| Autor: |
Xiaofang Zhou, Jianzhong Li, Heng Tao Shen, Kitsuregawa, Masaru, Yanchun Zhang, Antonellis, Ioannis, Bouras, Christos, Poulopoulos, Vassilis |
| Zdroj: |
Frontiers of WWW Research & Development - APWeb 2006; 2006, p391-401, 11p |
| Abstrakt: |
Existing news portals on the WWW aim to provide users with numerous articles that are categorized into specific topics. Such a categorization procedure improves presentation of the information to the end-user. We further improve usability of these systems by presenting the architecture of a personalized news classification system that exploits user's awareness of a topic in order to classify the articles in a ‘per-user' manner. The system's classification procedure bases upon a new text analysis and classification technique that represents documents using the vector space representation of their sentences. Traditional ‘term-to-documents' matrix is replaced by a ‘term-to-sentences' matrix that permits capturing more topic concepts of every document. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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