Inproceedings3308
Semantic Formalization of Cross-site User Browsing Behavior
Semantic Formalization of Cross-site User Browsing Behavior
Published: 2012
November
Buchtitel: Proceedings of the 2012 IEEE/WIC/ACM International Conference on Web Intelligence
Verlag: IEEE Computer Society Press
Erscheinungsort: Macao
Nicht-referierte Veröffentlichung
BibTeX
Kurzfassung
Large amounts of data are being produced daily
as detailed records of Web usage behavior, but the
task of deriving actionable knowledge from them
remains a challenge. Investigations of user browsing
behavior at multiple websites, while more beneficial
than studies restricted to a single site, still need to
tackle the problems of information heterogeneity and
mapping usage logs to meaningful events from the
application domain.
Focusing on the problem of modeling cross-site
browsing behavior, we present a formalization approach
based on a Web browsing Activity Model
(WAM). We introduce a novel two-staged approach
for the semantic enrichment of usage logs with
domain knowledge, bringing together Semantic Web
technologies and Machine Learning techniques.
For learning the semantic types of logs, we present
a supervised multi-class classification formulation,
deploying structural Support Vector Machines with
new sequential input features. We provide an implementation
of these approaches and show the results
of evaluation with real-world data.