Efficient Management and Optimization of Very Large Machine Learning Dataset for Question Answering
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00114687" target="_blank" >RIV/00216224:14330/20:00114687 - isvavai.cz</a>
Result on the web
<a href="https://nlp.fi.muni.cz/raslan/raslan20.pdf#page=21" target="_blank" >https://nlp.fi.muni.cz/raslan/raslan20.pdf#page=21</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Efficient Management and Optimization of Very Large Machine Learning Dataset for Question Answering
Original language description
Question answering strategies lean almost exclusively on deep neural network computations nowadays. Managing a large set of input data (questions, answers, full documents, metadata) in several forms suitable as the first layer of a selected network architecture can be a non-trivial task. In this paper, we present the details and evaluation of preparing a rich dataset of more than 13 thousand question-answer pairs with more than 6,500 full documents. We show, how a Python-optimized database in a network environment was utilized to offer fast responses based on the 26 GiB database of input data. A global hyperparameter optimization process with controlled running of thousands of evaluation experiments to reach a near-optimum setup of the learning process is also explicated.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
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)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020
ISBN
9788026316008
ISSN
2336-4289
e-ISSN
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Number of pages
12
Pages from-to
23-34
Publisher name
Tribun EU
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2020
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
000655471300003