Abstract. Web Directories have emerged as an alternative to the Search Engines for locating information on the Web. Typically, Web Directories rely on humans putting in significant time and effort into finding important pages on the Web and categorizing them in the Directory. In this paper, we experimentally study the automatic population of a Web Directory via the use of a subject hierarchy. For our study, we have constructed a subject hierarchy for the top level topics offered in Dmoz, by leveraging ontological content from available lexical resources. We first describe how we built our subject hierarchy. Then, we analytically present how the hierarchy can help in the construction of a Directory. We also introduce a ranking formula for sorting the pages listed in every Directory topic, based on the pages' quality, and we experimentally study the efficiency of our approach against other popular methods for creating Directories.
In this paper, we introduce the HiBO bookmark management system. HiBO aims at extending the populated personal repositories (aka bookmarks) by automatically organizing their contents into topics, through the use of a built-in subject hierarchy. HiBO offers customized personalized services, such as the meaningful grouping and ordering of bookmarks within the hierarchy's topics in terms of the bookmarks' conceptual similarity to each other. HiBO also provides a framework that allows the user to customize and assist the categorization process.
Web Directories are repositories of Web pages organized in a hierarchy of topics and sub-topics. In this paper, we present Direc-toryRank, a ranking framework that orders the pages within a given topic according to how informative they are about the topic. Our method works in three steps: first, it processes Web pages within a topic in order to extract structures that are called lexical chains, which are then used for measuring how informative a page is for a particular topic. Then, it measures the relative semantic similarity of the pages within a topic. Finally, the two metrics are combined for ranking all the pages within a topic before presenting them to the users.
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