A word clustering approach for language model-based sentence retrieval in question answering systems

@inproceedings{Momtazi2009AWC,
  title={A word clustering approach for language model-based sentence retrieval in question answering systems},
  author={Saeedeh Momtazi and Dietrich Klakow},
  booktitle={CIKM},
  year={2009}
}
In this paper we propose a term clustering approach to improve the performance of sentence retrieval in Question Answering (QA) systems. As the search in question answering is conducted over smaller segments of data than in a document retrieval task, the problems of data sparsity and exact matching become more critical. In this paper we propose Language Modeling (LM) techniques to overcome such problems and improve the sentence retrieval performance. Our proposed methods include building class… CONTINUE READING

Figures, Tables, Results, and Topics from this paper.

Key Quantitative Results

  • The results show that the methods investigated here enhanced the mean average precision of sentence retrieval from 23.62% to 29.91%.

Citations

Publications citing this paper.
SHOWING 1-10 OF 27 CITATIONS

Effective Term Weighting for Sentence Retrieval

VIEW 4 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Find relationship among applications

VIEW 7 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

UB-CQA: A user attribute based community question answering system

  • 2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)
  • 2017
VIEW 1 EXCERPT
CITES BACKGROUND

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…