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Paper Title:
A Link Classification based Approach to Website Topic Hierarchy Generation


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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