Open Access

ARTICLE

Extraction of Opinion Target Using Syntactic Rules in Urdu Text

Toqir A. Rana^1,*, Bahrooz Bakht¹, Mehtab Afzal¹, Natash Ali Mian², Muhammad Waseem Iqbal³, Abbas Khalid¹, Muhammad Raza Naqvi⁴

1 Department of Computer Science and IT, The University of Lahore, Lahore, 54000, Pakistan
2 School of Computer Science and Information Technology, Beaconhouse National University, Lahore, 54000, Pakistan
3 Department of Computer Science and IT, The Superior College (University Campus), Lahore, 54000, Pakistan
4 Universite de Toulouse Ecole, Nationale d’lng enieurs de Tarbes ENIT, Tarbes, 65000, France

* Corresponding Author: Toqir A. Rana. Email:

Intelligent Automation & Soft Computing 2021, 29(3), 839-853. https://doi.org/10.32604/iasc.2021.018572

Received 12 March 2021; Accepted 13 April 2021; Issue published 01 July 2021

Abstract

Opinion target or aspect extraction is the key task of aspect-based sentiment analysis. This task focuses on the extraction of targeted words or phrases against which a user has expressed his/her opinion. Although, opinion target extraction has been studied extensively in the English language domain, with notable work in other languages such as Chinese, Arabic etc., other regional languages have been neglected. One of the reasons is the lack of resources and available texts for these languages. Urdu is one, with millions of native and non-native speakers across the globe. In this paper, the Urdu language domain is focused on to identify opinion targets from written Urdu texts. To accomplish this task, several syntactic rules are crafted to identify users’ opinions and associated target words. These rules are crafted using the grammatical and linguistic context of the words in the sentence. To the best of our knowledge, there is no existing work available in the Urdu domain for opinion target extraction. The proposed methodology is evaluated on an Urdu language dataset and compared with an existing approach for the English language by applying the same technique. The experiments have demonstrated that the proposed approach achieves promising performance as compared to the applied English language domain approach.

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