Arvind Kumar Sharma

730 citations
47 papers · 244 · h-index 9

Impact in

Papers in

    • Recommender Systems and Techniques 4
    • Web Data Mining and Analysis 3
    • Spam and Phishing Detection 2
    • Advanced Text Analysis Techniques 4
    • Sentiment Analysis and Opinion Mining 3

Arvind Kumar Sharma

41 papers receiving 221 citations

Peers

Arvind Kumar Sharma
Comparison fields: 5 of 106
  • Geophysics 33
  • Information Systems 50
  • Artificial Intelligence 71
  • Pollution 16
  • Water Science and Technology 18
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Citations per field
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Citations per year

Countries citing papers authored by Arvind Kumar Sharma

Since Specialization
Citations

This map shows the geographic impact of Arvind Kumar Sharma'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 Arvind Kumar Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arvind Kumar Sharma more than expected).

Fields of papers citing papers by Arvind Kumar Sharma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arvind Kumar Sharma. 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 Arvind Kumar Sharma. The network helps show where Arvind Kumar Sharma may publish in the future.

Co-authors

The 25 scholars most cited alongside Arvind Kumar Sharma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Arvind Kumar Sharma Line = papers co-authored together Arvind Kumar Sharma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202438
2 201732
3 201717
4 202113
5 202212
6 201912
7 202012
8 201911
9
ASSESSMENT OF KNOWLEDGE, ATTITUDE AND PRACTICE ABOUT HEPATITIS B AMONG CLINICIANS & MEDICAL STUDENTS: A CROSS SECTIONAL STUDY
20159
10 20208
11 20218
12 20137
13 20236
14
A Framework for Predictive Web Prefetching at the Proxy Level using Data Mining
20085
15 20125
16 20174
17 20134
18 20243
19 20163
20 20153

About Arvind Kumar Sharma

Arvind Kumar Sharma is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Ocean Engineering and Geophysics, having authored 47 papers that have together received 244 indexed citations. Recurring topics across this work include Seismic Imaging and Inversion Techniques (5 papers), Advanced Text Analysis Techniques (4 papers), Recommender Systems and Techniques (4 papers), Web Data Mining and Analysis (3 papers), Sentiment Analysis and Opinion Mining (3 papers), Reservoir Engineering and Simulation Methods (3 papers), Advanced Steganography and Watermarking Techniques (2 papers) and Spam and Phishing Detection (2 papers). The work is most often cited by research in Geophysics (33 citations), Information Systems (50 citations), Artificial Intelligence (71 citations), Pollution (16 citations) and Water Science and Technology (18 citations). Arvind Kumar Sharma has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Munish Sharma, Munit Sharma, Simran Sharma, Preeti Gupta, Hariprasath Manoharan, Mohd Naved, Mohammad Shabbir Alam, Amit Kumar Verma, Vishal Kamboj and Amit Kumar. Their work appears in journals such as Journal of Geochemical Exploration, The Leading Edge, Saudi Pharmaceutical Journal, Indian Journal of Science and Technology and Urban Climate.

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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