By Olfa Nasraoui, Myra Spiliopoulou, Jaideep Srivastava, Bamshad Mobasher, Brij Masand
This publication constitutes the completely refereed post-proceedings of the eighth overseas Workshop on Mining net info, WEBKDD 2006, held in Philadelphia, PA, united states in August 2006 along side the twelfth ACM SIGKDD overseas convention on wisdom Discovery and knowledge Mining, KDD 2006.
The thirteen revised complete papers awarded including a close preface went via rounds of reviewing and development and have been conscientiously chosen for inclusion within the booklet. the improved papers convey new applied sciences from components like adaptive mining tools, move mining algorithms, recommendations for the Grid, in particular flat texts, records, photographs and streams, usability, e-commerce purposes, personalization, and advice engines.
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Additional resources for Advances in Web Mining and Web Usage Analysis: 8th International Workshop on Knowledge Discovery on the Web, WebKDD 2006 Philadelphia, USA, August 20,
Clickstream clustering using weighted longest common subsequences. In: Proc. of the Workshop on Web Mining, SIAM Conference on Data Mining, pp. 33–40 (2001) 4. : Improving www proxies performance with greedy-dual-sizefrequency caching policy. HP Laboratories Report No. HPL-98-69R1 (1998) 5. : Web mining: Information and pattern discovery on the world wide web. In: ICTAI 1997. Proceedings of the 9th IEEE International Conference on Tools with Artiﬁcial Intelligence, IEEE, Los Alamitos (1997) 6.
MAE represents the absolute diﬀerences between the real and the predicted values and is an extensively used metric. From our experimental study (Section 5) we understood that MAE is able to characterize the accuracy of prediction, but is not indicative for the accuracy of recommendation. Since in real-world recommender systems the experience of users mainly depends on the accuracy of recommendation, MAE may not be the preferred measure. For this reason we focus on widely accepted metrics from information retrieval.
ACM Press, New York (2001) 14. , Inc. com 15. : Web-log mining for quantitative temporal-event prediction. IEEE Computational Intelligence Bulletin 1(1), 10–18 (2002) 16. : Web-log mining for predictive web caching. edu Abstract. A number of methods exists that measure the distance between two web pages. Average-Clicks is a new measure of distance between web pages which fits user’s intuition of distance better than the traditional measure of clicks between two pages. Average-Clicks however assumes that the probability of the user following any link on a web page is the same and gives equal weights to each of the out-going links.
Advances in Web Mining and Web Usage Analysis: 8th International Workshop on Knowledge Discovery on the Web, WebKDD 2006 Philadelphia, USA, August 20, by Olfa Nasraoui, Myra Spiliopoulou, Jaideep Srivastava, Bamshad Mobasher, Brij Masand