Web usage mining has traditionally focused on the individual queries or query words leading to a web site or web page visit, mining patterns in such data. In our work, we aim to characterize websites in terms of the semantics of the queries that lead to them by linking queries to large knowledge bases on the Web. We demonstrate how to exploit such links for more effective pattern mining on query log data. We also show how such patterns can be used to qualitatively describe the differences between competing websites in the same domain and to quantitatively predict website abandonment. Copyright is held by the International World Wide Web Conference Committee (IW3C2).
CITATION STYLE
Hollink, L., Mika, P., & Blanco, R. (2013). Web usage mining with semantic analysis. In WWW 2013 - Proceedings of the 22nd International Conference on World Wide Web (pp. 561–570). Association for Computing Machinery. https://doi.org/10.1145/2488388.2488438
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