Dan Tecuci
Impact in
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- Geographic Information Systems Studies
- Automotive Engineering top 10%
- Spatial Cognition and Navigation
Papers in
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- Semantic Web and Ontologies 9
- Topic Modeling 7
- Natural Language Processing Techniques 5
- AI-based Problem Solving and Planning 4
- Logic, Reasoning, and Knowledge 2
- Intelligent Tutoring Systems and Adaptive Learning 1
- Co-authors
- Benjamin Kuipers (1 shared paper)Brian J. Stankiewicz (1 shared paper)Bruce Porter (7 shared papers)Ken Barker (4 shared papers)Peter E. Clark (2 shared papers)Peter Z. Yeh (4 shared papers)Vinay K. Chaudhri (2 shared papers)James Fan (3 shared papers)
- Journals
- AI Magazine (2 papers)Environment and Behavior (1 paper)The Florida AI Research Society (2 papers)Principles of Knowledge Representation and Reasoning (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)
- Partner nations
- United StatesGermanyAustralia
In The Last Decade
Dan Tecuci
12 papers receiving 215 citations
Peers
Comparison fields: 5 of 62
- Geography, Planning and Development 38
- Automotive Engineering 71
- Artificial Intelligence 141
- Building and Construction 26
- Experimental and Cognitive Psychology 21
Countries citing papers authored by Dan Tecuci
This map shows the geographic impact of Dan Tecuci'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 Dan Tecuci with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Tecuci more than expected).
Fields of papers citing papers by Dan Tecuci
This network shows the impact of papers produced by Dan Tecuci. 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 Dan Tecuci. The network helps show where Dan Tecuci may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Tecuci, 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 | 97 | |
| 2 | 2010 | 41 | |
| 3 | Learning by reading: a prototype system, performance baseline and lessons learned | 2007 | 32 |
| 4 | A question-answering system for AP chemistry: assessing KR&R technologies | 2004 | 24 |
| 5 | A generic memory module for events | 2007 | 22 |
| 6 | 2014 | 10 | |
| 7 | 2013 | 8 | |
| 8 | 2009 | 6 | |
| 9 | Using an Episodic Memory Module for Pattern Capture and Recognition. | 2006 | 3 |
| 10 | 2020 | 3 | |
| 11 | 2007 | 1 | |
| 12 | 2009 | 1 |
About Dan Tecuci
Dan Tecuci is a scholar working on Artificial Intelligence, Political Science and International Relations, Automotive Engineering, Control and Systems Engineering and Signal Processing, having authored 12 papers that have together received 248 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (9 papers), Topic Modeling (7 papers), Natural Language Processing Techniques (5 papers), AI-based Problem Solving and Planning (4 papers), Logic, Reasoning, and Knowledge (2 papers), Data Management and Algorithms (1 paper), Spatial Cognition and Navigation (1 paper) and Intelligent Tutoring Systems and Adaptive Learning (1 paper). The work is most often cited by research in Geography, Planning and Development (38 citations), Automotive Engineering (71 citations), Artificial Intelligence (141 citations), Building and Construction (26 citations) and Experimental and Cognitive Psychology (21 citations). Dan Tecuci has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include Benjamin Kuipers, Brian J. Stankiewicz, Bruce Porter, Ken Barker, Peter E. Clark, Peter Z. Yeh, Vinay K. Chaudhri, James Fan, Sunil Kumar Mishra and Ulli Waltinger. Their work appears in journals such as AI Magazine, Environment and Behavior, The Florida AI Research Society, Principles of Knowledge Representation and Reasoning and Proceedings of the AAAI Conference on Artificial Intelligence.
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.