Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/7542
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dc.contributor.authorKeshava, V.-
dc.contributor.authorAvvara, P.-
dc.contributor.authorSowmya, Kamath S.-
dc.contributor.authorGeetha, V.-
dc.date.accessioned2020-03-30T10:02:29Z-
dc.date.available2020-03-30T10:02:29Z-
dc.date.issued2018-
dc.identifier.citationProceedings of the 2017 International Conference on Asian Language Processing, IALP 2017, 2018, Vol.2018-January, , pp.127-130en_US
dc.identifier.urihttps://idr.nitk.ac.in/jspui/handle/123456789/7542-
dc.description.abstractDomain-specific taxonomies constitute a valuable resource as they offer extensive support in information retrieval related activities like browsing, searching, recommendations and personalization. Such taxonomies can bridge the gap between the lack of domain-specific querying knowledge in potential users and the actual content. In case of multilingual content, taxonomies can play a pivotal role in boosting search performance for content across language barriers. In this paper, a domain-agnostic framework for building an evolving, domain-specific taxonomy for the Hindi, given a set of well-organized data points is proposed. The approach is intended for designing a hierarchical taxonomy enriched with synonyms and other morphological variants using WordNet and Word2vec models respectively. The hierarchical structure acts as a base which binds the taxonomy to a given domain. Such enrichment can improve taxonomy coverage within the given domain. The focus is also on building a taxonomy that can self-evolve over time, with high precision and recall, with minimal manual effort. � 2017 IEEE.en_US
dc.titleConstructing an enriched domain taxonomy for Hindi using word embeddingsen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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