Abstract

The web is pervading all walks of life and its huge increase in information volume has made the web personalization mandatory. Web Personalization may be achieved by web mining especially the web usage mining technique on the surfing behavior. Learning the surfing behavioral pattern has emerged into a promising research area to achieve web personalization. Till recently web usage mining was done on server logs on website visits and was found insufficient. The goal can be further alleviated if the task or mood of surfer is also learnt. Very shortly, a new approach of web usage mining of client or browser logs on website visits to understand the task or mood of surfer have come into view. It will make the prediction of next web pages by a surfer more accurate. Exploration of browsing behavior at browser to understand an intended task or mood of surfer is hereby termed as ‘Browsing Language’ as epitome of body language of any person. This work discusses the issues of web usage mining the client side behavior logs for single website only. Implementation of such a capability into a browser will develop the literature of browsing language and may also reduce the overhead of server in realizing web personalization.

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