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Named-entity recognition for Hindi language using context pattern-based maximum entropy

Autorzy
Jain Arti , Yadav Divakar , Arora Anuja , Tayal Devendra K.
Treść / Zawartość
Pełne teksty:
Jain.pdf
Identyfikatory
DOI
10.7494/csci.2022.23.1.3977
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper describes a named-entity-recognition (NER) system for the Hindi language that uses two methodologies: an existing baseline maximum entropy-based named-entity (BL-MENE) model, and the proposed context pattern-based MENE (CP-MENE) framework. BL-MENE utilizes several baseline features for the NER task but suffers from inaccurate named-entity (NE) boundary detection, misclassification errors, and the partial recognition of NEs due to certain missing essentials. However, the CP-MENE-based NER task incorporates extensive features and patterns that are set to overcome these problems. In fact, CP-MENE’s features include right-boundary, left-boundary, part-of-speech, synonym, gazetteer and relative pronoun features. CP-MENE formulates a kind of recursive relationship for extracting highly ranked NE patterns that are generated through regular expressions via Python@ code. Since the web content of the Hindi language is arising nowadays (especially in health care applications), this work is conducted on the Hindi health data (HHD) corpus (which is readily available from the Kaggle dataset). Our experiments were conducted on four NE categories; namely, Person (PER), Disease (DIS), Consumable (CNS), and Symptom (SMP).
Słowa kluczowe
EN
Wydawca
Wydawnictwa AGH
Czasopismo
Computer Science
Rocznik
2022
Tom
T. 23 (1)
Strony
81--115
Opis fizyczny
Bibliogr. 141 poz., rys., tab.
Twórcy
autor
Jain Arti
ajain.jiit@gmail.com
  • Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India
autor
Yadav Divakar
divakar.yadav0@gmail.com
  • Divakar Yadav NIT Hamirpur, Himachal Pradesh, India
autor
Arora Anuja
anuja.arora29@gmail.com
  • Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India
autor
Tayal Devendra K.
dev_tayal2001@yahoo.com
  • Indira Gandhi Delhi Technical University for Women, New Delhi, India
Bibliografia
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Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
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Bibliografia
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