Eric Crestan

484 citations
12 papers · 294 · h-index 8

Impact in

Papers in

    • Natural Language Processing Techniques 4
    • Topic Modeling 4
    • Text and Document Classification Technologies 4
    • Algorithms and Data Compression 3
    • Semantic Web and Ontologies 2
    • Web Data Mining and Analysis 7
    • Information Retrieval and Search Behavior 3

Eric Crestan

12 papers receiving 268 citations

Peers

Eric Crestan
Comparison fields: 5 of 28
  • Artificial Intelligence 245
  • Management Science and Operations Research 80
  • Information Systems 110
  • Signal Processing 31
  • Computer Vision and Pattern Recognition 28
Replace Elmar Haußmann with:
Elmar Haußmann Germany
Diego Ceccarelli Italy
Yunhua Hu China
Girija Limaye India
Srinivasan H. Sengamedu United States
Yee Fan Tan Singapore
Lawrence H. Reeve United States
Paramita Mirza Germany
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Citations per field
00.5×1.5×1.9×
Elmar Haußmann · 1×
Citations per year

Countries citing papers authored by Eric Crestan

Since Specialization
Citations

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

Fields of papers citing papers by Eric Crestan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Eric Crestan, 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 Eric Crestan Line = papers co-authored together Eric Crestan links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2009165
2 201153
3 200922
4 201012
5 201011
6
Coupling Named Entity Recognition, Vector-Space Model and Knowledge Bases for TREC 11 Question Answering Track.
20028
7
Improving WSD with Multi-Level View of Context Monitored by Similarity Measure
20018
8 20148
9
Peut-on trouver la taille de contexte optimale en désambiguïsation sémantique?
20032
10 20042
11
Use of Query Similarity for Improving Presentation of News Verticals
20112
12
Browsing Help for a Faster Retrieval
20041

About Eric Crestan

Eric Crestan is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Management Science and Operations Research and Infectious Diseases, having authored 12 papers that have together received 294 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (7 papers), Natural Language Processing Techniques (4 papers), Topic Modeling (4 papers), Text and Document Classification Technologies (4 papers), Algorithms and Data Compression (3 papers), Information Retrieval and Search Behavior (3 papers), Semantic Web and Ontologies (2 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (245 citations), Management Science and Operations Research (80 citations), Information Systems (110 citations), Signal Processing (31 citations) and Computer Vision and Pattern Recognition (28 citations). Eric Crestan has collaborated with scholars based in United States, Netherlands and Germany. Frequent co-authors include Patrick Pantel, Ana-Maria Popescu, Marc El-Bèze, Julia Kiseleva, Patrice Bellot, Fernando Díaz, Rao Shen, Youssef Billawala and Annie Louis. Their work appears in journals such as TU/e Research Portal, International Conference on Computational Linguistics and Text REtrieval Conference.

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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