Ljiljana Dolamic
- Artificial Intelligence top 10%
- Information Systems top 10%
- General Health Professions
- Sociology and Political Science
- Computer Vision and Pattern Recognition
- Co-authors
- Jacques SavoyCélia BoyerPhilippe Cudré-MaurouxGiuseppe CuccuJie YangTanja SamardżićFabio RinaldiNatalia Grabar
- Topics
- Topic Modeling (14 papers)Natural Language Processing Techniques (12 papers)Information Retrieval and Search Behavior (10 papers)
- Journals
- Communications of the ACMJournal of Medical Internet ResearchInformation Processing & Management
- Partner nations
- SwitzerlandNetherlandsFrance
In The Last Decade
Ljiljana Dolamic
27 papers receiving 209 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 172
- Information Systems 69
- General Health Professions 41
- Sociology and Political Science 24
- Computer Vision and Pattern Recognition 17
Countries citing papers authored by Ljiljana Dolamic
This map shows the geographic impact of Ljiljana Dolamic'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 Ljiljana Dolamic with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ljiljana Dolamic more than expected).
Fields of papers citing papers by Ljiljana Dolamic
This network shows the impact of papers produced by Ljiljana Dolamic. 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 Ljiljana Dolamic. The network helps show where Ljiljana Dolamic may publish in the future.
Co-authorship network of co-authors of Ljiljana Dolamic
This figure shows the co-authorship network connecting the top 25 collaborators of Ljiljana Dolamic. A scholar is included among the top collaborators of Ljiljana Dolamic based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ljiljana Dolamic. Ljiljana Dolamic is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 32 | |
| 10 | UniNE at FIRE 2010: Hindi, Bengali, and Marathi IR | 0 |
| 11 | 1 | |
| 12 | 1 | |
| 13 | Ad Hoc Retrieval with the Persian Language | 2 |
| 14 | 5 | |
| 15 | BRIEF COMMUNICATION When Stopword Lists Make the Difference | 1 |
| 16 | 27 | |
| 17 | UniNE at CLEF 2009: Persian Ad Hoc Retrieval and IP | 1 |
| 18 | 12 | |
| 19 | 27 | |
| 20 | UniNE at Domain-Specific IR - CLEF 2008: Scientific Data Retrieval: Various Query Expansion Approaches | 0 |
About Ljiljana Dolamic
Ljiljana Dolamic is a scholar working on Artificial Intelligence, Information Systems and Linguistics and Language, having authored 32 papers that have together received 228 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (12 papers) and Information Retrieval and Search Behavior (10 papers). The work is most often cited by research in Artificial Intelligence (172 citations), Information Systems (69 citations) and General Health Professions (41 citations). Ljiljana Dolamic has collaborated with scholars based in Switzerland, Netherlands and France. Frequent co-authors include Jacques Savoy, Célia Boyer, Philippe Cudré-Mauroux, Giuseppe Cuccu, Jie Yang, Tanja Samardżić, Fabio Rinaldi, Natalia Grabar, Pascal Frossard and Rachid Guerraoui. Their work appears in journals such as Communications of the ACM, Journal of Medical Internet Research and Information Processing & Management.
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.