eprintid: 12637
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/26/37
datestamp: 2023-11-10 03:27:11
lastmod: 2023-11-10 03:27:11
status_changed: 2023-11-10 01:49:10
type: conference_item
metadata_visibility: show
creators_name: Baseer, F.
creators_name: Jaafar, J.
creators_name: Aziz, I.B.A.
creators_name: Habib, A.
title: Refined Urdu Lexicon Development K-Means Clustering Based Computational Model Using Colloquial Romanized Urdu Dataset
ispublished: pub
keywords: Computation theory; Computational methods; Intelligent computing, Computational model; Edit distance; K-means clustering techniques; Potential selection; Tokenization; Urdu lexicon; User friendly; Written communications, K-means clustering
note: cited By 0; Conference of 2020 International Conference on Computational Intelligence, ICCI 2020 ; Conference Date: 8 October 2020 Through 9 October 2020; Conference Code:164916
abstract: Urdu is among the most widely used languages in the world for verbal and written communication. Due to lack of optimized and user friendly native Urdu-script support on various platforms, it is mostly written in Romanized script in soft form. In our research, we have developed a refined Urdu lexicon using tokens with the highest frequency of occurrence in the data set. This data set is basically a raw corpus of colloquial Urdu written in Romanized script. The corpus was collected from volunteer participants who used this language as a mode of communication on the Internet and text massaging. The raw corpus is passed through a series of steps such as Prepossessing, Tokenization and Annotation before passing it to computationally extensive subsequent steps. Edit Distance and K-means Clustering techniques are used for identification of candidate tokens and their potential selection/ inclusion in the refined lexicon. We have also identified most commonly used tokens, candidate tokens and other lingual attributes from the data collected. Based on analysis, we have proposed a computational model for refined colloquial Romanized Urdu lexicon development. © 2020 IEEE.
date: 2020
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097536620&doi=10.1109%2fICCI51257.2020.9247814&partnerID=40&md5=1b1f615b9f333e079497762ef059e259
id_number: 10.1109/ICCI51257.2020.9247814
full_text_status: none
publication: 2020 International Conference on Computational Intelligence, ICCI 2020
pagerange: 57-62
refereed: TRUE
isbn: 9781728154473
citation:   Baseer, F. and Jaafar, J. and Aziz, I.B.A. and Habib, A.  (2020) Refined Urdu Lexicon Development K-Means Clustering Based Computational Model Using Colloquial Romanized Urdu Dataset.  In: UNSPECIFIED.