Although web navigation hierarchies, such as Yahoo.com and Open Directory Project, enable effective browsing, their individual nodes cannot be indexed for search independently. This is because contents of the individual nodes in a hierarchy are related to the contents of their neighbors, ancestors, and descendants in the structure. In this paper, we show that significant improvements in precision can be obtained by leveraging knowledge about the structure of hierarchical web content. In particular, we propose a novel keyword weight propagation technique to properly enrich the data nodes in web hierarchies. Our approach relies on leveraging the context provided by neighbor entries in a given structure. We leverage this information for developing relativecontent preserving keyword propagation schemes. We compare the results obtained through proposed hierarchically-informed keyword weight (pre-) propagation schemes to existing state-of-the-art score and keyword propagation techniques and show that our approach significantly improves the precision. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Kim, J. W., & Candan, K. S. (2007). Leveraging structural knowledge for hierarchically-informed keyword weight propagation in the web. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4811 LNAI, pp. 72–91). Springer Verlag. https://doi.org/10.1007/978-3-540-77485-3_5
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