Behavior-Based Web Page Evaluation

This paper describes our efforts to investigate factors in a user´s browsing behavior to help automatically evaluate Web pages that the user shows interest in. To evaluate a Web page automatically, we have developed a client-side logging/analyzing tool: the GINIS framework. We do not focus on clicking, scrolling, navigation, or duration of visit alone, but we propose integrating these patterns of interaction to recognize and evaluate a user´s response to a given Web page. Unlike most previous Web studies that have analyzed access seen at proxies or server, this work focuses primarily on client site user behavior using a customized Web browser. First, GINIS unobtrusively gathers logs of user behavior through the user´s natural interaction with the Web browser. Then it analyses the logs and extracts effective rules to evaluate Web pages using a machine-learning method. Eventually, GINIS is able to automatically evaluate Web pages using these learned rules, after which the evaluation can be utilized in a variety of user profiling