Sachindra Joshi
- Artificial Intelligence top 2%
- Topic Modeling 36
- Natural Language Processing Techniques 29
- Speech and dialogue systems 17
- Text and Document Classification Technologies 9
- Advanced Text Analysis Techniques 8
- Sentiment Analysis and Opinion Mining 6
- Information Systems top 5%
- Data Mining Algorithms and Applications 7
- Web Data Mining and Analysis 6
- Signal Processing top 10%
- Co-authors
- Subhabrata MukherjeeRaghu KrishnapuramVineet KumarSong FengChulaka GunasekaraKrishna KummamuruBhushan MandhaniTanveer A. Faruquie
- Journals
- Neurocomputing (1 paper)Machine Learning (2 papers)Proceedings of the VLDB Endowment (1 paper)
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
Sachindra Joshi
58 papers receiving 623 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 561
- Information Systems 196
- Signal Processing 54
- Computer Vision and Pattern Recognition 97
- Health Informatics 4
Countries citing papers authored by Sachindra Joshi
This map shows the geographic impact of Sachindra Joshi'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 Sachindra Joshi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sachindra Joshi more than expected).
Fields of papers citing papers by Sachindra Joshi
This network shows the impact of papers produced by Sachindra Joshi. 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 Sachindra Joshi. The network helps show where Sachindra Joshi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sachindra Joshi, 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 | 2025 | 2 | |
| 2 | 2024 | 8 | |
| 3 | 2023 | 2 | |
| 4 | 2022 | 5 | |
| 5 | 2022 | 0 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 5 | |
| 8 | 2021 | 4 | |
| 9 | 2021 | 2 | |
| 10 | 2020 | 57 | |
| 11 | Dialogue-act-driven Conversation Model : An Experimental Study | 2018 | 5 |
| 12 | Non-sentential Question Resolution using Sequence to Sequence Learning | 2016 | 12 |
| 13 | Sentiment Aggregation using ConceptNet Ontology | 2013 | 25 |
| 14 | Finding Influential Authors in Brand-Age Communities | 2012 | 7 |
| 15 | 2011 | 40 | |
| 16 | Automated Concept Extraction to aid Legal eDiscovery Review | 2009 | 2 |
| 17 | Learning Decision Lists with Known Rules for Text Mining | 2008 | 3 |
| 18 | 2008 | 11 | |
| 19 | 2008 | 7 | |
| 20 | 2006 | 7 |
About Sachindra Joshi
Sachindra Joshi is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 63 papers that have together received 670 indexed citations. Recurring topics across this work include Topic Modeling (36 papers), Natural Language Processing Techniques (29 papers), Speech and dialogue systems (17 papers), Text and Document Classification Technologies (9 papers), Advanced Text Analysis Techniques (8 papers), Data Mining Algorithms and Applications (7 papers), Sentiment Analysis and Opinion Mining (6 papers) and Web Data Mining and Analysis (6 papers). The work is most often cited by research in Artificial Intelligence (561 citations), Information Systems (196 citations) and Signal Processing (54 citations). Sachindra Joshi has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Subhabrata Mukherjee, Raghu Krishnapuram, Vineet Kumar, Song Feng, Chulaka Gunasekara, Krishna Kummamuru, Bhushan Mandhani, Tanveer A. Faruquie, Ashwin Srinivasan and Sumit Negi. Their work appears in journals such as Neurocomputing, Machine Learning 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.