• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제3권2호
• /
• pp.222-226
• /
• 2003

Information retrieval must be able to search the most suitable document that user need from document set. If foretell document adaptedness by similarity degree about QL(Query Language) of document, documents that search person does not require are searched. In this paper, showed that can search the most suitable document on user's request searching document of the whole space using genetic algorithm and used knowledge-base operator to solve various model's problem.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제5권4호
• /
• pp.353-359
• /
• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems (UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between 0 -1. Second, RDB and SQL (Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS (Knowledge Management Systems).

• 한국멀티미디어학회:학술대회논문집
• /
• 한국멀티미디어학회 1998년도 춘계학술발표논문집
• /
• pp.133-137
• /
• 1998

MPEG-7의 Standard Description을 위한 여러 가지 요소에 대한 정의가 여러 연구에서 약간의 차이를 주고 있지만 전체적인 방향은 형성되어 지고 있는 실정이다. 본 연구에서는 그 요소들에서 지능형 멀티미디어 탐색엔진에서 high level linguistic query를 처리할 수 있는 fuzzy interenced database 기능을 MPEG-7과 연계할 수 있는가를 연구하였다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
• /
• pp.271-275
• /
• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this Purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between $0\∼1$. Second, RDB and SQL(Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS(Knowledge Management Systems)

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
• /
• pp.153-156
• /
• 2005

In this paper, a framework for implementing UFIS (Unified Fuzzy rule-based knowledge Inference System) is presented. First, fuzzy clustering and fuzzy rules deal with the presence of the knowledge in DB (DataBase) and its value is presented with a value between 0 and 1. Second, RDB (Relational DB) and SQL queries provide more flexible functionality fur knowledge management than the conventional non-fuzzy knowledge management systems. Therefore, the obtained fuzzy rules offer the user additional information to be added to the query with the purpose of guiding the search and improving the retrieval in knowledge base and/ or rule base. The framework can be used as DM (Data Mining) and ES (Expert Systems) development and easily integrated with conventional KMS (Knowledge Management Systems) and ES.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제2권1호
• /
• pp.9-14
• /
• 2002

Boolean retrieval is simple and elegant. However, since there is no provision for term weighting, no ranking of the answer set is generated. As a result, the size of the output might be too large or too small. Relevance feedback is the most popular query reformulation strategy. in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2012년도 추계학술대회
• /
• pp.387-388
• /
• 2012

본 논문은 스니핏을 이용시 가끔 사용자의 의도와는 다른 잘못된 웹 페이지를 방문하는 문제를 해결하기 위해 퍼지를 이용한 새로운 스니핏 추출 방법을 제안한다. 제안방법은 의사연관 피드백을 이용하여 사용자의 질의를 확장학고, 확장된 질의와 웹 페이지 사이에 퍼지 연관을 이용함으로써 사용자의 의도가 의미적으로 더 잘 포함되는 스니핏을 추출할 수 있다.

• 한국정보통신학회논문지
• /
• 제16권11호
• /
• pp.2374-2381
• /
• 2012

본 논문은 퍼지와 의미특징을 이용한 새로운 스니핏 추출의 성능향상 방법을 제안한다. 제안방법은 문장집합의 의미특징을 이용하여 대표문장을 생성하고, 대표문장과 문장집합의 퍼지관계를 이용함으로써 질의를 잘 나타내는 스니핏을 추출한다. 또한 의사연관 피드백을 이용하여 질의를 확장함으로써 사용자의 의도가 의미적으로 더 잘 포함되는 스니핏을 추출할 수 있다. 실험결과 제안방법이 다른 방법에 비해서 스니핏 추출에 더 좋은 성능을 보인다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제16권1호
• /
• pp.36-43
• /
• 2016

The transformation time among queries in the database management system (DBMS) is responsible for the execution time of users' queries, because a conventional DBMS does not consider the transformation cost when queries are transformed for execution. To reduce the transformation time (cost reduction) during execution, we propose an optimal query transformation method by exploring queries from a cost-based point of view. This cost-based point of view means considering the cost whenever queries are transformed for execution. Toward that end, we explore and compare set off heuristic, linear, and exhaustive cost-based transformations. Further, we describe practical methods of cost-based transformation integration and some query transformation problems. Our results show that, some cost-based transformations significantly improve query execution time. For instance, linear and heuristic transformed queries work 43% and 74% better than exhaustive queries.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제11권2호
• /
• pp.95-102
• /
• 2011

In this paper, a Mobile Continuous Query Processing System (MCQPS) is designed to solve problems related to database hoarding, maintenance of shared data consistency, and optimization of logging. These problems are caused by weak connectivity and disconnection of wireless networks inherent in mobile database systems under mobile client-server environments. We show the superiority of the proposed MCQPS by comparing its performance to the Client-Intercept-Server (C-I-S) model. In addition, several experimental results show the effectiveness of our proposed indexing structure and methodology for real-time continuous queries.