate the semantic relatedness to words in the user profile. The experiments were conducted by installing a query expansion and re-ranking modules on the general web search systems. The results showed that this method has 92% precision and 82% recall in the top 10 search results, proving the enhanced performance.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.233-240
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• 2004

This paper presents a method to implicitly resolve ambiguities using dynamic incremental clustering in Korean-to-English and Japanese-to-English cross-language information retrieval (CLIR). The main objective of this paper shows that document clusters can effectively resolve the ambiguities tremendously increased in translated queries as well as take into account the context of all the terms in a document. In the framework we propose, a query in Korean/Japanese is first translated into English by looking up bilingual dictionaries, then documents are retrieved for the translated query terms based on the vector space retrieval model or the probabilistic retrieval model. For the top-ranked retrieved documents, query-oriented document clusters are incrementally created and the weight of each retrieved document is re-calculated by using the clusters. In the experiment based on TREC test collection, our method achieved 39.41% and 36.79% improvement for translated queries without ambiguity resolution in Korean-to-English CLIR, and 17.89% and 30.46% improvements in Japanese-to-English CLIR, on the vector space retrieval and on the probabilistic retrieval, respectively. Our method achieved 12.30% improvements for all translation queries, compared with blind feedback in Korean-to-English CLIR. These results indicate that cluster analysis help to resolve ambiguity.

• The KIPS Transactions:PartB
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• v.8B no.2
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• pp.115-122
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• 2001

퍼지관계 개념에 기반한 BK-FIRM(Bandler-Kohout 퍼지정보검색기법)은 형태론에 입각한 기존의 정보검색기법과는 달리 문서와 용어의 상대적 의미에 근거한 퍼지정보검색기법이다. BK-FIRM은 시소러스 자동 구축 기능, 검색 결과의 퍼지화된 우선 순위 제공과 같은 장점을 가지고 있다. 그러나, BK-퍼지정보검색기법은 높은 시간복잡도(time complexity)의 검색 연산을 내재하고 있어 다양한 분야 적용이 불가능하다. 본 논문에서는 축소용어집합을 이용하여 BK-FIRM의 시간복잡도를 낮춘 A-FIRM(개선된 Bandler-Kohout 퍼지정보검색모델)을 소개하고 이를 정보검색시스템으로 설계 및 구현한 A-FIRS(개선된 Bandler-Kohout 퍼지정보검색시스템)를 구현한다. A-FIRS는 크게 문서베이스와 시소러스를 구축하는 전처리부(preprocess unit)와 사용자의 검색요구를 처리하여 문서를 검색하는 실시간처리부(real-time process unit)로 나누어지며, 각 처리부는 기능적 특성에 따라 4개의 처리단계로 구성된다. A-FIRS는 WWW 기반 환경과 연동하도록 설계되었으며, WWW 환경의 사용자로부터 주어진 검색요구를 처리하여 검색결과를 제공한다.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.269-282
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• 2007

We propose a personalized concept-based retrieval technique that uses domain ontology. Proposed system consist or representative concept extraction, user profile construction, and concept-based retrieval stages. First, we extract representative concept with using technique form contents and create the domain ontology. We compose user profile analysis that uses domain ontology for personalized concept-based retrieval. To verify the efficiency of the proposed technique, we perform experiment for Internet site in the engineering area. The results of experiment show that the proposed technique using the domain ontology and user profiles is more efficient than the existing techniques. Hence, the proposed concept-based retrieval technique can be expected to contribute to the development of an efficient personalized recommendation system or e-Commerce system.