Automated Question Answering System for Community-Based Questions

Chanin Pithyaachariyakul, Anagha Kulkarni

AAAI 2018 pp. 8131-8132

doi:10.1609/AAAI.V32I1.12159 /aaai/2018/pithyaachariyakul2018aaai-automated/

Abstract

We present our attempt at developing an efficient Question Answering system for both factoid and non-factoid questions from any domain. Empirical evaluation of our system using multiple datasets demonstrates that our system outperforms the best system from the TREC LiveQA tracks, while keeping the response time to under less than half a minute.

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Cite

Text

Pithyaachariyakul and Kulkarni. "Automated Question Answering System for Community-Based Questions." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.12159

Markdown

[Pithyaachariyakul and Kulkarni. "Automated Question Answering System for Community-Based Questions." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/pithyaachariyakul2018aaai-automated/) doi:10.1609/AAAI.V32I1.12159

BibTeX

@inproceedings{pithyaachariyakul2018aaai-automated,
  title     = {{Automated Question Answering System for Community-Based Questions}},
  author    = {Pithyaachariyakul, Chanin and Kulkarni, Anagha},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {8131-8132},
  doi       = {10.1609/AAAI.V32I1.12159},
  url       = {https://mlanthology.org/aaai/2018/pithyaachariyakul2018aaai-automated/}
}