Rahim Dehkharghani

Work place: Faculty of Engineering, University of Bonab, Bonab, Iran

E-mail: rdehkharghani@bonabu.ac.ir


Research Interests: Computational Science and Engineering, Natural Language Processing, Data Mining, Data Structures and Algorithms


Rahim Dehkharghani: he received his PhD in Computer Science and Engineering, Artificial Intelligence branch, from Sabanci Universty, Istanbul, in 2015 and his MSc degree in Computer Engineering, Software branch from Shahid Beheshti University, Tehran, in 2007. His main research area is Natural Language Processing and Data Mining. He specifically works on sentiment analysis of textual data. He is a faculty member of Computer Engineering group at University of Bonab (Bonab, Iran) since 2016.

Author Articles
A Hybrid Approach to Generating Adjective Polarity Lexicon and its Application to Turkish Sentiment Analysis

By Rahim Dehkharghani

DOI: https://doi.org/10.5815/ijmecs.2018.11.02, Pub. Date: 8 Nov. 2018

Many approaches to sentiment analysis benefit from polarity lexicons. Existing methods proposed for building such lexicons can be grouped into two categories: (1) Lexicon based approaches which use lexicons such as dictionaries and WordNet, and (2) Corpus based approaches which use a large corpus to extract semantic relations among words. Adjectives play an important role in polarity lexicons because they are better polarity estimators compared to other parts of speech. Among natural languages, Turkish, similar to other non-English languages suffers from the shortage of polarity resources. In this work, a hybrid approach is proposed for building adjective polarity lexicon, which is experimented on Turkish combines both lexicon based and corpus based methods. The obtained classification accuracies in classifying adjectives as positive, negative, or neutral, range from 71% to 91%.

[...] Read more.
Other Articles