AUTOMATIC MAINTENANCE OF WEB DIRECTORIES BY MINING WEB BROWSING DATA

Authors

  • CARLOS HURTADO Faculty of Engineering and Science, Universidad Adolfo Ib´a˜nez Diagonal Las Torres 2640, Santiago, Chile
  • MARCELO MENDOZA Computer Science Department, Universidad T´ecnica Federico Santa Mar´ıa Vicu˜na Mackenna 3939, Santiago, Chile

Keywords:

Web directories, Web Mining, Query Logs

Abstract

Web directories allow Web users to browse a hierarchy of categories, under which di- fferent types of resources are classified. We study the problem of maintaining a Web directory, that is, the problem of continually discovering and ranking resources that are relevant to the categories of the directory. We propose an unsupervised computational method that conducts the maintenance of the directory by analyses of user browsing data. The method is based on the extraction and classification of user sessions (se- quences of resources selected by users) into the categories of the directory. In addition, we show that the directory maintenance method can be slightly modified to find queries that are useful to find relevant resources allowing users to switch from directory browsing to query formulation. Experimental results allow for affirmation that the proposed me- thods are effective, that they attain identification of new pages in each category and also recommend related queries with high precision, without needing labeled data to conduct traditional web page and query classification tasks.

 

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Published

2011-09-29

How to Cite

HURTADO, C. ., & MENDOZA, M. . (2011). AUTOMATIC MAINTENANCE OF WEB DIRECTORIES BY MINING WEB BROWSING DATA. Journal of Web Engineering, 10(2), 153–173. Retrieved from https://journals.riverpublishers.com/index.php/JWE/article/view/3977

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