Sumit Bhatia

1.4k citations
50 papers · 726 indexed · h-index 15

Sumit Bhatia

45 papers receiving 692 citations

Peers

Sumit Bhatia
Comparison fields: 5 of 74
  • Artificial Intelligence 485
  • Information Systems 282
  • Computer Science Applications 31
  • Signal Processing 49
  • Computer Vision and Pattern Recognition 91
Replace Sheng-yi Kong with:
Sheng-yi Kong Taiwan
Nicholas Kolkin United States
Xuan-Hieu Phan Japan
Yiu‐Kai Ng United States
Svetlin Bostandjiev United States
Hsin-Chang Yang Taiwan
Michael Jugovac Germany
Andréi Popescu-Belis Switzerland
Thierry Declerck Germany
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Citations per field
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Sheng-yi Kong · 1×
Citations per year

Countries citing papers authored by Sumit Bhatia

Since Specialization
Citations

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

Fields of papers citing papers by Sumit Bhatia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
2 20244
3 20240
4 20243
5 20232
6 20231
7 20223
8
EmEL++: Embeddings for EL++ Description Logic.
20212
9 20211
10
A Topic-Aligned Multilingual Corpus of Wikipedia Articles for Studying Information Asymmetry in Low Resource Languages.
20205
11 20201
12 20197
13 201810
14 201534
15
Production of Yogurt Powder Using Foam-Mat Drying
201241
16
Classifying User Messages For Managing Web Forum Data.
201221
17 2011100
18 201012
19 20102
20
BioinQA: Addressing bottlenecks of Biomedical Domain through Biomedical Question Answering System
20084

About Sumit Bhatia

Sumit Bhatia is a scholar working on Artificial Intelligence, Information Systems, Communication, Signal Processing and Statistical and Nonlinear Physics, having authored 50 papers that have together received 726 indexed citations. Recurring topics across this work include Topic Modeling (20 papers), Natural Language Processing Techniques (13 papers), Advanced Text Analysis Techniques (10 papers), Web Data Mining and Analysis (10 papers), Information Retrieval and Search Behavior (9 papers), Semantic Web and Ontologies (8 papers), Biomedical Text Mining and Ontologies (7 papers) and Sentiment Analysis and Opinion Mining (5 papers). The work is most often cited by research in Artificial Intelligence (485 citations), Information Systems (282 citations), Computer Science Applications (31 citations), Signal Processing (49 citations) and Computer Vision and Pattern Recognition (91 citations). Sumit Bhatia has collaborated with scholars based in United States, India and France. Frequent co-authors include Prasenjit Mitra, C. Lee Giles, Debapriyo Majumdar, Prakhar Biyani, Suppawong Tuarob, Wunwisa Krasaekoopt, Quanzeng You, Jiebo Luo, Saurabh Kataria and Dwaipayan Roy. Their work appears in journals such as Journal of the Association for Information Science and Technology, ACM SIGIR Forum, ACM Transactions on Information Systems, Proceedings of the American Society for Information Science and Technology and Knowledge-Based Systems.

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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