Download Advanced Techniques in Web Intelligence-2: Web User Browsing by Pablo E. Román, Juan D. Velásquez (auth.), Juan D. PDF

By Pablo E. Román, Juan D. Velásquez (auth.), Juan D. Velásquez, Vasile Palade, Lakhmi C. Jain (eds.)

ISBN-10: 3642333257

ISBN-13: 9783642333255

This study quantity specializes in examining the internet consumer searching behaviour and personal tastes in conventional web-based environments, social networks and net 2.0 purposes, by utilizing complex thoughts in facts acquisition, info processing, trend extraction and cognitive technological know-how for modeling the human activities.
The publication is directed to graduate scholars, researchers/scientists and engineers drawn to updating their wisdom with the hot developments in net consumer research, for constructing the following iteration of web-based platforms and functions.

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Extra info for Advanced Techniques in Web Intelligence-2: Web User Browsing Behaviour and Preference Analysis

Example text

For this, several methods have been proposed, ranging from basic heuristics to complex optimization formulations. 3. Applications regarding how to collect and process information about the feedback of Web users is presented. In this case, the nature of the data can be either explicit or implicit, contributed by the end users as they interact with a particular website. 4, main concepts regarding implicit and explicit relevance feedback collection and processing techniques are introduced, as well as a discussion on how eye tracking devices have been used to improve the understanding of the end user.

Web users are proposed to be “information foragers” where their utility is based on a TF-IDF text measure [56]. Using such a specification the SNIF-ACT browsing model has been proposed [67].

The merging process is usually related to the fact that information might be distributed over several Web servers, and a synchronization process must be performed. Once the data is cleaned and merged, the process of user session identification (or sessionization) is fundamental for most of Web usage mining applications. For this, several methods have been proposed, ranging from basic heuristics to complex optimization formulations. 3. Applications regarding how to collect and process information about the feedback of Web users is presented.

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