Expert Systems with Applications
Volume 37, Issue 8, August 2010, Pages 5607-5613
ISSN: 09574174
CODEN: ESAPE
DOI: 10.1016/j.eswa.2010.02.052
Document Type: Article
Source Type: Journal
View at publisher|
Probabilistic neural network approach to the classification of
demonstrative pronouns for indirect anaphora in Hindi
Dutta, K.a
, Prakash, N.b
, Kaushik, S.c
a Department of Computer Science and Engineering, National Institute of Technology, Hamirpur
(HP), India
b School of Information Technology, Guru Gobind Singh Indra Prastha University, Delhi, India
c
Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, India
Abstract
In this paper, we propose the application of probabilistic neural networks (PNNs) to the classification
scheme of demonstrative pronouns for indirect anaphora in Hindi corpus. The Demonstrative Pronouns in
Hindi, "yeh"(this/it), "veh"(that/those), "iss"(this/it), and "uss"(that/those) can be personal or demonstrative.
The differentiation can be ascertained from only the situation or the context. The case marking of pronouns
further add the constraints on linguistic patterns. We propose to cast such an anaphora as a semantic
inference process, which encompasses several salient linguistic characteristic features such as grammatical
role, proximity, syntactic category and semantic cues. Our focus of study is demonstrative pronouns without
noun phrase antecedent in Hindi written corpus. We analyzed 313 news items having 3890 sentences, 3101
pronouns, of which 608 instances covered those demonstrative pronouns, which had 183 instances with
non-NP-antecedents. The effectiveness of the approach is demonstrated through set of simulations and
evaluations. © 2010 Elsevier Ltd. All rights reserved.
Language of original document
English
Author keywords
Anaphora; Neural network; Semantic
Index Keywords
Anaphora; Classification scheme; Linguistic patterns; Noun phrase; Probabilistic neural networks; Semantic
cues; Semantic inference
Engineering controlled terms: Linguistics; Semantics
Engineering main heading: Neural networks
Dutta, K.; Department of Computer Science and Engineering, National Institute of Technology, Hamirpur (HP),
India; email:kd@nitham.ac.in
© Copyright 2010 Elsevier B.V., All rights reserved.
Expert Systems with Applications
Volume 37, Issue 8, August 2010, Pages 5607-5613