Emanuel Lacić
Impact in
- Information Systems top 10%
- Recommender Systems and Techniques
Papers in
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- Recommender Systems and Techniques 15
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- Advanced Graph Neural Networks 6
- Topic Modeling 4
- Co-authors
- Dominik Kowald (14 shared papers)Elisabeth Lex (11 shared papers)Christoph Trattner (5 shared papers)Mario Lovrić (2 shared papers)Roman Kern (2 shared papers)Denis Parra (2 shared papers)Matthias Traub (4 shared papers)Morten Arendt Rasmussen (1 shared paper)
- Journals
- Frontiers in Big Data (1 paper)User Modeling and User-Adapted Interaction (1 paper)Pharmaceuticals (1 paper)Children (1 paper)it - Information Technology (1 paper)
In The Last Decade
Emanuel Lacić
19 papers receiving 173 citations
Peers
Comparison fields: 5 of 56
- Information Systems 103
- Health Informatics 3
- Computer Science Applications 12
- Management Science and Operations Research 27
- Artificial Intelligence 69
Countries citing papers authored by Emanuel Lacić
This map shows the geographic impact of Emanuel Lacić'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 Emanuel Lacić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emanuel Lacić more than expected).
Fields of papers citing papers by Emanuel Lacić
This network shows the impact of papers produced by Emanuel Lacić. 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 Emanuel Lacić. The network helps show where Emanuel Lacić may publish in the future.
Co-authors
The 13 scholars most cited alongside Emanuel Lacić, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 22 | |
| 2 | 2021 | 19 | |
| 3 | 2021 | 18 | |
| 4 | 2016 | 18 | |
| 5 | 2020 | 15 | |
| 6 | Tackling Cold-Start Users in Recommender Systems with Indoor Positioning Systems | 2015 | 12 |
| 7 | 2014 | 12 | |
| 8 | 2014 | 12 | |
| 9 | 2015 | 10 | |
| 10 | 2019 | 8 | |
| 11 | 2023 | 7 | |
| 12 | 2014 | 7 | |
| 13 | 2015 | 7 | |
| 14 | ScaR: Towards a Real-Time Recommender Framework Following the Microservices Architecture | 2015 | 5 |
| 15 | 2014 | 4 | |
| 16 | 2017 | 1 | |
| 17 | 2018 | 1 | |
| 18 | Real-Time Recommendations in a Multi-Domain Environment. | 2016 | 1 |
| 19 | 2023 | 1 | |
| 20 | 2015 | 1 |
About Emanuel Lacić
Emanuel Lacić is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Statistical and Nonlinear Physics and Transportation, having authored 21 papers that have together received 181 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (15 papers), Advanced Graph Neural Networks (6 papers), Topic Modeling (4 papers), Caching and Content Delivery (4 papers), Peer-to-Peer Network Technologies (3 papers), Distributed and Parallel Computing Systems (2 papers), Complex Network Analysis Techniques (2 papers) and Software System Performance and Reliability (1 paper). The work is most often cited by research in Information Systems (103 citations), Health Informatics (3 citations), Computer Science Applications (12 citations), Management Science and Operations Research (27 citations) and Artificial Intelligence (69 citations). Emanuel Lacić has collaborated with scholars based in Austria, Croatia and Chile. Frequent co-authors include Dominik Kowald, Elisabeth Lex, Christoph Trattner, Mario Lovrić, Roman Kern, Denis Parra, Matthias Traub, Morten Arendt Rasmussen, Junghoo Cho and Mirjana Turkalj. Their work appears in journals such as Frontiers in Big Data, User Modeling and User-Adapted Interaction, Pharmaceuticals, Children and it - Information Technology.
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.