Lucas Drumond
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- Online Learning and Analytics 5
- Computational Mathematics top 5%
- Information Systems top 1%
- Recommender Systems and Techniques 9
- Data Mining Algorithms and Applications 3
- Educational Technology and Assessment 3
- Artificial Intelligence top 2%
- Semantic Web and Ontologies 7
- Intelligent Tutoring Systems and Adaptive Learning 5
- Topic Modeling 4
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- Complex Network Analysis Techniques 3
Lucas Drumond
32 papers receiving 863 citations
Peers
Comparison fields: 5 of 71
- Computer Science Applications 212
- Computational Mathematics 18
- Information Systems 593
- Artificial Intelligence 534
- Management Science and Operations Research 149
Countries citing papers authored by Lucas Drumond
This map shows the geographic impact of Lucas Drumond'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 Lucas Drumond with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lucas Drumond more than expected).
Fields of papers citing papers by Lucas Drumond
This network shows the impact of papers produced by Lucas Drumond. 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 Lucas Drumond. The network helps show where Lucas Drumond may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Lucas Drumond, 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 | 2 | |
| 2 | 2018 | 40 | |
| 3 | 2017 | 1 | |
| 4 | 2017 | 1 | |
| 5 | Matrix Factorization for Near Real-time Geolocation Prediction in Twitter Stream. | 2016 | 1 |
| 6 | Geo_ML @ MediaEval Placing Task 2015 | 2015 | 1 |
| 7 | 2014 | 11 | |
| 8 | 2013 | 3 | |
| 9 | Using factorization machines for student modeling. | 2012 | 16 |
| 10 | Factorization techniques for student performance classification and ranking. | 2012 | 2 |
| 11 | 2012 | 90 | |
| 12 | 2012 | 17 | |
| 13 | Personalized Ranking for non-uniformly sampled items | 2011 | 37 |
| 14 | Bayesian Personalized Ranking for Non-Uniformly Sampled Items | 2011 | 15 |
| 15 | 2010 | 9 | |
| 16 | A Knowledge-based Retrieval Model. | 2009 | 2 |
| 17 | A Similarity Analysis Model for Semantic Web Information Filtering Applications. | 2008 | 2 |
| 18 | 2008 | 2 | |
| 19 | 2008 | 5 | |
| 20 | 2007 | 1 |
About Lucas Drumond
Lucas Drumond is a scholar working on Computational Mathematics, Computer Science Applications and Information Systems, having authored 32 papers that have together received 914 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (9 papers), Semantic Web and Ontologies (7 papers), Online Learning and Analytics (5 papers), Intelligent Tutoring Systems and Adaptive Learning (5 papers), Topic Modeling (4 papers), Complex Network Analysis Techniques (3 papers), Data Mining Algorithms and Applications (3 papers) and Educational Technology and Assessment (3 papers). The work is most often cited by research in Computer Science Applications (212 citations), Computational Mathematics (18 citations) and Information Systems (593 citations). Lucas Drumond has collaborated with scholars based in Germany, Brazil and Ireland. Frequent co-authors include Lars Schmidt-Thieme, Christoph Freudenthaler, Artus Krohn-Grimberghe, Nguyen Thai-Nghe, Zeno Gantner, Steffen Rendle, Ernesto Diaz-Aviles, Wolfgang Nejdl, Rosario Girardi and Tomáš Horváth.
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.