Vineet Chaoji

2.2k citations
26 papers · 1.2k indexed · 1 hit paper · h-index 14
Topics
Complex Network Analysis Techniques (7 papers)Data Management and Algorithms (7 papers)Advanced Clustering Algorithms Research (5 papers)

In The Last Decade

Vineet Chaoji

25 papers receiving 1.2k citations

Hit Papers

Link prediction using supervised learning20062026201220192006100200300400500

Peers

Vineet Chaoji
Comparison fields: 5 of 112
  • Artificial Intelligence 653
  • Statistical and Nonlinear Physics 558
  • Computer Networks and Communications 294
  • Information Systems 283
  • Signal Processing 218
Replace Chaokun Wang with:
Chaokun Wang China
Juan-Carlos Cubero Spain
Nan Du United States
Sihong Xie United States
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Vineet Chaoji relative to Chaokun Wang China Chaokun Wang's profile →
Citations per field
00.5×1.6×
Chaokun Wang · 1×
Citations per year

Countries citing papers authored by Vineet Chaoji

Since Specialization
Citations

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

Fields of papers citing papers by Vineet Chaoji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vineet Chaoji

This figure shows the co-authorship network connecting the top 25 collaborators of Vineet Chaoji. A scholar is included among the top collaborators of Vineet Chaoji 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 Vineet Chaoji. Vineet Chaoji 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 1
2 2
3 15
4
DOCUMENT CLUSTERING WITH BURSTY INFORMATION
4
5 22
6 84
7 13
8 54
9 3
10 100
11 4
12 124
13 20
14 43
15 20
16 20
17 21
18
Link prediction using supervised learningbreakdown →
539
19
VENUS: A System for Novelty Detection in Video Streams with Learning.
6
20 7

About Vineet Chaoji

Vineet Chaoji is a scholar working on Signal Processing, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 26 papers that have together received 1.2k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (7 papers), Data Management and Algorithms (7 papers) and Advanced Clustering Algorithms Research (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (558 citations), Artificial Intelligence (653 citations) and Signal Processing (218 citations). Vineet Chaoji has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Mohammed J. Zaki, Mohammad Al Hasan, Saeed Salem, Hilmi Yıldırım, Rushi Bhatt, Rajeev Rastogi, Medha Atre, James Hendler, Sayan Ranu and Rajesh Parekh. Their work appears in journals such as PLoS ONE, Pattern Recognition Letters and Proceedings of the VLDB Endowment.

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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