PREDICTING WEB REQUESTS EFFICIENTLY USING A PROBABILITY MODEL

Shanchan Wu, Wenyuan Wang

Abstract

As the world-wide-web grows rapidly and a user's browsing experiences are needed to be personalized, the problem of predicting a user's behavior on a web-site has become important. In this paper, we present a probability model to utilize path profiles of users from web logs to predict the user's future requests. Each of the user's next probable requests is given a conditional probability value, which is calculated according to the function presented by us. Our model can give several predictions ranked by the values of their probability instead of giving one, thus increasing recommending ability. Based on a compact tree structure, our algorithm is efficient. Our result can potentially be applied to a wide range of applications on the web, including pre-sending, pre-fetching, enhancement of recommendation systems as well as web caching policies. The experiments show that our model has a good performance.

References

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Paper Citation


in Harvard Style

Wu S. and Wang W. (2004). PREDICTING WEB REQUESTS EFFICIENTLY USING A PROBABILITY MODEL . In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 972-8865-00-7, pages 48-53. DOI: 10.5220/0002622000480053


in Bibtex Style

@conference{iceis04,
author={Shanchan Wu and Wenyuan Wang},
title={PREDICTING WEB REQUESTS EFFICIENTLY USING A PROBABILITY MODEL},
booktitle={Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2004},
pages={48-53},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002622000480053},
isbn={972-8865-00-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - PREDICTING WEB REQUESTS EFFICIENTLY USING A PROBABILITY MODEL
SN - 972-8865-00-7
AU - Wu S.
AU - Wang W.
PY - 2004
SP - 48
EP - 53
DO - 10.5220/0002622000480053