DirectoryRank

Krikos, Vlassis; Stamou, Sofia; Kokosis, Pavlos; Ntoulas, Alexandros; Christodoulakis, Dimitris

doi:10.1145/1097047.1097052

Cited by 8 publications

References 8 publications

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Classifying Web Data in Directory Structures

Stamou¹,

Ntoulas

Krikos³

et al. 2006

Frontiers of WWW Research and Development - APWeb 2006

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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.

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Classifying Web Data in Directory Structures

Stamou¹,

Ntoulas

Krikos³

et al. 2006

Frontiers of WWW Research and Development - APWeb 2006

Self Cite

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Improving Hierarchical Taxonomy Integration with Semantic Feature Expansion on Category-Specific Terms

Yang¹,

Chen²,

Hung³

et al.

Information Retrieval Technology

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In recent years, the hierarchical taxonomy integration problem has obtained considerable attention in many research studies. Many types of implicit information embedded in the source taxonomy are explored to improve the integration performance. The semantic information embedded in the source taxonomy, however, has not been discussed in previous research. In this paper, an enhanced integration approach called SFE (Semantic Feature Expansion) is proposed to exploit the semantic information of the category-specific terms. From our experiments on two hierarchical Web taxonomies, the results show that the integration performance can be further improved with the SFE scheme.

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