Medical dataset classification for Kurdish short text over social media

被引：6

作者：

Saeed, Ari M. ^{[1
]}

Hussein, Shnya R. ^{[1
]}

Ali, Chro M. ^{[1
]}

Rashid, Tarik A. ^{[2
]}

机构：

[1] Univ Halabja, Comp Sci Dept, KRG, Kurdistan, Kurdistan, Iraq

[2] Univ Kurdistan Hawler, Comp Sci & Engn Dept, KRG, Erbil, Kurdistan, Iraq

来源：

DATA IN BRIEF | 2022年 / 42卷

关键词：

Machine learning; Medical text classification; Kurdish short text; Text pre-processing;

D O I：

10.1016/j.dib.2022.108089

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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%. (C) 2022 The Author(s). Published by Elsevier Inc.

引用

页数：10

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