The Automated Acquisition of Topic Signatures for Text Summarization

@inproceedings{Lin2000TheAA,
  title={The Automated Acquisition of Topic Signatures for Text Summarization},
  author={Chin-Yew Lin and Eduard H. Hovy},
  booktitle={COLING},
  year={2000}
}
In order to produce a good summary, one has to identify the most relevant portions of a given text. We describe in this paper a method for automatically training topic signatures-sets of related words, with associated weights, organized around head topics and illustrate with signatures we created with 6,194 TREC collection texts over 4 selected topics. We describe the possible integration of topic signatures with outologies and its evaluaton on an automated text summarization system. 

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References

Publications referenced by this paper.
SHOWING 1-10 OF 10 REFERENCES

Automated Text Summarization In SUMMARIST

VIEW 11 EXCERPTS

Building a Large-Scale Knowledge Base for Machine Translation

VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

TextTiling: Segmenting Text into Multi-paragraph Subtopic Passages

VIEW 2 EXCERPTS

An empirical study of automated dictionary construction for information extraction in three domains

  • . EllenRilo
  • Arti cial Intelligence Journal, 85, August.
  • 1996

Accurate Methods for the Statistics of Surprise and Coincidence

  • Ted Dunning
  • Computer Science
  • Computational Linguistics
  • 1993
VIEW 1 EXCERPT

Elements of Information Theory

VIEW 1 EXCERPT

An overview of the frump system

VIEW 1 EXCERPT