期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2014
期号：ICETS
页码：1236
出版社：S&S Publications
摘要：rel ationships between consumer emotions and their buying behaviors have been well documented. Technology - savvy consumers often use the web to find information on products and services before they commit to buying. We propose a semantic web usage mining approach for discovering periodic web access patterns from annotated web usage logs which incorporates information on consumer emotions and beha viors through self - reporting and behavioral tracking. We use fuzzy logic to represent real - life temporal concepts (e.g., morning) and requested resource attributes (ontological domain concepts for the requested URLs) of peri odic pattern based web access ac tivities. These fuzzy temporal and resource representati ons, which contain both behavioral and emotional cues, are incorporated i nto a Personal Web Usage Lattice that models the user's web access activities. From this, we generate a Personal Web Usage Onto logy written in OWL, which enables semantic web applications such as personalized web resources recommendation. Finally, we demonstrate the effectiveness of our approach by presenting experimental results in the context of personalized web resources recomm endati on with varying degrees of emotional influence. Emotional influence has been found to contribute positively to adaptation in personalized recommendation.
关键词：Emotion and behavior profiling; ; behavioral tracking; recommender system; webl og ; min ; ing; knowledge discovery; on ; tology generation; ; semantic web
