Abe Ittycheriah
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Text and Document Classification Technologies
- Semantic Web and Ontologies
- Advanced Text Analysis Techniques
- Speech and dialogue systems
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- Multimodal Machine Learning Applications
Papers in
-
- Natural Language Processing Techniques 8
- Topic Modeling 8
- Algorithms and Data Compression 2
- Advanced Text Analysis Techniques 1
- Authorship Attribution and Profiling 1
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- Multimodal Machine Learning Applications 2
- Handwritten Text Recognition Techniques 1
- Co-authors
- Hongyan Jing (2 shared papers)Tong Zhang (1 shared paper)Radu Florian (1 shared paper)Haitao Mi (4 shared papers)Salim Roukos (2 shared papers)Nanda Kambhatla (2 shared papers)Zhiguo Wang (2 shared papers)Xiaoqiang Luo (1 shared paper)
- Journals
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (1 paper)
- Partner nations
- United StatesNetherlandsMexico
In The Last Decade
Abe Ittycheriah
9 papers receiving 563 citations
Peers
Comparison fields: 5 of 37
- Artificial Intelligence 612
- Computer Vision and Pattern Recognition 118
- Information Systems 75
- Management Science and Operations Research 34
- Signal Processing 19
Countries citing papers authored by Abe Ittycheriah
This map shows the geographic impact of Abe Ittycheriah'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 Abe Ittycheriah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abe Ittycheriah more than expected).
Fields of papers citing papers by Abe Ittycheriah
This network shows the impact of papers produced by Abe Ittycheriah. 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 Abe Ittycheriah. The network helps show where Abe Ittycheriah may publish in the future.
Co-authors
The 16 scholars most cited alongside Abe Ittycheriah, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 244 | |
| 2 | 2004 | 150 | |
| 3 | 2016 | 79 | |
| 4 | 2016 | 72 | |
| 5 | 2003 | 42 | |
| 6 | 2016 | 31 | |
| 7 | 2020 | 19 | |
| 8 | 2014 | 4 | |
| 9 | 2008 | 2 |
About Abe Ittycheriah
Abe Ittycheriah is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science, Information Systems and Infectious Diseases, having authored 9 papers that have together received 643 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Topic Modeling (8 papers), Multimodal Machine Learning Applications (2 papers), Algorithms and Data Compression (2 papers), Advanced Text Analysis Techniques (1 paper), Authorship Attribution and Profiling (1 paper), Handwritten Text Recognition Techniques (1 paper) and Misinformation and Its Impacts (1 paper). The work is most often cited by research in Artificial Intelligence (612 citations), Computer Vision and Pattern Recognition (118 citations), Information Systems (75 citations), Management Science and Operations Research (34 citations) and Signal Processing (19 citations). Abe Ittycheriah has collaborated with scholars based in United States, Netherlands and Mexico. Frequent co-authors include Hongyan Jing, Tong Zhang, Radu Florian, Haitao Mi, Salim Roukos, Nanda Kambhatla, Zhiguo Wang, Xiaoqiang Luo, Zhiguo Wang and Baskaran Sankaran. Their work appears in journals such as Rare & Special e-Zone (The Hong Kong University of Science and Technology).
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.