Niladri Chatterjee

990 citations
76 papers · 502 · h-index 14

Impact in

Papers in

Niladri Chatterjee

68 papers receiving 456 citations

Peers

Niladri Chatterjee
Comparison fields: 5 of 85
  • Safety, Risk, Reliability and Quality 103
  • Artificial Intelligence 283
  • Transportation 53
  • Information Systems 71
  • Building and Construction 38
Replace Hsiao-Te Chang with:
Hsiao-Te Chang Taiwan
Ayush Jain India
Kenneth A. Perrine United States
Salima Hassas France
Marcin Detyniecki France
Pino Caballero‐Gil Spain
Poj Tangamchit Thailand
Sara Manzoni Italy
R. Prabha India
Martin Wirz Switzerland
Niladri Chatterjee relative to Hsiao-Te Chang Taiwan Hsiao-Te Chang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Niladri Chatterjee

Since Specialization
Citations

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

Fields of papers citing papers by Niladri Chatterjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201240
2 202131
3 201730
4
Identification of divergence for English to Hindi EBMT
200329
5 201823
6 201022
7 202317
8 200717
9 201216
10 201616
11 200715
12 201814
13 201313
14 201813
15 201813
16 201412
17
Study of divergence for example based English-Hindi machine translation
200112
18 201412
19 201411
20 201610

About Niladri Chatterjee

Niladri Chatterjee is a scholar working on Artificial Intelligence, Safety, Risk, Reliability and Quality, Information Systems, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 76 papers that have together received 502 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (34 papers), Topic Modeling (31 papers), Traffic and Road Safety (11 papers), Advanced Text Analysis Techniques (10 papers), Text Readability and Simplification (8 papers), Rough Sets and Fuzzy Logic (8 papers), Speech and dialogue systems (6 papers) and Urban Transport and Accessibility (5 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (103 citations), Artificial Intelligence (283 citations), Transportation (53 citations), Information Systems (71 citations) and Building and Construction (38 citations). Niladri Chatterjee has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Geetam Tiwari, Deepa Gupta, Neha Kaushik, Shiwali Mohan, M. V. Rama Krishna, K. Ramachandra Rao, Renu Balyan, Umang Gupta, Udit Gupta and Joseph Fazio. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, Accident Analysis & Prevention, Computer Speech & Language, Natural Language Engineering 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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