Siamese Convolutional Neural Networks for Recognizing Partial Entailment
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00115010" target="_blank" >RIV/00216224:14330/18:00115010 - isvavai.cz</a>
Result on the web
<a href="http://daz2018.fit.vutbr.cz/DaZ_WIKT_2018_Sbornik.pdf" target="_blank" >http://daz2018.fit.vutbr.cz/DaZ_WIKT_2018_Sbornik.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Siamese Convolutional Neural Networks for Recognizing Partial Entailment
Original language description
Recognizing textual entailment (RTE), i. e., a decision problem whether a sentence (called hypothesis) can be inferred from a given text, became a well established and widely studied task. As a consequence of the traditional binary (or ternary) class formulation, it is not possible to express the fact that a fragment of the hypothesis is entailed by the text, even though the “whole” entailment of the hypothesis from the text does not hold. The notions of partial textual entailment – and faceted entailment in particular – address this problem. In this paper, we introduce a siamese CNN architecture with a static attention mechanism together with a sentence compression and provide an evaluation over modified SemEval 2013 Task 8 dataset.
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Siamese Convolutional Neural Networks for Recognizing Partial Entailment
ISBN
9788021456792
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
237-242
Publisher name
Vysoké učení technické v Brně
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2018
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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