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Mapping Documents onto Web Page Ontology

  • Dunja Mladenić
  • Marko Grobelnik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3209)

Abstract

The paper describes an approach to automatically mapping Web pages onto ontology using document classification based on the Yahoo! ontology of Web pages. Techniques developed for learning on text data are used here on the hierarchical classification structure (ontology of Web documents). The high number of features is reduced by taking into account the hierarchical structure and using feature subset selection developed for the Naive Bayesian classifier. We focus on data sets with many features that also have a highly unbalanced class distribution. Documents are represented as word-vectors that include word sequences of up to five consecutive words. Based on the hierarchical structure the problem is divided into subproblems, each representing one on the categories included in the Yahoo! hierarchy. The resulting model is a set of independent classifiers, each used to predict the probability that a new document is a member of the corresponding category represented as a node in the hierarchy. Our example problem is automatic document categorization where we want to identify documents relevant for the selected category. Usually, only about 1%-10% of examples belong to the selected category. Experimental evaluation on real-world data shows that the proposed approach gives good results. Our experimental comparison of eleven feature scoring measures show that considering data and algorithm characteristics significantly improves the performance.

Keywords

Feature Selection Information Gain Feature Subset Term Frequency Word Sequence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Dunja Mladenić
    • 1
    • 2
  • Marko Grobelnik
    • 1
  1. 1.J.Stefan InstituteLjubljanaSlovenia
  2. 2.Carnegie Mellon UniversityPittsburghUSA

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