Daniel Valcarce
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Information Retrieval and Search Behavior
- Expert finding and Q&A systems
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- Advanced Bandit Algorithms Research
Papers in
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- Recommender Systems and Techniques 17
- Information Retrieval and Search Behavior 7
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- Topic Modeling 7
- Advanced Graph Neural Networks 2
- Co-authors
- Javier Parapar (13 shared papers)Álvaro Barreiro (12 shared papers)Alejandro Bellogín (2 shared papers)Pablo Castells (2 shared papers)José Antonio Pérez‐Simón (1 shared paper)María Díez‐Campelo (1 shared paper)Enric Carreras (1 shared paper)Jesús F. San Miguel (1 shared paper)
In The Last Decade
Daniel Valcarce
20 papers receiving 242 citations
Peers
Comparison fields: 5 of 52
- Information Systems 196
- Management Science and Operations Research 57
- Artificial Intelligence 121
- Transportation 22
- Computer Vision and Pattern Recognition 51
Countries citing papers authored by Daniel Valcarce
This map shows the geographic impact of Daniel Valcarce'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 Daniel Valcarce with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Valcarce more than expected).
Fields of papers citing papers by Daniel Valcarce
This network shows the impact of papers produced by Daniel Valcarce. 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 Daniel Valcarce. The network helps show where Daniel Valcarce may publish in the future.
Co-authors
The 17 scholars most cited alongside Daniel Valcarce, 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 | 2018 | 47 | |
| 2 | 2019 | 43 | |
| 3 | 2020 | 39 | |
| 4 | 2016 | 29 | |
| 5 | 2018 | 17 | |
| 6 | 2016 | 13 | |
| 7 | 2004 | 10 | |
| 8 | 2015 | 9 | |
| 9 | 2017 | 8 | |
| 10 | 2015 | 6 | |
| 11 | 2019 | 6 | |
| 12 | 2018 | 6 | |
| 13 | 2017 | 5 | |
| 14 | 2018 | 4 | |
| 15 | 2020 | 2 | |
| 16 | 2020 | 1 | |
| 17 | 2019 | 1 | |
| 18 | 2018 | 1 | |
| 19 | 2018 | 1 | |
| 20 | 2018 | 1 |
About Daniel Valcarce
Daniel Valcarce is a scholar working on Information Systems, Artificial Intelligence, Management Science and Operations Research, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 20 papers that have together received 249 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (17 papers), Topic Modeling (7 papers), Information Retrieval and Search Behavior (7 papers), Advanced Bandit Algorithms Research (5 papers), Image Retrieval and Classification Techniques (3 papers), Advanced Image and Video Retrieval Techniques (2 papers), Advanced Graph Neural Networks (2 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Information Systems (196 citations), Management Science and Operations Research (57 citations), Artificial Intelligence (121 citations), Transportation (22 citations) and Computer Vision and Pattern Recognition (51 citations). Daniel Valcarce has collaborated with scholars based in Spain, Italy and Brazil. Frequent co-authors include Javier Parapar, Álvaro Barreiro, Alejandro Bellogín, Pablo Castells, José Antonio Pérez‐Simón, María Díez‐Campelo, Enric Carreras, Jesús F. San Miguel, Álvaro Urbano and Rodrigo Martino. Their work appears in journals such as Engineering Applications of Artificial Intelligence, Knowledge-Based Systems, Information Retrieval, ACM SIGIR Forum and Blood.
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.