International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Science | Sudan | Volume 9 Issue 2, February 2020


Domain-Speci?c View of Semantic

Yousif Haroon | Mohsen Rshwan


Abstract: This paper investigates how universal pre-trained embedding can be adapted to handle the diversity of semantic in specific domains. And present a novel adapting method that relies on the view of semantic constraints to adapt an off the shelf word embedding to close fit the view of the semantics of the target domain. The view of semantic constraints are extracted from quite available resources, a text corpus and a domain-specific dictionary. The view of semantic extraction eliminates the need for rare special-purpose semantic resources and the additional effort for locally trained embedding. The method is implemented as a lightweight final tuning process. The results show that our method outperformed the state of the art embedding adapting methods in the task of Community Question Answering (CQA) for the Arabic medical domain.


Keywords: Word Embedding, Embedding Adaptation, Query Expansion, Transfer Learning, NLP


Edition: Volume 9 Issue 2, February 2020,


Pages: 691 - 696


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How to Cite this Article?

Yousif Haroon, Mohsen Rshwan, "Domain-Speci?c View of Semantic", International Journal of Science and Research (IJSR), Volume 9 Issue 2, February 2020, pp. 691-696, https://www.ijsr.net/get_abstract.php?paper_id=SR20210124238

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