Rahul Jha

1.1k citations
46 papers · 606 · h-index 13

Impact in

Papers in

Rahul Jha

43 papers receiving 564 citations

Peers

Rahul Jha
Comparison fields: 5 of 88
  • Artificial Intelligence 389
  • Statistics, Probability and Uncertainty 46
  • Human-Computer Interaction 21
  • Information Systems 72
  • Computer Vision and Pattern Recognition 56
Replace Dongyeop Kang with:
Dongyeop Kang United States
Chén Mĭn United States
Christian Plaunt United States
Reza Ravanmehr Iran
Mickaël Coustaty France
Diana Purwitasari Indonesia
Wenting Wang China
Ilaria Tiddi Netherlands
Chengyu Wang China
Phil Laplante United States
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Citations per field
00.5×6.6×
Dongyeop Kang · 1×
Citations per year

Countries citing papers authored by Rahul Jha

Since Specialization
Citations

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

Fields of papers citing papers by Rahul Jha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rahul Jha. 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 Rahul Jha. The network helps show where Rahul Jha may publish in the future.

Co-authors

The 25 scholars most cited alongside Rahul Jha, 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 Rahul Jha Line = papers co-authored together Rahul Jha links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021110
2 201674
3 201654
4 202143
5 201938
6 200537
7 202333
8
Identifying the Semantic Orientation of Foreign Words
201124
9 202122
10
The computational linguistics summarization pilot task
201420
11
A System for Summarizing Scientific Topics Starting from Keywords
201318
12 202313
13 201813
14 201512
15 202112
16 202111
17 202210
18 20157
19 20147
20 20226

About Rahul Jha

Rahul Jha is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Control and Systems Engineering, Information Systems and Computer Networks and Communications, having authored 46 papers that have together received 606 indexed citations. Recurring topics across this work include Topic Modeling (16 papers), Advanced Text Analysis Techniques (10 papers), Natural Language Processing Techniques (8 papers), Smart Grid Security and Resilience (6 papers), Blockchain Technology Applications and Security (5 papers), Semantic Web and Ontologies (3 papers), Advanced Malware Detection Techniques (3 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Artificial Intelligence (389 citations), Statistics, Probability and Uncertainty (46 citations), Human-Computer Interaction (21 citations), Information Systems (72 citations) and Computer Vision and Pattern Recognition (56 citations). Rahul Jha has collaborated with scholars based in United States, India and Nepal. Frequent co-authors include Dragomir Radev, Aslı Çelikyılmaz, Sung‐Jin Lee, Vahed Qazvinian, Amjad Abu-Jbara, Dilip Kumar Pratihar, Balvinder Singh, Da Yin, Ming Zhong and Xipeng Qiu. Their work appears in journals such as Pharmaceutical Development and Technology, Robotics and Autonomous Systems, Natural Language Engineering, Journal of the Association for Information Science and Technology and Journal of Molecular Liquids.

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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