Detailed Information on Publication Record
2014
An Architecture for Scientific Document Retrieval Using Textual and Math Entailment Modules
PAKRAY, Partha and Petr SOJKABasic information
Original name
An Architecture for Scientific Document Retrieval Using Textual and Math Entailment Modules
Authors
PAKRAY, Partha (356 India, belonging to the institution) and Petr SOJKA (203 Czech Republic, guarantor, belonging to the institution)
Edition
Brno, Eighth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2014, p. 107-117, 11 pp. 2014
Publisher
Tribun EU
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Czech Republic
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
printed version "print"
References:
RIV identification code
RIV/00216224:14330/14:00077458
Organization unit
Faculty of Informatics
ISSN
UT WoS
000374560500014
Keywords (in Czech)
reprezentace jazyka; výběr významu; výběr významového slova; výběr významu slova; diskretizace reprezentace; reprezentace významu; empirická lingvistika
Keywords in English
natural language representation; priming; lexical priming; semantic priming; data discretization; language modelling; representation of meaning; personal mental lexicon; empirical linguistics
Tags
International impact
Změněno: 11/1/2017 09:50, doc. RNDr. Petr Sojka, Ph.D.
Abstract
V originále
We present an architecture for scientific document retrieval. An existing system for textual and math-ware retrieval Math Indexer and Searcher MIaS is designed for extensions by modules for textual and math-aware entailment. The goal is to increase quality of retrieval (precision and recall) by handling natural languge variations of expressing semantically the same in texts and/or formulae. Entailment modules are designed to use several, ordered layers of processing on lexical, syntactic and semantic levels using natural language processing tools adapted for handling tree structures like mathematical formulae. If these tools are not able to decide on the entailment, generic knowledge databases are used deploying distributional semantics methods and tools. It is shown that sole use of distributional semantics for semantic textual entailment decisions on sentence level is surprisingly good. Finally, further research plans to deploy results in the digital mathematical libraries are outlined.
Links
LG13010, research and development project |
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250503, interní kód MU |
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