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      Medical dataset classification for Kurdish short text over social media

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          Abstract

          The Facebook application is used as a resource for collecting the comments of this dataset, The dataset consists of 6756 comments to create a Medical Kurdish Dataset (MKD). The samples are comments of users, which are gathered from different posts of pages (Medical, News, Economy, Education, and Sport). Six steps as a preprocessing technique are performed on the raw dataset to clean and remove noise in the comments by replacing characters. The comments (short text) are labeled for positive class (medical comment) and negative class (non-medical comment) as text classification. The percentage ratio of the negative class is 55% while the positive class is 45%.

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          Social media competitive analysis and text mining: A case study in the pizza industry

          Shenghua Zha, Ling Li, Wu He (2013)
          Article 0 comments Cited 113 times – based on 0 reviews     Review now
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            A survey of pre-processing techniques to improve short-text quality: a case study on hate speech detection on twitter

            Usman Naseem, Imran Razzak, Peter W. Eklund (2021)
            Article 0 comments Cited 14 times – based on 0 reviews     Review now
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              An extensive dataset of handwritten central Kurdish isolated characters

              Rebin Ahmed, Tarik Rashid, Polla Fatah … (2021)
              To collect the handwritten format of separate Kurdish characters, each character has been printed on a grid of 14 × 9 of A4 paper. Each paper is filled with only one printed character so that the volunteers know what character should be written in each paper. Then each paper has been scanned, spliced, and cropped with a macro in photoshop to make sure the same process is applied for all characters. The grids of the characters have been filled mainly by volunteers of students from multiple universities in Erbil.
              Article 0 comments Cited 4 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Ari M. Saeed
                Journal
                Journal ID (nlm-ta): Data Brief
                Journal ID (iso-abbrev): Data Brief
                Title: Data in Brief
                Publisher: Elsevier
                ISSN (Electronic): 2352-3409
                Publication date PMC-release: 23 March 2022
                Publication date Collection: June 2022
                Publication date (Electronic): 23 March 2022
                Volume: 42
                Electronic Location Identifier: 108089
                Affiliations
                [a ]Computer Science Department, University of Halabja, KRG, Halabja, Kurdistan, Iraq
                [b ]Computer Science and Engineering Department, University of Kurdistan-Hawlêr, KRG, Erbil, Kurdistan, Iraq
                Author notes
                [* ]Corresponding author. ari.said@ 123456uoh.edu.iq
                Article
                Publisher Item ID: S2352-3409(22)00300-6 Publisher ID: 108089
                DOI: 10.1016/j.dib.2022.108089
                PMC ID: 8980624
                SO-VID: c21da945-b5c7-462c-b83f-5324edae49a1
                Copyright © © 2022 The Author(s). Published by Elsevier Inc.
                License:

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                Date received : 17 January 2022
                Date revision received : 14 March 2022
                Date accepted : 16 March 2022
                Categories
                Subject: Data Article

                Keywords: machine learning,medical text classification,kurdish short text,text pre-processing
                Data availability:
                Keywords: machine learning, medical text classification, kurdish short text, text pre-processing

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