Laurianne Sitbon

1.8k citations
116 papers · 1.0k indexed · h-index 18

Laurianne Sitbon

107 papers receiving 1.0k citations

Peers

Laurianne Sitbon
Comparison fields: 5 of 93
  • Artificial Intelligence 318
  • Occupational Therapy 267
  • Demography 260
  • Human-Computer Interaction 254
  • Cognitive Neuroscience 246
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Countries citing papers authored by Laurianne Sitbon

Since Specialization
Citations

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

Fields of papers citing papers by Laurianne Sitbon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laurianne Sitbon

This figure shows the co-authorship network connecting the top 25 collaborators of Laurianne Sitbon. A scholar is included among the top collaborators of Laurianne Sitbon 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 Laurianne Sitbon. Laurianne Sitbon 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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9
The efficiency of corpus-based distributional models for literature-based discovery on large data sets
3
10
Modelling the information seeking user by the decisions they make
2
11
Proceedings of the Seventeenth Australasian Document Computing Symposium
1
12
Modelling Word Meaning using Efficient Tensor Representations
10
13
Tensor query expansion: A cognitively motivated relevance model
4
14
AEHRC & QUT at TREC 2011 Medical Track: a concept-based information retrieval approach
9
15
Analysis of the effect of negation on information retrieval of medical data
9
16 1
17
Testing for the non-separability of bi-ambiguous compounds
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18
Rule-based approach for identifying assertions in clinical free-text data
1
19
Evaluating robustness of a QA system through a corpus of real-life questions
1
20
Dernières évolutions de SQuaLIA, le système de Questions/Réponses du LIA
0

About Laurianne Sitbon

Laurianne Sitbon is a scholar working on Human Factors and Ergonomics, Occupational Therapy and Human-Computer Interaction, having authored 116 papers that have together received 1.0k indexed citations. Recurring topics across this work include Topic Modeling (33 papers), Technology Use by Older Adults (23 papers) and Assistive Technology in Communication and Mobility (21 papers). The work is most often cited by research in Occupational Therapy (267 citations), Human Factors and Ergonomics (130 citations) and Human-Computer Interaction (254 citations). Laurianne Sitbon has collaborated with scholars based in Australia, France and United Kingdom. Frequent co-authors include Margot Brereton, Bernd Ploderer, Peter Bruza, Andrew A. Bayor, Cara Wilson, Guido Zuccon, Bevan Koopman, Michael Lawley, Anthony Nguyen and Paul Roe. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Journal of the American Medical Informatics Association and Methods in Ecology and Evolution.

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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