PhD Thesis

When the Answer comes into Question in Question-Answering

Ana Cristina Bastos Mendes2013

Key information

Authors:

Ana Cristina Bastos Mendes (Ana Cristina Bastos Mendes)

Supervisors:

Maria Luísa Torres Ribeiro Marques da Silva Coheur (Maria Luísa Torres Ribeiro Marques da Silva Coheur)

Published in

10/16/2013

Abstract

A Question-Answering system aims at returning correct answers to questions posed in natural language. The typical architecture of a Question-Answering system includes a component dedicated to Answer Extraction, which is the focus of this thesis. This thesis starts by presenting Just.Ask, the Question-Answering system developed during the course of these Ph.D. studies, that represents the baseline and the target of all the experiments. Afterwards, the tasks of candidate answer extraction and final answer selection are addressed. The former uses (lexico-syntactic) patterns, automatically learned from largescale information sources using a minimally supervised approach. In the latter, semantic relations – equivalence and inclusion – are detected between the candidate answers and used to better choose the final answer. Finally, a new approach to the Question-Answering challenge is presented, making Just. Ask the first system, to the best of our knowledge, which uses the correct answers to past questions to answer future questions, employing the learned patterns. In this approach, the user has a fundamental role that allows the learning process to be triggered: s/he confirms the correctness of the system’s answer(s). However, if none of the returned answers is correct, the user can provide the correct answer to the posed question.

Publication details

Authors in the community:

Supervisors of this institution:

RENATES TID

101296584

Degree Name

Doutoramento em Engenharia Informática e de Computadores

Fields of Science and Technology (FOS)

electrical-engineering-electronic-engineering-information-engineering - Electrical engineering, electronic engineering, information engineering

Keywords

  • Question-Answering Systems
  • Candidate Answer Extraction
  • Lexico-syntactic Patterns
  • Pattern Learning
  • Pattern/Sentence Unification
  • Relaxation Strategies
  • Final Answer Selection
  • Semantic
  • Relations
  • Learning to Answer
  • User Feedback

Publication language (ISO code)

eng - English

Rights type:

Embargo lifted

Date available:

08/11/2014

Institution name

Instituto Superior Técnico