Sentence and Word Embedding Employed in Open Question-Answering
Marek Medveď, Aleš Horák
2018
Abstract
The Automatic Question Answering, or AQA, system is a representative of open domain QA systems, where the answer selection process leans on syntactic and semantic similarities between the question and the answering text snippets. Such approach is specifically oriented to languages with fine grained syntactic and morphologic features that help to guide the correct QA match. In this paper, we present the latest results of the AQA system with new word embedding criteria implementation. All AQA processing steps (question processing, answer selection and answer extraction) are syntax-based with advanced scoring obtained by a combination of several similarity criteria (TF-IDF, tree distance, ...). Adding the word embedding parameters helped to resolve the QA match in cases, where the answer is expressed by semantically near equivalents. We describe the design and implementation of the whole QA process and provide a new evaluation of the AQA system with the word embedding criteria measured with an expanded version of Simple Question-Answering Database, or SQAD, with more than 3,000 question-answer pairs extracted from the Czech Wikipedia.
DownloadPaper Citation
in Harvard Style
Medveď M. and Horák A. (2018). Sentence and Word Embedding Employed in Open Question-Answering.In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-275-2, pages 486-492. DOI: 10.5220/0006595904860492
in Bibtex Style
@conference{icaart18,
author={Marek Medveď and Aleš Horák},
title={Sentence and Word Embedding Employed in Open Question-Answering},
booktitle={Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2018},
pages={486-492},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006595904860492},
isbn={978-989-758-275-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Sentence and Word Embedding Employed in Open Question-Answering
SN - 978-989-758-275-2
AU - Medveď M.
AU - Horák A.
PY - 2018
SP - 486
EP - 492
DO - 10.5220/0006595904860492