Adwait Ratnaparkhi

3.9k total citations · 1 hit paper
27 papers, 2.3k citations indexed

About

Adwait Ratnaparkhi is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Adwait Ratnaparkhi has authored 27 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 9 papers in Information Systems and 3 papers in Computer Networks and Communications. Recurrent topics in Adwait Ratnaparkhi's work include Topic Modeling (12 papers), Natural Language Processing Techniques (12 papers) and Speech and dialogue systems (8 papers). Adwait Ratnaparkhi is often cited by papers focused on Topic Modeling (12 papers), Natural Language Processing Techniques (12 papers) and Speech and dialogue systems (8 papers). Adwait Ratnaparkhi collaborates with scholars based in United States, Austria and United Kingdom. Adwait Ratnaparkhi's co-authors include Mitchell P. Marcus, Jeffrey C. Reynar, Salim Roukos, Abraham Ittycheriah, Wei-Jing Zhu, Martin Franz, Richard J. Mammone, Andrew Hatch, F. Jelinek and R. L. Mercer and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, Machine Learning and Computer Speech & Language.

In The Last Decade

Adwait Ratnaparkhi

27 papers receiving 1.9k citations

Hit Papers

A Maximum Entropy Model for Part-Of-Speech Tagging 1996 2026 2006 2016 1996 250 500 750

Peers

Adwait Ratnaparkhi
Comparison fields: 5 of 87
  • Artificial Intelligence 2.1k
  • Information Systems 336
  • Molecular Biology 185
  • Computer Vision and Pattern Recognition 180
  • Signal Processing 70
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Citations per field, relative to Adwait Ratnaparkhi
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Citations per year, relative to Adwait Ratnaparkhi
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Countries citing papers authored by Adwait Ratnaparkhi

Since Specialization
Citations

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

Fields of papers citing papers by Adwait Ratnaparkhi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adwait Ratnaparkhi

This figure shows the co-authorship network connecting the top 25 collaborators of Adwait Ratnaparkhi. A scholar is included among the top collaborators of Adwait Ratnaparkhi 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 Adwait Ratnaparkhi. Adwait Ratnaparkhi 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
# Work Indexed citations
1 18
2 8
3 2
4 1
5 3
6 2
7 19
8 32
9 14
10 28
11
IBM's Statistical Question Answering System.
107
12 167
13
Maximum entropy models for natural language ambiguity resolution
289
14 54
15 272
16
A Simple Introduction to Maximum Entropy Models for Natural Language Processing
110
17
A Maximum Entropy Model for Part-Of-Speech Tagging breakdown →
838
18 28
19 50
20 137

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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