Mukta Majumder

421 citations
22 papers · 246 indexed · h-index 10
Topics
Topic Modeling (13 papers)Advanced Text Analysis Techniques (7 papers)Natural Language Processing Techniques (6 papers)
Partner nations
IndiaNorway

In The Last Decade

Mukta Majumder

20 papers receiving 231 citations

Peers

Mukta Majumder
Comparison fields: 5 of 48
  • Artificial Intelligence 179
  • Information Systems 78
  • Computer Science Applications 37
  • Computer Vision and Pattern Recognition 33
  • Education 22
Replace Jorge Civera with:
Jorge Civera Spain
Patrick Ocheja Japan
M. Anbarasan India
Leonard Tang United States
Ghader Kurdi Saudi Arabia
Nour-eddine El Faddouli Morocco
David Boulanger Canada
Komminist Weldemariam Italy
Ghassan Z. Qadah United Arab Emirates
Md. Kishor Morol Bangladesh
Mukta Majumder relative to Jorge Civera Spain Jorge Civera's profile →
Citations per field
00.5×2.6×
Jorge Civera · 1×
Citations per year

Countries citing papers authored by Mukta Majumder

Since Specialization
Citations

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

Fields of papers citing papers by Mukta Majumder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mukta Majumder

This figure shows the co-authorship network connecting the top 25 collaborators of Mukta Majumder. A scholar is included among the top collaborators of Mukta Majumder 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 Mukta Majumder. Mukta Majumder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 6
4 0
5 10
6 14
7 1
8 3
9 53
10 22
11 4
12
Development of a hindi named entity recognition system without using manually annotated training corpus.
2
13 13
14 9
15 20
16 1
17 35
18 16
19 4
20 13

About Mukta Majumder

Mukta Majumder is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 22 papers that have together received 246 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Advanced Text Analysis Techniques (7 papers) and Natural Language Processing Techniques (6 papers). The work is most often cited by research in Computer Science Applications (37 citations), Artificial Intelligence (179 citations) and Health Informatics (7 citations). Mukta Majumder has collaborated with scholars based in India and Norway. Frequent co-authors include Sujan Kumar Saha, Santanu Phadikar, Arif Ahmed Sekh, Arindam Bhattacharya, Biswapati Jana and Amit Prakash. Their work appears in journals such as Neural Computing and Applications, Multimedia Tools and Applications and Soft Computing.

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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