Abstract
This paper describes an information system, which classifies web pages in specific categories according to a proposed relevance feedback mechanism. The proposed relevance feedback mechanism is called Balanced Relevance Weighting Mechanism — BRWM and uses the proportion of the already relevant categorized information amount for feature classification. Experimental measurements over an e-commerce framework, which describes the fundamental phases of web commercial transactions verified the robustness of using the mechanism on real data. Except from revealing the accomplished sequences in a web commerce transaction, the system can be used as an assistant and consultation tool for classification purposes. In addition, BRWM was compared with a similar relevance feedback mechanism from the literature over the established corpus of Reuters-21578 text categorization test collection, presenting promising results.
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© 2006 International Federation for Information Processing
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Anagnostopoulos, I., Anagnostopoulos, C., Vergados, D.D., Maglogiannis, I. (2006). BRWM: A relevance feedback mechanism for web page clustering. In: Maglogiannis, I., Karpouzis, K., Bramer, M. (eds) Artificial Intelligence Applications and Innovations. AIAI 2006. IFIP International Federation for Information Processing, vol 204. Springer, Boston, MA . https://doi.org/10.1007/0-387-34224-9_6
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DOI: https://doi.org/10.1007/0-387-34224-9_6
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