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A link classification based approach to website topic hierarchy generation
Conference proceeding

A link classification based approach to website topic hierarchy generation

Nan Liu and Christopher C. Yang
Proceedings of the 16th international conference on World Wide Web, pp 1127-1128
08 May 2007
DOI: https://doi.org/10.1145/1242572.1242728

Abstract

Information systems -- Information retrieval Information systems -- Information retrieval -- Information retrieval query processing Information systems -- Information retrieval -- Retrieval models and ranking Information systems -- Information retrieval -- Retrieval tasks and goals -- Clustering and classification Information systems -- Information systems applications -- Data mining -- Clustering
Hierarchical models are commonly used to organize a Website's content. A Website's content structure can be represented by a topic hierarchy, a directed tree rooted at a Website's homepage in which the vertices and edges correspond to Web pages and hyperlinks. In this work, we propose a new method for constructing the topic hierarchy of a Website. We model the Website's link structure using weighted directed graph, in which the edge weights are computed using a classifier that predicts if an edge connects a pair of nodes representing a topic and a sub-topic. We then pose the problem of building the topic hierarchy as finding the shortest-path tree and directed minimum spanning tree in the weighted graph. We've done extensive experiments using real Websites and obtained very promising results.

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9 citations in Scopus

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