Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/100462
標題: Categorization of Multiple Documents Using Fuzzy Overlapping Clustering Based on Formal Concept Analysis
作者: Yi-Hui Chen 
Eric Jui-Lin Lu 
Ya-Wen Cheng 
關鍵字: Overlapping clustering;Formal Concept Analysis;fuzzy logic
摘要: 
Most clustering algorithms build disjoint clusters. However, clusters might be overlapped because documents may belong to two or more categories in the real world. For example, a paper discussing the Apple Watch may be categorized into either 3C, Fashion, or even Clothing and Shoes. Therefore, overlapping clustering algorithms have been studied such that a resource can be assigned to one or more clusters. Formal Concept Analysis (FCA), which has many practical applications in information science, has been used in disjoin clustering, but has not been studied in overlapping clustering. To make overlapping clustering possible by using FCA, we propose an approach, including two types of transformation. From the experimental results, it shows that the proposed fuzzy overlapping clustering performed more efficiently than existing overlapping clustering methods. The positive results confirm the feasibility of the proposed scheme used in overlapping clustering. Also, it can be used in applications such as recommendation systems.
URI: http://hdl.handle.net/11455/100462
Appears in Collections:資訊管理學系

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