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政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 > Item 140.119/26987

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/26987

Title:	Ontology-Based Structured Cosine Similarity in Document Summarization: with Applications to Mobile Audio-Based Knowledge Management
Authors:	苑守慈;Jerry Sun Yuan, Soe-Tysr
Date:	2005-10
Issue Date:	2009-01-17 15:59:53 (UTC+8)
Abstract:	Development of algorithms for automated text categorization in massive text document sets is an important research area of data mining and knowledge discovery. Most of the text-clustering methods were grounded in the term-based measurement of distance or similarity, ignoring the structure of the documents. In this paper, we present a novel method named structured cosine similarity (SCS) that furnishes document clustering with a new way of modeling on document summarization, considering the structure of the documents so as to improve the performance of document clustering in terms of quality, stability, and efficiency. This study was motivated by the problem of clustering speech documents (of no rich document features) attained from the wireless experience oral sharing conducted by mobile workforce of enterprises, fulfilling audio-based knowledge management. In other words, this problem aims to facilitate knowledge acquisition and sharing by speech. The evaluations also show fairly promising results on our method of structured cosine similarity.
Relation:	IEEE Transactions on Transactions on Systems Man and Cybernetics Part B, 35(5), 1028-1040
Data Type:	article
DOI 連結:	http://dx.doi.org/10.1109/TSMCB.2005.850153
DOI:	10.1109/TSMCB.2005.850153
Appears in Collections:	[資訊管理學系] 期刊論文

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