Titlebook: WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles; 4th International Wo Osmar R. Zaïane,Jaideep Srivastava,Brij Mas

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LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition,99% [Heer02b]. In this paper, we describe the further development of this work into a prototype service called LumberJack, a push-button analysis system that is both more automated and accurate than past systems.

glowing

Mining eBay: Bidding Strategies and Shill Detection, that might lead to the identified behaviors. We then apply a clustering algorithm to look at each bidder’s behavior across several engagements, and find a few natural clusters. Finally, we apply association rule analysis to the data and find cases of likely shill behavior, but find no cross-correlation with any particular bidding behavior.

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矛盾心理

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Coping with Sparsity in a Recommender System,nts", artificial users that rate in accordance with some predefined preferences. We show that both ideas pay off, albeit in different ways: Transitive correlations provide a small help for virtually no price, whereas rating agents improve the coverage of the system significantly but also have a negative impact on the system performance.

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