MOTIVATION & SCOPE

Web intelligence has sought to understand and predict Web behavior in order to improve a specific exogenous outcome such as the checkout of a shopping cart or improvement in meaningful search results. More interest is given now to understanding those behaviors themselves. For instance, it is of interest to understand individual and collective Web behaviors to further model and support knowledge extraction in applications such as cybersecurity, recommendation systems, and human computation systems. This proposed symposium on behavioral Web analytics aims to bring together artificial intelligence researchers from the machine learning & planning community, the cognitive science community, social computing community, and the human-centered computing community to develop a more meaningful understanding of individual and group behavior in online environments.

TOPICS

Topics of interest include, but are not limited to the following:

Characterization of Web behavior (for example, click rate, revisit rate, session length)

Categorization of Web behavior (for example, shopping, information seeking)

Modeling Web behavior including behavioral changes (computational models, tools and techniques)

Authentication/Identification (learning methodologies for attribution)

Inferring intent from Web behavior

Assessment of Web behavior (metrics for trustworthiness, influence)

IMPORTANT DATES

Paper submission: June 12, 2013
Acceptance Notification: June 21, 2013
Camera-ready papers due: September 12, 2013
Registration deadline: September 20,2013
Symposium: November 15-17, 2013

ORGANIZING COMMITTEE
Myriam Abramson myriam.abramson@nrl.navy.mil
Nitin Agarwal nxagarwal@ualr.edu


For more information, please consult
https://sites.google.com/site/behavioralwebanalytics