Munirathnam Srikanth
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Signal Processing
- Molecular Biology
- Co-authors
- Rohini K. SrihariDan MoldovanMarta TatuAndrew BennettAdriana BadulescuWu XiaoyunMiguel E. Ruiz
- Topics
- Topic Modeling (10 papers)Semantic Web and Ontologies (7 papers)Information Retrieval and Search Behavior (6 papers)
- Journals
- Text REtrieval ConferenceCLEF (Working Notes)
- Partner nations
- United States
In The Last Decade
Munirathnam Srikanth
16 papers receiving 214 citations
Peers
Comparison fields: 5 of 19
- Artificial Intelligence 178
- Computer Vision and Pattern Recognition 89
- Information Systems 86
- Signal Processing 27
- Molecular Biology 23
Countries citing papers authored by Munirathnam Srikanth
This map shows the geographic impact of Munirathnam Srikanth'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 Munirathnam Srikanth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Munirathnam Srikanth more than expected).
Fields of papers citing papers by Munirathnam Srikanth
This network shows the impact of papers produced by Munirathnam Srikanth. 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 Munirathnam Srikanth. The network helps show where Munirathnam Srikanth may publish in the future.
Co-authorship network of co-authors of Munirathnam Srikanth
This figure shows the co-authorship network connecting the top 25 collaborators of Munirathnam Srikanth. A scholar is included among the top collaborators of Munirathnam Srikanth 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 Munirathnam Srikanth. Munirathnam Srikanth is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 31 | |
| 2 | Automatic Ontology Creation from Text for National Intelligence Priorities Framework (NIPF). | 8 |
| 3 | 25 | |
| 4 | 3 | |
| 5 | 12 | |
| 6 | 68 | |
| 7 | LCC at TRECVID 2005 | 3 |
| 8 | UB at TREC 13: Genomics Track. | 0 |
| 9 | 2 | |
| 10 | Exploiting query features in language modeling approach for information retrieval | 4 |
| 11 | 1 | |
| 12 | 11 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 12 | |
| 16 | UB at TREC 11: Batch and Adaptive Filtering. | 2 |
| 17 | 58 | |
| 18 | 3 |
About Munirathnam Srikanth
Munirathnam Srikanth is a scholar working on Artificial Intelligence, Information Systems and Signal Processing, having authored 18 papers that have together received 245 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Semantic Web and Ontologies (7 papers) and Information Retrieval and Search Behavior (6 papers). The work is most often cited by research in Artificial Intelligence (178 citations), Computer Vision and Pattern Recognition (89 citations) and Information Systems (86 citations). Munirathnam Srikanth has collaborated with scholars based in United States. Frequent co-authors include Rohini K. Srihari, Dan Moldovan, Marta Tatu, Andrew Bennett, Adriana Badulescu, Wu Xiaoyun and Miguel E. Ruiz. Their work appears in journals such as Text REtrieval Conference and CLEF (Working Notes).
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.