Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06) (2006)
Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.49
Colin DeLong , University of Minnesota
Sandeep Mane , University of Minnesota
Jaideep Srivastava , University of Minnesota
In ranking algorithms for web graphs, such as PageRank and HITS, the lack of attention to concepts/topics representing web page content causes problems such as topic drift and mutually reinforcing relationships between hosts. This paper proposes a novel approach to expand the Web graph to incorporate conceptual information encoded by links (anchor text) between web pages. Using web graph link structure and conceptual information associated with each web page (automatically extracted from anchor text of inlinks), a new graph is defined where each node represents a unique pair of a web page and concept associated with that web page, and an edge represents an explicit or implicit link between two such nodes. This graph captures inter-concept relationships, which is then utilized by ranking algorithms. Our experimental results show that such an approach improves accuracy (e.g., first X precision) by retrieving links which are more authoritative given a user?s context.
J. Srivastava, C. DeLong and S. Mane, "Concept-Aware Ranking: Teaching an Old Graph New Moves," Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)(ICDMW), Hong Kong, China, 2006, pp. 80-88.