WEB USAGE MINING OF ONLINE CONSUMER BEHAVIOR USING SPATIAL AND TEMPORAL INFORMATION
Publication Date : 01/03/2016
The web has become an increasingly popular medium for consumer to exchange or find ideas, opinions, experiences on products and services. Many consumers go further than online information sharing and actually perform purchases on the web. The documentation may contain the relationships between consumer emotions and their buying behaviors. Technology-savvy consumers often use the web to find information on products and services before they commit to buying. The project proposes 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. The project uses fuzzy logic to represent real-life temporal concepts (e.g., morning) and requested resource attributes (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 data that models the user’s web access activities. From this, a Personal Web Usage is generated, which enables web applications such as personalized web resources recommendation. Emotional influence has been found to contribute positively to adaptation in personalized recommendation.
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