Exploring Web-based Translation Resources Applied to Hindi-English Cross-Lingual Information Retrieval
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AB6G3C78B" target="_blank" >RIV/00216208:11320/23:B6G3C78B - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/doi/10.1145/3569010" target="_blank" >https://dl.acm.org/doi/10.1145/3569010</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3569010" target="_blank" >10.1145/3569010</a>
Alternative languages
Result language
angličtina
Original language name
Exploring Web-based Translation Resources Applied to Hindi-English Cross-Lingual Information Retrieval
Original language description
"Internet users perceive a multilingual web but are unfamiliar with it due to communication in their regional language called Cross-Lingual Information Retrieval (CLIR). In CLIR, a translation technique is used to translate the user queries into the target documents language. Conventional translation techniques are based on either a manual dictionary or a parallel corpus. While the trending Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) techniques are trained on a parallel corpus. NMT is not so mature for Hindi-English translation, according to the literature, SMT performs better than the NMT. SMT provides a static translation due to the limited vocabularies in the available parallel corpus. It may not provide the translations for missing or unseen words while the web provides a dynamic interface where multiple users are updating information at the same time. The web may provide the translations for missing or unseen words, therefore, the web is effectively used for technically developed languages like English, German, Spanish, Russian, and Chinese. In this paper, different web resources such as Wikipedia, Hindi WordNet & Indo WordNet, ConceptNet, and online dictionary-based translation techniques are proposed and applied to Hindi-English CLIR. Wikipedia-based translation approach incorporates three modules, i.e., exactly matched, partially matched, and disambiguation to address the issues of wrong inter-wiki links, partially matched terms, and ambiguous articles. Hindi WordNet & Indo WorNet attribute ”English synset” and ConceptNet attributes ”Related term” & ”Synonymy” are used for obtaining translations. Further, WordNet path similarity is used to disambiguate translations. Various online dictionaries are available that return multiple relevant and irrelevant translations. The proposed approaches are compared to the SMT where the Wikipedia-based approach achieves approximately similar mean average precision to SMT."
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
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
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"ACM Transactions on Asian and Low-Resource Language Information Processing"
ISSN
2375-4699
e-ISSN
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Volume of the periodical
""
Issue of the periodical within the volume
2023-9
Country of publishing house
US - UNITED STATES
Number of pages
19
Pages from-to
1-19
UT code for WoS article
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EID of the result in the Scopus database
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