DocumentCode :
258691
Title :
Pronominal anaphora resolution using salience score for Malayalam
Author :
Athira, S. ; Lekshmi, T.S. ; Rajeev, R.R. ; Sherly, Elizabeth ; Reghuraj, P.C.
fYear :
2014
fDate :
17-18 Dec. 2014
Firstpage :
47
Lastpage :
51
Abstract :
Anaphora resolution (AR) is the process of resolving references to an entity in the discourse. The paper presents an algorithm to identify the pronominals and its antecedents in the Malayalam text input. Anaphora resolution is achieved by employing a hybrid of statistical machine learning and rule based approaches. The system is implemented by exploiting the morphological richness of the language and it makes use of parts of speech tagging, subject-object identification and person-number-gender of the NPs. We outline a simple, efficient but a naive algorithm for anaphora resolution, which computes the salience value score for each antecedents. The system performance is evaluated with precision, recall measures which produced promising results. The anaphora resolution system itself can improve the performance of many NLP applications such as text summarisation, text categorisation and term extraction.
Keywords :
natural language processing; text analysis; AR; Malayalam text input; NLP applications; person-number-gender; pronominal anaphora resolution system; salience score; salience value score; speech tagging; statistical machine learning; subject-object identification; term extraction; text categorisation; text summarisation; Accuracy; Decision trees; Hidden Markov models; Machine learning algorithms; Speech; Tagging; Training; Anaphora resolution; antecedents; discourse; pronominals; salience value;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Systems and Communications (ICCSC), 2014 First International Conference on
Conference_Location :
Trivandrum
Print_ISBN :
978-1-4799-6012-5
Type :
conf
DOI :
10.1109/COMPSC.2014.7032619
Filename :
7032619
Link To Document :
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