Daisuke Bekki

664 citations
28 papers · 149 · h-index 8

Impact in

Papers in

    • Natural Language Processing Techniques 19
    • Topic Modeling 15
    • Semantic Web and Ontologies 11
    • Logic, Reasoning, and Knowledge 6
    • Speech and dialogue systems 5
    • Biomedical Text Mining and Ontologies 3

Daisuke Bekki

21 papers receiving 135 citations

Peers

Daisuke Bekki
Comparison fields: 5 of 26
  • Artificial Intelligence 135
  • Computer Vision and Pattern Recognition 25
  • Language and Linguistics 9
  • Information Systems 17
  • Computer Science Applications 4
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Citations per year

Countries citing papers authored by Daisuke Bekki

Since Specialization
Citations

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

Fields of papers citing papers by Daisuke Bekki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Daisuke Bekki, 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 Daisuke Bekki Line = papers co-authored together Daisuke Bekki links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201531
2 201623
3 201718
4 20168
5 20118
6 20197
7 20177
8 20187
9 20146
10 20176
11 20206
12 20184
13 20063
14 20173
15
Building Japanese Textual Entailment Specialized Data Sets for Inference of Basic Sentence Relations
20132
16 20092
17
Toward a Discourse Theory for Annotating Causal Relations in Japanese
20142
18
Annotation and Analysis of Discourse Relations, Temporal Relations and Multi-Layered Situational Relations in Japanese Texts
20161
19
Constructive Generalized Quantifiers Revisited
20141
20 20231

About Daisuke Bekki

Daisuke Bekki is a scholar working on Artificial Intelligence, Molecular Biology, Language and Linguistics, Computational Theory and Mathematics and Information Systems, having authored 28 papers that have together received 149 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (19 papers), Topic Modeling (15 papers), Semantic Web and Ontologies (11 papers), Logic, Reasoning, and Knowledge (6 papers), Speech and dialogue systems (5 papers), Biomedical Text Mining and Ontologies (3 papers), Syntax, Semantics, Linguistic Variation (3 papers) and Web Data Mining and Analysis (1 paper). The work is most often cited by research in Artificial Intelligence (135 citations), Computer Vision and Pattern Recognition (25 citations), Language and Linguistics (9 citations), Information Systems (17 citations) and Computer Science Applications (4 citations). Daisuke Bekki has collaborated with scholars based in Japan, Germany and Australia. Frequent co-authors include Koji Mineshima, Pascual Martínez-Gómez, Yusuke Miyao, Hiroshi Noji, Ken Satoh, Jun’ichi Tsujii, Mihoko Otake, Yoichi Motomura, Saku Sugawara and Shinpei Ogata. Their work appears in journals such as Applied Ontology, Lecture notes in computer science, Meeting of the Association for Computational Linguistics, DOAJ (DOAJ: Directory of Open Access Journals) and Journal of Natural Language Processing.

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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