Locality discriminating indexing for document classification

ABSTRACT

This paper introduces a locality discriminating indexing (LDI) algorithm for document classification. Based on the hypothesis that samples from different classes reside in class-specific manifold structures, LDI seeks for a projection which best preserves the within-class local structures while suppresses the between-class overlap. Comparative experiments show that the proposed method isable to derives compact discriminating document representations for classification.

REFERENCES

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• 2: Xiaofei He , Deng Cai , Haifeng Liu , Wei-Ying Ma, Locality preserving indexing for document representation, Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, July 25-29, 2004, Sheffield, United Kingdom [doi>10.1145/1008992.1009012]
• 3: F. R. K. Chung. Spectral graph theory. American Mathematical Society, AMS Press, 1997.
• 4: Fabrizio Sebastiani, Machine learning in automated text categorization, ACM Computing Surveys (CSUR), v.34 n.1, p.1-47, March 2002 [doi>10.1145/505282.505283]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Indexing methods

General Terms:
Algorithms

Keywords:
document classification, document indexing, manifold analysis