Igor Mel’čuk

4.5k citations
143 papers · 1.9k · h-index 23

Impact in

Papers in

    • Historical Linguistics and Language Studies 31
    • Lexicography and Language Studies 31
    • Syntax, Semantics, Linguistic Variation 28
    • linguistics and terminology studies 21
    • Natural Language Processing Techniques 35

Igor Mel’čuk

118 papers receiving 1.5k citations

Peers

Igor Mel’čuk
Comparison fields: 5 of 61
  • Language and Linguistics 1.3k
  • Linguistics and Language 239
  • Experimental and Cognitive Psychology 360
  • Artificial Intelligence 957
  • Philosophy 302
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Citations per year

Countries citing papers authored by Igor Mel’čuk

Since Specialization
Citations

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

Fields of papers citing papers by Igor Mel’čuk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Igor Mel’čuk. 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 Igor Mel’čuk. The network helps show where Igor Mel’čuk may publish in the future.

Co-authors

The 24 scholars most cited alongside Igor Mel’čuk, 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 Igor Mel’čuk Line = papers co-authored together Igor Mel’čuk links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 143 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Lexical functions: a tool for the description of lexical relations in a lexicon
1996143
2 1998126
3 2006120
4
Introduction à la lexicologie explicative et combinatoire
1995112
5
A formal lexicon in the Meaning-Text Theory: (or how to do lexica with words)
198787
6
DEC dictionnaire explicatif et combinatoire du français contemporain
198482
7 199981
8 197064
9 198162
10 200160
11 198658
12 199648
13 196944
14 201244
15 201243
16 200443
17 199441
18 200035
19 200429
20 200928

About Igor Mel’čuk

Igor Mel’čuk is a scholar working on Language and Linguistics, Artificial Intelligence, Philosophy, Linguistics and Language and Cultural Studies, having authored 143 papers that have together received 1.9k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (35 papers), Historical Linguistics and Language Studies (31 papers), Lexicography and Language Studies (31 papers), Syntax, Semantics, Linguistic Variation (28 papers), Linguistics and Discourse Analysis (24 papers), linguistics and terminology studies (21 papers), French Language Learning Methods (12 papers) and Discourse Analysis and Cultural Communication (11 papers). The work is most often cited by research in Language and Linguistics (1.3k citations), Linguistics and Language (239 citations), Experimental and Cognitive Psychology (360 citations), Artificial Intelligence (957 citations) and Philosophy (302 citations). Igor Mel’čuk has collaborated with scholars based in Canada, Russia and France. Frequent co-authors include Alain Polguère, André Clas, Leo Wanner, Lidija Iordanskaja, Paul T. Roberge, Richard Kittredge, David Beck, Robert F. Ilson, Douglas A. Kibbee and Sylvain Kahane. Their work appears in journals such as Linguistics, Studies in Language, Machine Translation, International Journal of Lexicography and Language.

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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