Recurrent Networks in AQA Answer Selection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00101541" target="_blank" >RIV/00216224:14330/18:00101541 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Recurrent Networks in AQA Answer Selection
Original language description
Unlimited, or open domain, question answering system AQA is being developed and tested with the Simple Question Answering Data-base (SQAD) for the Czech language. AQA is optimized for work with morphologically rich languages and makes use of syntactic cues provided by the morphosyntactic analysis. In this paper, we introduce a new answer selection module being developed for the AQA system. The module is based on recurrent neural networks processing the question and answer sentences to derive the most probable answer sentence. We present the details of the module architecture and offer a detailed evaluation of various hyperparameter setups. The module is trained and tested with 8,500 question-answer pairs using the SQAD v2.1 benchmark dataset.
Czech name
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Czech description
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Project
<a href="/en/project/GA18-23891S" target="_blank" >GA18-23891S: Hyperintensional Reasoning over Natural Language Texts</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the Twelfth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2018
ISBN
9788026315179
ISSN
2336-4289
e-ISSN
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Number of pages
10
Pages from-to
53-62
Publisher name
Tribun EU
Place of publication
Brno
Event location
Karlova Studánka
Event date
Jan 1, 2018
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000612420300007

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