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ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Hypertext Categorization using Hyperlink Patterns and Meta Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
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AusDM '06 Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61
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Floatcascade learning for fast imbalanced web mining
Proceedings of the 17th international conference on World Wide Web
Automatic Recognition of News Web Pages
PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Query-log mining for detecting spam
AIRWeb '08 Proceedings of the 4th international workshop on Adversarial information retrieval on the web
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ACM Computing Surveys (CSUR)
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ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
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Proceedings of the 18th ACM conference on Information and knowledge management
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Tensor Framework and Combined Symmetry for Hypertext Mining
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IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
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It is well known that Web-page classification can be enhanced by using hyperlinks that provide linkages between Web pages. However, in the Web space, hyperlinks are usually sparse, noisy and thus in many situations can only provide limited help in classification. In this paper, we extend the concept of linkages from explicit hyperlinks to implicit links built between Web pages. By observing that people who search the Web with the same queries often click on different, but related documents together, we draw implicit links between Web pages that are clicked after the same queries. Those pages are implicitly linked. We provide an approach for automatically building the implicit links between Web pages using Web query logs, together with a thorough comparison between the uses of implicit and explicit links in Web page classification. Our experimental results on a large dataset confirm that the use of the implicit links is better than using explicit links in classification performance, with an increase of more than 10.5% in terms of the Macro-F1 measurement.