Automated Question Answering System for Community-Based Questions

Authors

  • Chanin Pithyaachariyakul San Francisco State University
  • Anagha Kulkarni San Francisco State University

DOI:

https://doi.org/10.1609/aaai.v32i1.12159

Keywords:

Question Answering, Query formulation, Answer ranking, Open-domain

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.

AAAI 2018 Proceedings Cover

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Published

2018-04-29

How to Cite

Pithyaachariyakul, C., & Kulkarni, A. (2018). Automated Question Answering System for Community-Based Questions. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.12159

Issue

Vol. 32 No. 1 (2018): Thirty-Second AAAI Conference on Artificial Intelligence

Section

Student Abstract Track