An empirical evaluation of models of text document similarity

@inproceedings{Lee2005AnEE,
  title={An empirical evaluation of models of text document similarity},
  author={Michael D. Lee},
  year={2005}
}
Modeling the semantic similarity between text documents presents a significant theoretical challenge for cognitive science, with ready-made applications in information handling and decision support systems dealing with text. While a number of candidate models exist, they have generally not been assessed in terms of their ability to emulate human judgments of similarity. To address this problem, we conducted an experiment that collected repeated similarity measures for each pair of documents in… CONTINUE READING
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Comparison of hjuman and latent semantic analysis ( lsa ) judgments of pairwise document similarities for a news corpus

  • B. M. Pincombe
  • 2004
1 Excerpt

Comparison of human and latent semantic analysis ( LSA ) judgments of pairwise document similarities for a news corpus

  • B. M. Pincombe
  • 2004
1 Excerpt

Comparison of human and latent semantic analysis (LSA) judgments of pairwise document similarities for a news corpus. Defence Science and Technology Organisation Research Report DSTO–RR–0278

  • B. M. Pincombe
  • 2004
1 Excerpt