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Information 2018, 9(9), 228; https://doi.org/10.3390/info9090228

A Web Page Clustering Method Based on Formal Concept Analysis

School of Information Science and Engineering, Central South University, Changsha 410000, China
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Received: 21 August 2018 / Revised: 31 August 2018 / Accepted: 2 September 2018 / Published: 6 September 2018
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Abstract

Web page clustering is an important technology for sorting network resources. By extraction and clustering based on the similarity of the Web page, a large amount of information on a Web page can be organized effectively. In this paper, after describing the extraction of Web feature words, calculation methods for the weighting of feature words are studied deeply. Taking Web pages as objects and Web feature words as attributes, a formal context is constructed for using formal concept analysis. An algorithm for constructing a concept lattice based on cross data links was proposed and was successfully applied. This method can be used to cluster the Web pages using the concept lattice hierarchy. Experimental results indicate that the proposed algorithm is better than previous competitors with regard to time consumption and the clustering effect. View Full-Text
Keywords: formal concept analysis; feature weight; cross linked list; concept lattice; Web page clustering formal concept analysis; feature weight; cross linked list; concept lattice; Web page clustering
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Zhang, Z.; Zhao, J.; Yan, X. A Web Page Clustering Method Based on Formal Concept Analysis. Information 2018, 9, 228.

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