Simon Dooms

590 citations
25 papers · 426 indexed · h-index 13

Simon Dooms

25 papers receiving 408 citations

Peers

Simon Dooms
Comparison fields: 5 of 49
  • Information Systems 357
  • Computer Vision and Pattern Recognition 126
  • Transportation 39
  • Management Science and Operations Research 63
  • Artificial Intelligence 157
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Citations per year

Countries citing papers authored by Simon Dooms

Since Specialization
Citations

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

Fields of papers citing papers by Simon Dooms

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 13 scholars most cited alongside Simon Dooms, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Simon Dooms Line = papers co-authored together Simon Dooms links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201613
2
Improving IMDb movie recommendations with interactive settings and filters
20143
3 20148
4 20147
5 201421
6 20142
7
MovieTweetings: a movie rating dataset collected from twitter
201378
8
An Improved Data Aggregation Strategy for Group Recommendations
20131
9
Social Recommendations for Events
201312
10 20132
11 201345
12 201388
13 201310
14 201312
15 201314
16 201216
17
A user-centric evaluation of recommender algorithms for an event recommendation system
201122
18
Analysis of the information value of user connections for video recommendations in a social network
20111
19 20114
20 201012

About Simon Dooms

Simon Dooms is a scholar working on Information Systems, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 25 papers that have together received 426 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (21 papers), Caching and Content Delivery (5 papers), Advanced Bandit Algorithms Research (5 papers), Multimedia Communication and Technology (4 papers), Expert finding and Q&A systems (3 papers), Image and Video Quality Assessment (3 papers), IoT and Edge/Fog Computing (2 papers) and Distributed and Parallel Computing Systems (2 papers). The work is most often cited by research in Information Systems (357 citations), Computer Vision and Pattern Recognition (126 citations) and Transportation (39 citations). Simon Dooms has collaborated with scholars based in Belgium and Netherlands. Frequent co-authors include Luc Martens, Toon De Pessemier, Kris Vanhecke, Alan Said, Domonkos Tikk, Babak Loni, Pieter Audenaert, Jan Fostier, Alejandro Bellogín and Wendy Van den Broeck. Their work appears in journals such as Multimedia Tools and Applications, ACM Transactions on Intelligent Systems and Technology, Journal of Intelligent Information Systems, ACM SIGWEB Newsletter and Ghent University Academic Bibliography (Ghent University).

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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