• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1302-1306
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• 2004

This paper proposes a model for information filtering (IF) on the Web. The user information need is described into two levels in this model: profiles on category level, and Boolean queries on document level. To efficiently estimate the relevance between the user information need and documents by fuzzy, the user information need is treated as a rough set on the space of documents. The rough set decision theory is used to classify the new documents according to the user information need. In return for this, the new documents are divided into three parts: positive region, boundary region, and negative region. We modified user profile by the user's relevance feedback and discerning words in the documents. In experimental we compared the results of three methods, firstly is to search documents that are not passed the filtering system. Second, search documents that passed the filtering system. Lastly, search documents after modified user profile. The result from using these techniques can obtain higher precision.

• Archives of design research
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• v.19 no.2 s.64
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• pp.81-90
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• 2006

Pedestrians perceive differently from the sideway views or the exteriors of the buildings on the way to their destinations. Therefore, the navigation experience can become much different when the path was chosen based on the individual's preference from it is not. By focusing on the effects of the individual pedestrian' path choice on their navigation, this paper presents an algorithm designed for pedestrians to be able to explore their preferred path and proposes a prototype of navigation system based on the algorithm. The navigation support system searches for the best path upon their individual preferences and information of the destination. The system provides the process of retrieving the final path via the pedestrian-support system interaction. The path retrieval is peformed with the combinational matrix of keywords that are formulates Fuzzy theory from the correlations between the terms describing preferences used in the path preference survey. This paper presents the potentials of the path finding method tailored to pedestrians' preferences by a simulation of the proposed path retrieval algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.242-251
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• 2000

퍼지관계 개념을 응용한 BK-퍼지정보검색기법은 형태론에 입각하는 기존의 정보검색기법과는 달리 문서와 용어의 상대적 의미에 근거한 정보검색 기법이다. 그러나 BK-퍼지정보검색기법은 높은 시간복잡도(time complexity)의 검색 연산을 내재하고 있어 실제 대용량의 정보 검색은 사실상 불가능하다. 본 논문에서는 BK-퍼지검색정보모델의 시간복잡도를 낮추기 위해, 축소용어집합(reduced term set)을 이용한 개선된 BK-퍼지정보검색모델(A-FIRM)을 제안한다. 개선된 BK-FIRM은 시스템 처리시간과 신뢰도 간 상층점(trade-off)을 제공한다. 축소용어집합은 용어집합의 부분집합으로서 검색결과의 신뢰도와 밀접한 관계를 가진다. 동일한 크기의 축소용어집합이 주어질 때, 보다 적절한 용어들로 구성된 축소용어집합이 보다 나은 검색 신뢰도를 이끈다. 따라서 보다 적절한 축소용어집합 구성을 위한 축소용어집합 추출방법이 요구된다. 본 논문에서는 축소용어집합 추출방법을 크게 무작위 추출, 규칙에 의한 추출, 인간에 의한 직관적 추출 방법으로 구분하고 검색결과의 신뢰도 변화 형태를 분석한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.77-80
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• 2000

정보 검색은 사용자가 원하는 요구에 가장 적합한 정보를 검색할 수 있도록 되어야 한다. 질의어가 문서에 대하여 어느 정도의 유사성을 가지고 존재하느냐를 기준으로 문서를 순서화 한다. 실제 순서화된 문서들을 보면 질의어와는 다른 문서들이 순서화 되는 경우를 볼 수 있다 본 논문에서는 순서화 되는 문서들 중에서 그 문서들이 질의어와 어느 정도 가까운지를 확장 퍼지 개념 네트워크에 근거한 문서 검색을 위한 퍼지 순위 처리를 위한 방법을 제시한다 확장 퍼지 개념 네트워크에는 개념들 사이에 4가지의 퍼지 관계를 사용한다. 퍼지 양의 관계, 퍼지 음의 관계, 퍼지 일반화, 및 퍼지 세분화 등이 있다. 확장 퍼지 개념 네트워크는 관계 행렬과 관련 행렬로 모델화 한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.124-128
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• 2011

Music emotion recognition is currently one of the most attractive research areas in music information retrieval. In order to use emotion as clues when searching for a particular music, several music based emotion recognizing systems are fundamentally utilized. In order to maximize user satisfaction, the recognition accuracy is very important. In this paper, we develop a new music emotion recognition system, which employs a multilabel feature selector and multilabel classifier. The performance of the proposed system is demonstrated using novel musical emotion data.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.17-35
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• 2011

The collective intelligence is a common-based production by the collaboration and competition of many peer individuals. In other words, it is the aggregation of individual intelligence to lead the wisdom of crowd. Recently, the utilization of the collective intelligence has become one of the emerging research areas, since it has been adopted as an important principle of web 2.0 to aim openness, sharing and participation. This paper introduces an approach to seek the collective intelligence by cognition of the relation and interaction among individual participants. It describes a methodology well-suited to evaluate individual intelligence in information retrieval and classification as an application field. The research investigates how to derive and represent such cognitive intelligence from individuals through the application of fuzzy relational theory to personal construct theory and knowledge grid technique. Crucial to this research is to implement formally and process interpretatively the cognitive knowledge of participants who makes the mutual relation and social interaction. What is needed is a technique to analyze cognitive intelligence structure in the form of Hasse diagram, which is an instantiation of this perceptive intelligence of human beings. The search for the collective intelligence requires a theory of similarity to deal with underlying problems; clustering of social subgroups of individuals through identification of individual intelligence and commonality among intelligence and then elicitation of collective intelligence to aggregate the congruence or sharing of all the participants of the entire group. Unlike standard approaches to similarity based on statistical techniques, the method presented employs a theory of fuzzy relational products with the related computational procedures to cover issues of similarity and dissimilarity.