Leveraging Neurodata to Support Web User Behavior Analysis

Given its complexity, understanding the behavior of users on the Web has been one of the most challenging tasks for data mining-related fields. Historically, most of the approaches have considered web logs as the main source of data. This has led to several successful cases, both in industry and academia, but has also presented several issues and limitations. Given the new challenges and the need for personalization, improvement is required in the overall understanding of the processes that lie behind web browsing decision making. The use of neurodata to support this analysis represents a huge opportunity in terms of understanding the actions taken by the user on the web in a more comprehensive way. Techniques such as eye tracking, pupil dilation and EEG analysis could provide valuable information to craft more robust models. This chapter overviews the current state of the art of the use of neurodata for web-based analysis, providing a description and analysis in terms of the feasibility and effectiveness of each strategy given a specific problem.

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