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Issue No.02 - April-June (2012 vol.3)
pp: 152-164
Guan Hong , Dept. of Comput., Unitec, Auckland, New Zealand
The relationships 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 behaviors 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 periodic pattern-based web access activities. These fuzzy temporal and resource representations, which contain both behavioral and emotional cues, are incorporated into a Personal Web Usage Lattice that models the user's web access activities. From this, we generate a Personal Web Usage Ontology 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 recommendation with varying degrees of emotional influence. Emotional influence has been found to contribute positively to adaptation in personalized recommendation.
recommender systems, consumer behaviour, data mining, fuzzy logic, Internet, ontologies (artificial intelligence), personalized Web resources recommendation, consumer emotion, behavior analysis, buying behaviors, technology-savvy consumers, semantic Web usage mining approach, periodic Web access patterns discovering, annotated web usage logs, consumer behaviors, self-reporting, behavioral tracking, fuzzy logic, real-life temporal concepts, periodic pattern-based Web access activities, fuzzy temporal representations, resource representations, personal Web usage lattice, personal Web usage ontology, OWL, Ontologies, Semantic Web, Context, Lattices, Association rules, Semantics, semantic web., Emotion and behavior profiling, behavioral tracking, adaptation in mid to long-term interaction, consumer habits, personalization, recommender system, weblog mining, knowledge discovery, ontology generation
Guan Hong, "Generation of Personalized Ontology Based on Consumer Emotion and Behavior Analysis", IEEE Transactions on Affective Computing, vol.3, no. 2, pp. 152-164, April-June 2012, doi:10.1109/T-AFFC.2011.22
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