• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.192-195
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• 2008

People have tendency of forgetting music title, though they easily remember particular part of music. If a music search system can find the title through a part of melody, this will provide very convenient interface to users. In this paper, we propose an algorithm that enables this type of search using feature transformation function. The original music is transformed to new feature information with sequential melodies. When a melody that is a part of search music is given to the system, the music retrieval system searches the music similar to the feature information of the melody. Moreover, this transformation function can be easily extended to various music recognition systems.

• Journal of the Korea Society of Computer and Information
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• v.9 no.2
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• pp.1-6
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• 2004

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used fuzzy conditional probability and trapezoidal. we proposed the model that can Process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition. Our goal of study is make an intelligent automatic navigation agent model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.450-453
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• 1999

In this paper, the cooperative retrieval system to interface between users and DB, image data and knowledge-based database(KDB), being formed in a linguistic knowledge expression, of system is presented. Conventional database retrieval systems provide the data only in case that the data exactly corresponding with users' requirements exist in these systems, but don't in other cases. In order to resolve this problem, if the data users require are not in existence, this system shows the data and image information which are approximate with knowledge-based database materialized by fuzzy clustering and allocation of linguistic label.

• Archives of design research
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• v.20 no.3 s.71
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• pp.203-214
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• 2007

This study proposes an information retrieval method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. Firstly, the research evaluated subjects' preferences on commercial spaces set to a hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose methods of Navigation Knowledge Base (NKB). The NKB was composed of three elements; 1. the correlation model between emotional characteristics, 2. the causal relationship between visual characteristics and emotional characteristics, 3. the transformation model between visual characteristics and the physical characteristics. Secondly, this study classified the pedestrian's destination search into 4 types with his or her preferences and the time conditions limited during navigation. For each type it presented the Destination Search Algorithm (DSA). Finally, the research simulated the destination search in 4 navigation types using NKB and DSA and verified the availability of the information retrieval method reflecting pedestrian's preferences. In conclusion, the proposed information search method will be applied to reflect the user's preferences to develop information appliances.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.531-536
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• 2014

With the very large quantity of information available on the Internet, techniques for dealing with the abundance of documents have become increasingly necessary but the problem of processing information in the documents is still technically challenging and remains under study. Automatic document summary techniques have been considered as one of critical solutions for processing documents to retain the important points and to remove duplicated contents of the original documents. In this paper, we propose a document summarization technique that uses a fuzzy theory. Proposed summary technique solves the ambiguous problem of various features determining the importance of the sentence and the experiment result shows that the technique generates better results than other previous techniques.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.51-53
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• 2008

최근 오디오 압축 기술의 발전에 힘입은 디지털 음원과 웹 스트리밍의 보급으로, 사용자가 음악 정보에 손쉽게 접할 수 있게 되었다. 이에 따라 음악을 보다 쉽고 효율적인 방법으로 검색하는 방법뿐 아니라 사용자의 환경에 따라 적절한 음악을 검색할 수 있는 기능의 필요성이 증가하게 되었다. 본 논문에서는 음악의 특징에 따라 분류된 데이터베이스를 사용하고, 사용자의 감정을 분석하여 적절한 음악을 검색하는 시스템을 제안한다. 본 시스템은 사용자의 감정 입력을 효율적으로 처리하기 위한 방법으로 Thayer의 2D emotional space를 적용하여 Valence-Arousal model의 두 가지의 입력을 처리한다. 가장 적합한 음악의 정보를 얻기 위해 사용된 Fuzzy Inference System의 IF-THEN 규칙을 정의하기 위하여 언어적으로 정의된 기존의 음악 감정 연구 결과를 적용하였고, 도출된 결과와 가장 유사도가 깊은 음악을 우선적으로 검색하도록 설계하였다. 이와 같이 구현된 시스템의 타당성을 검증하기 위해 사용자 설문조사를 수행하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.288-291
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• 2004

This paper proposes an intelligent search modeling using avatar agent. This system consists of some modules such as agent interface, agent management, preprocessor, interface machine. Core-Symbol Database and Spell Checker are related to the preprocessor module and Interface Machine is connected with Best Aggregate Designer. Our avatar agent system does the indexing work that converts user's natural language type sentence to the proper words that is suitable for the specific branch information retrieval. Indexing is one of the preprocessing steps that make it possible to guarantee the specialty of user's input and increases the reliability of the result. It references a database that consists of synonym and specific branch dictionary. The resulting symbol after indexing is used for draft search by the internet search engine. The retrieval page position and link information are stored in the database. We experimented our system with the stock market keyword SAMSUNG_SDI, IBM, and SONY and compared the result with that of Altavista and Google search engine. It showed quite excellent results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.159-165
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• 2015

The need for the recognition of music emotion has become apparent in many music information retrieval applications. In addition to the large pool of techniques that have already been developed in machine learning and data mining, various emerging applications have led to a wealth of newly proposed techniques. In the music information retrieval community, many studies and applications have concentrated on tag-based music recommendation. The limitation of music emotion tags is the ambiguity caused by a single music tag covering too many subcategories. To overcome this, multiple tags can be used simultaneously to specify music clips more precisely. In this paper, we propose a novel technique to rank the proper tag combinations based on the acoustic similarity of music clips.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.15-20
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• 2009

Much amount of data which demand fuzzy information system requires various analysis through the fuzzy set visualization. Therefore, this study proposes how to visualize fuzzy data set using variation of Venn diagram. For the fuzzy data which are related to many topics and have ranking of relation, this way gives results that users want by visualizing intersection, union and complementary set. That is, it visualizes the set of fuzzy data which have many topics at once, or the set of all fuzzy data which has topics, or the set of fuzzy data not related to a topic. Users control these sets by overlapping or piling them; visualized with Venn diagram, which is user-oriented. One distinct advantage of this visualization is the fact that it delivers web documents which users of search engine and web developers want much quickly. Furthermore, its possibility can be expanded to several purposes by using for information retrieval.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.424-431
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• 2012

In information retrieval, search engine provide the rank of web page and the summary of the web page information to user. Snippet is a summaries information of representing web pages. Visiting the web page by the user is affected by the snippet. User sometime visits the wrong page with respect to user intention when uses snippet. The snippet extraction method is difficult to accurate comprehending user intention. In order to solve above problem, this paper proposes a new snippet extraction method using fuzzy implication operator and relevance feedback. The proposed method uses relevance feedback to expand the use's query. The method uses the fuzzy implication operator between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention. The experimental results demonstrate that the proposed method can achieve better snippet extraction performance than the other methods.