Weighting of Passages in Question Answering
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00101863" target="_blank" >RIV/00216224:14330/18:00101863 - isvavai.cz</a>
Result on the web
<a href="https://www.fi.muni.cz/usr/sojka/papers/raslan-2018-novotny-sojka.pdf" target="_blank" >https://www.fi.muni.cz/usr/sojka/papers/raslan-2018-novotny-sojka.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Weighting of Passages in Question Answering
Original language description
Modern text retrieval systems employ text segmentation during the indexing of documents. We show that, rather than returning the passages to the user, significant improvements are achieved on the semantic text similarity task on question answering (QA) datasets by combining all passages from a document into a single result with an aggregate similarity score. Following an analysis of the SemEval-2016 and 2017 task 3 datasets, we develop a weighted averaging operator that achieves state-of-the-art results on subtask B and can be implemented into existing search engines. Segmentation in information retrieval matters. Our results show that paying attention to important passages by using a task-specific weighting method leads to the best results on these question answering domain retrieval tasks.
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/TD03000295" target="_blank" >TD03000295: Intelligent software for semantic text search</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
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
Proceedings of the Twelve Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2018
ISBN
9788026315179
ISSN
2336-4289
e-ISSN
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Number of pages
10
Pages from-to
31-40
Publisher name
Tribun EU
Place of publication
Brno
Event location
Karlova Studánka
Event date
Dec 7, 2018
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000612420300005