Download Advances in Web Mining and Web Usage Analysis: 8th by Olfa Nasraoui, Myra Spiliopoulou, Jaideep Srivastava, PDF

By Olfa Nasraoui, Myra Spiliopoulou, Jaideep Srivastava, Bamshad Mobasher, Brij Masand

This publication constitutes the completely refereed post-proceedings of the eighth foreign Workshop on Mining net facts, 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 rigorously chosen for inclusion within the booklet. the improved papers convey new applied sciences from components like adaptive mining tools, circulation mining algorithms, strategies for the Grid, specially flat texts, files, images and streams, usability, e-commerce functions, personalization, and suggestion engines.

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Sample text

Nearest-neighbor CF is based either on common user or item similarities, to form the user’s neighborhood. The effectiveness of the aforementioned approaches would be augmented, if we could combine them. In this paper, we use biclustering to disclose this duality between users and items, by grouping them in both dimensions simultaneously. We propose a novel nearest-biclusters algorithm, which uses a new similarity measure that achieves partial matching of users’ preferences. We apply nearest-biclusters in combination with a biclustering algorithm – Bimax – for constant values.

28 K. Beemanapalli, R. Rangarajan, and J. 1 Test Data We have run our experiments on the CS website which is the Computer Science Department website of the University of Minnesota. edu [17]. The usage data has been collected over a period of 2 weeks in Apr 2006. The data set has been reduced to about 100,000 user sessions by refining and filtering the data. Noise data such as one page sessions, broken sessions etc have been removed to reduce the negative impact on the algorithm. We have implemented a web crawler to spider the website and collect the link information.

A part of the session data was used to train the model and then the model was tested on the remaining sessions. The next page that will be accessed was predicted for the test sessions and if the predicted page was actually accessed later on it the session, it was considered a hit. The definitions of the various measures used to measure the effectiveness of these models as taken from [3] are restated below: • Hit Ratio (HR): Percentage of hits. If a recommended page is actually requested later in the session, we declare a hit.

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