| Type of Material: | Thesis |
| Title: | Devolopment of San ani Arabic Parts of Speech Tagger A BI GRUs CRF Model |
| Researcher: | Sabah Mohammed Mohammed Nasser Al-Shehabi |
| Guide: | Rajyarama, K |
| Department: | Centre for Applied Linguistics and Translation Studies |
| Publisher: | University of Hyderabad, Hyderabad |
| Place: | Hyderabad |
| Year: | 2021 |
| Language: | English |
| Subject: | Arts and Humanities | Language | Language and Linguisticsn | Comparative Literature | Arts, Humanities and Languages |
| Dissertation/Thesis Note: | PhD; Centre for Applied Linguistics and Translation Studies, University of Hyderabad, Hyderabad, Hyderabad |
| Fulltext: | Shodhganga |
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| 001 | 448554 | |
| 003 | IN-AhILN | |
| 005 | 2023-07-24 15:37:38 | |
| 008 | __ | 230724t2021||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_448554 |
| 040 | __ | |aHYDR_500046|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aSabah Mohammed Mohammed Nasser Al-Shehabi|eResearcher |
| 110 | __ | |aCentre for Applied Linguistics and Translation Studies|bUniversity of Hyderabad, Hyderabad|dHyderabad|ein |
| 245 | __ | |aDevolopment of San ani Arabic Parts of Speech Tagger A BI GRUs CRF Model |
| 260 | __ | |aHyderabad|bUniversity of Hyderabad, Hyderabad|c2021 |
| 300 | __ | |a218p.|dNone |
| 502 | __ | |cCentre for Applied Linguistics and Translation Studies, University of Hyderabad, Hyderabad, Hyderabad|bPhD |
| 518 | __ | |oDate of Award|d2021 |
| 518 | __ | |oDate of Registration|d2015 |
| 520 | __ | |aOne of the essential pre-processing tasks for building and improving NLP applications is known as parts-of-speech tagging. The tagging process involves the assigning of an appropriate part of speech tag to each word/token in a text. It also plays a fundamental role in developing many natural language processing applications such as syntactic parsing, named-entity recognition, automatic translation, ontology engineering, question answering, and information retrieval.newlineIn Arabic Natural Language Processing (NLP), the undivided attention of research was directed to Modern Standard Arabic (MSA) and occasionally Classical Arabic. The main bulk of research placed MSA in the spotlight, avoiding other Arabic forms. However, during the last decade, the situation has been changing. The prevalence of dialectal interchange through social media platforms gradually drives attention towards Arabic dialects.newlineNowadays, work on dialectal Arabic NLP is still in elementary stages due to several challenges, including |
| 650 | __ | |aComparative Literature|2UGC |
| 650 | __ | |aArts, Humanities and Languages|2AIU |
| 653 | __ | |aArts and Humanities |
| 653 | __ | |aLanguage |
| 653 | __ | |aLanguage and Linguisticsn |
| 700 | __ | |aRajyarama, K|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/413698|yShodhganga |
| 905 | __ | |afromsg |
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