Luc Lamontagne

548 citations
41 papers · 215 indexed · h-index 8
Topics
Topic Modeling (15 papers)Natural Language Processing Techniques (9 papers)Software Testing and Debugging Techniques (5 papers)
Partner nations
CanadaFranceDenmark

In The Last Decade

Luc Lamontagne

39 papers receiving 203 citations

Peers

Luc Lamontagne
Comparison fields: 5 of 76
  • Artificial Intelligence 78
  • Information Systems 63
  • Software 43
  • Management Science and Operations Research 29
  • Computer Vision and Pattern Recognition 25
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Citations per field
00.5×4.8×
Marco Adelfio · 1×
Citations per year

Countries citing papers authored by Luc Lamontagne

Since Specialization
Citations

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

Fields of papers citing papers by Luc Lamontagne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luc Lamontagne

This figure shows the co-authorship network connecting the top 25 collaborators of Luc Lamontagne. A scholar is included among the top collaborators of Luc Lamontagne 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 Luc Lamontagne. Luc Lamontagne 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
Encoding Neighbor Information into Geographical Embeddings Using Convolutional Neural Networks.
2
10
Building User Interest Profiles Using DBpedia in a Question Answering System.
2
11
Word embeddings and Global Preference for Contextual Suggestion.
4
12
Laval University and Lakehead University Experiments at TREC 2015 Contextual Suggestion Track
1
13
Optimizing Question-Answering Systems Using Genetic Algorithms
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14
Learning Case Feature Weights from Relevance and Ranking Feedback
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15
Towards a Unified Metrics Suite for JUnit Test Cases.
4
16 15
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The optimal searcher path problem with a visibility criterion in discrete time and space
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18
Reinforcement of Local Pattern Cases for Playing Tetris.
5
19
Applying Case-Based Reasoning to Email Response.
4
20
Using Statistical Word Associations for the Retrieval of Strongly-Textual Cases.
3

About Luc Lamontagne

Luc Lamontagne is a scholar working on Software, Artificial Intelligence and Management Science and Operations Research, having authored 41 papers that have together received 215 indexed citations. Recurring topics across this work include Topic Modeling (15 papers), Natural Language Processing Techniques (9 papers) and Software Testing and Debugging Techniques (5 papers). The work is most often cited by research in Software (43 citations), Information Systems (63 citations) and Artificial Intelligence (78 citations). Luc Lamontagne has collaborated with scholars based in Canada, France and Denmark. Frequent co-authors include Mourad Badri, Fadel Touré, Étienne Marceau, Irène Abi‐Zeid, Hélène Cossette, Guy Lapalme, Richard Khoury, Mario Marchand, Claude Bouchard and Jacques Desrosiers. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Journal of Environmental 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.

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