Laura Hollink

49 papers receiving 885 citations

Peers

Laura Hollink
Comparison fields: 5 of 80
  • Artificial Intelligence 534
  • Computer Vision and Pattern Recognition 470
  • Information Systems 209
  • Signal Processing 120
  • Molecular Biology 109
Replace Nicola Ferro with:
Nicola Ferro Italy
Marieke van Erp Netherlands
Carina Silberer Germany
Antoine Isaac Netherlands
Aitor Soroa Spain
Clare R. Voss United States
Bruce Croft United States
Bernardo Magnini Italy
Alessandro Oltramari United States
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Laura Hollink relative to Nicola Ferro Italy Nicola Ferro's profile →
Citations per field
00.5×3.0×
Nicola Ferro · 1×
Citations per year

Countries citing papers authored by Laura Hollink

Since Specialization
Citations

This map shows the geographic impact of Laura Hollink'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 Laura Hollink with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laura Hollink more than expected).

Fields of papers citing papers by Laura Hollink

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laura Hollink. 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 Laura Hollink. The network helps show where Laura Hollink may publish in the future.

Co-authorship network of co-authors of Laura Hollink

This figure shows the co-authorship network connecting the top 25 collaborators of Laura Hollink. A scholar is included among the top collaborators of Laura Hollink 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 Laura Hollink. Laura Hollink is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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Proceedings of the 14th International Conference on Semantic Systems, SEMANTICS 2018, Vienna, Austria, September 10-13, 2018
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Exploring concept representations for concept drift detection
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A Corpus of Images and Text in Online News
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Results of the Ontology Alignment Evaluation Initiative 2012
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Multilingual and Cross-lingual Ontology Matching and its Application to Financial Accounting Standards
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A common multimedia annotation framework for cross linking cultural heritage digital collections
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The Interaction Between Automatic Annotation and Query Expansion: a retrieval experiment on a large cultural heritage archive
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About Laura Hollink

Laura Hollink is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 51 papers that have together received 1.0k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (22 papers), Image Retrieval and Classification Techniques (15 papers) and Video Analysis and Summarization (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (470 citations), Artificial Intelligence (534 citations) and Signal Processing (120 citations). Laura Hollink has collaborated with scholars based in Netherlands, Spain and Germany. Frequent co-authors include Guus Schreiber, Marcel Worring, Bob Wielinga, A.T. Schreiber, Véronique Malaisé, Maarten de Rijke, Bouke Huurnink, Willem Robert van Hage, Roxane Segers and Jan Wielemaker. Their work appears in journals such as IEEE Transactions on Multimedia, International Journal of Human-Computer Studies and Multimedia Tools and Applications.

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.

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