Detailed Information on Publication Record
2014
Yamraj: Binary-class and Multi-class based Textual Entailment System for Japanese (JA) and Chinese Simplified (CS)
PAKRAY, ParthaBasic information
Original name
Yamraj: Binary-class and Multi-class based Textual Entailment System for Japanese (JA) and Chinese Simplified (CS)
Authors
PAKRAY, Partha (356 India, guarantor, belonging to the institution)
Edition
Tokyo, Proceedings of the 11th NTCIR Conference on Evaluation of Information Access Technologies, p. 298-303, 6 pp. 2014
Publisher
National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430 Japan
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
storage medium (CD, DVD, flash disk)
References:
RIV identification code
RIV/00216224:14330/14:00077754
Organization unit
Faculty of Informatics
ISBN
978-4-86049-065-2
Keywords (in Czech)
ekvivalence textů; informační systémy;dolování v textech;DML-CZ;sémantika
Keywords in English
textual entailment; information systems; information retrieval; text mining
Tags
Tags
International impact
Změněno: 14/12/2014 15:49, doc. RNDr. Petr Sojka, Ph.D.
Abstract
V originále
The article presents the experiments carried out as part of the participation in Recognizing Inference in TExt and Validation (RITE-VAL) at NTCIR-11 for Japanese. RITE-VAL has two subtasks i.e. Fact Validation and System Validation subtask for Chinese-Simplified (CS), Chinese-Traditional (CT), English (EN), and Japanese (JA) and semantic relation between two texts such as entailment, contradiction, and independence. We have submitted run for Japanese (JA) System Validation (one run BC and one for MC), Chinese Simplified (CS) System Validation (one run). The Textual Entailment system used the web based Google translator system for Machine Translation purpose. The system is based on Support Vector Machine that uses features from lexical similarity, lexical distance, and syntactic similarity.
Links
LG13010, research and development project |
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MUNI/A/0765/2013, interní kód MU |
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