Khairullah Khan

1.2k total citations · 1 hit paper
31 papers, 787 citations indexed

About

Khairullah Khan is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Khairullah Khan has authored 31 papers receiving a total of 787 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 10 papers in Information Systems and 3 papers in Sociology and Political Science. Recurrent topics in Khairullah Khan's work include Advanced Text Analysis Techniques (18 papers), Sentiment Analysis and Opinion Mining (16 papers) and Text and Document Classification Technologies (13 papers). Khairullah Khan is often cited by papers focused on Advanced Text Analysis Techniques (18 papers), Sentiment Analysis and Opinion Mining (16 papers) and Text and Document Classification Technologies (13 papers). Khairullah Khan collaborates with scholars based in Pakistan, Malaysia and China. Khairullah Khan's co-authors include Baharum Baharudin, Lam Hong Lee, Irfan Ullah Khan, Ashraf Ullah, Wahab Khan, Jian Yang, Wei Zhang, Atta‐ur Rahman, Atta Rahman and Muhammad Kamran and has published in prestigious journals such as Multimedia Tools and Applications, Journal of King Saud University - Computer and Information Sciences and Arabian Journal for Science and Engineering.

In The Last Decade

Khairullah Khan

29 papers receiving 688 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Review of Machine Learning Algorithms for Text-Documents Classification

2010 454 citations Baharum Baharudin, Khairullah Khan et al. profile →

Peers

Khairullah Khan

AI

IS

SPS

MSOR

SP

Liang Zhou United States

Lin Yue China

Jack Wu Hong Kong

Guixian Xu China

Shakeel Ahmad Pakistan

Yu–N Cheah Malaysia

Baharum Baharudin Malaysia

Debasis Ganguly Ireland

Yi Cai China

Liang Zhou United States

Khairullah Khan

940 ×1.6

AI

275 ×1.0

IS

66 ×0.9

SPS

79 ×1.5

MSOR

31 ×0.8

SP

Citations per year, relative to Khairullah Khan Khairullah Khan (= 1×) peers Liang Zhou

Countries citing papers authored by Khairullah Khan

Since Specialization

Citations

This map shows the geographic impact of Khairullah Khan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Khairullah Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khairullah Khan more than expected).

Fields of papers citing papers by Khairullah Khan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Khairullah Khan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Khairullah Khan. The network helps show where Khairullah Khan may publish in the future.

Co-authorship network of co-authors of Khairullah Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Khairullah Khan. A scholar is included among the top collaborators of Khairullah Khan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Khairullah Khan. Khairullah Khan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Khan, Khairullah, et al.. (2025). EVOLUTION OF SENTIMENT ANALYSIS IN REVIEWS FOR INTELLIGENT PRODUCT RECOMMENDATIONS. 2(1). 142–166.

2.

Khan, Khairullah, et al.. (2025). Immoral post detection using a one-dimensional convolutional neural network-based LSTM network. Multimedia Tools and Applications. 84(32). 39885–39904.

3.

Khan, Khairullah, et al.. (2024). Deep Learning-Based Identification of Immoral Posts on Social Media Using Fine-tuned Bert Model. 3(4). 26–39. 1 indexed citations

4.

Khan, Aman Ullah, et al.. (2024). Comparison of Machine Learning and Deep Learning Models for Part-of-Speech Tagging. 1(2). 106–116. 1 indexed citations

5.

Khan, Khairullah, et al.. (2023). Understanding Quality of Products from Customers’ Attitude Using Advanced Machine Learning Methods. Computers. 12(3). 49–49. 9 indexed citations

6.

Khan, Khairullah & Wahab Khan. (2018). Sentence Level Domain Independent Opinion and Targets Identification in Unstructured Reviews. Computers. 7(4). 70–70. 1 indexed citations

7.

Khan, Khairullah, et al.. (2018). Urdu Word Segmentation using Machine Learning Approaches. International Journal of Advanced Computer Science and Applications. 9(6). 8 indexed citations

8.

Khan, Irfan Ullah, et al.. (2018). Empirical Analysis of Recent Advances, Characteristics and Challenges of Big Data. ICST Transactions on Scalable Information Systems. 0(0). 159621–159621. 3 indexed citations

9.

Khan, Khairullah, et al.. (2018). Urdu Sentiment Analysis. International Journal of Advanced Computer Science and Applications. 9(9). 15 indexed citations

10.

Khan, Khairullah, et al.. (2018). Impact of Anaphora Resolution on Opinion Target Identification. International Journal of Advanced Computer Science and Applications. 9(6). 2 indexed citations

11.

Khan, Khairullah, Ashraf Ullah, & Baharum Baharudin. (2016). Pattern and semantic analysis to improve unsupervised techniques for opinion target identification. Kuwait Journal of Science. 43(1). 10 indexed citations

12.

Khan, Khairullah, Baharum Baharudin, & Irfan Ullah Khan. (2014). A Review of Unsupervised Approaches of Opinion Target Extraction from Unstructured Reviews. Research Journal of Applied Sciences Engineering and Technology. 7(12). 2400–2410. 4 indexed citations

13.

Khan, Khairullah, et al.. (2014). Identifying Product Features from Customer Reviews Using Hybrid Patterns. The International Arab Journal of Information Technology. 11. 281–286. 19 indexed citations

14.

Khan, Khairullah, et al.. (2014). Mining opinion components from unstructured reviews: A review. Journal of King Saud University - Computer and Information Sciences. 26(3). 258–275. 88 indexed citations

15.

Khan, Khairullah, Baharum Baharudin, & Irfan Ullah Khan. (2013). Mining Opinion Targets from Text Documents: A Review. Journal of Emerging Technologies in Web Intelligence. 5(4). 3 indexed citations

16.

Khan, Irfan Ullah, et al.. (2011). An Overview of E-Documents Classification. 6 indexed citations

17.

Khan, Irfan Ullah, Baharum Baharudin, & Khairullah Khan. (2011). Sentiment Classification Using Sentence-level Lexical Based Semantic Orientation of Online Reviews. Trends in Applied Sciences Research. 6(10). 1141–1157. 31 indexed citations

18.

Khan, Irfan Ullah, et al.. (2010). Sentence based sentiment classification from online customer reviews. 1–6. 19 indexed citations

19.

Khan, Irfan Ullah, Khairullah Khan, & Baharum Baharudin. (2009). Frequent Patterns Minning of Stock Data Using Hybrid Clustering Association Algorithm. 667–671. 9 indexed citations

20.

Khan, Khairullah, Jian Yang, & Wei Zhang. (2007). Unsupervised Classification of Polarimetric SAR Images by EM Algorithm. IEICE Transactions on Communications. E90-B(12). 3632–3642. 14 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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