Ryutaro Ichise

99 papers receiving 1.1k citations

Peers

Ryutaro Ichise
Comparison fields: 5 of 85
  • Artificial Intelligence 840
  • Information Systems 307
  • Statistical and Nonlinear Physics 201
  • Management Science and Operations Research 177
  • Molecular Biology 149
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Citations per year

Countries citing papers authored by Ryutaro Ichise

Since Specialization
Citations

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

Fields of papers citing papers by Ryutaro Ichise

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryutaro Ichise

This figure shows the co-authorship network connecting the top 25 collaborators of Ryutaro Ichise. A scholar is included among the top collaborators of Ryutaro Ichise 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 Ryutaro Ichise. Ryutaro Ichise 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
1 11
2 4
3 1
4
Correcting Range Violation Errors in DBpedia.
2
5
T2KG: An End-to-End System for Creating Knowledge Graph from Unstructured Text.
32
6
An Ontology based Map Converter for Intelligent Vehicles.
0
7
A Heuristic Approach for Configuration Learning of Supervised Instance Matching.
1
8
ScSLINT: Time and Memory Efficient Interlinking Framework for Linked Data.
3
9
SLINT+ results for OAEI 2013 instance matching
6
10
Exploiting Information Flow and Active Links for Link Prediction in Social Networks
3
11
SLINT: a schema-independent linked data interlinking system
17
12
Exploiting Information Flow and Active Links for Link Prediction in Social Networks (人工知能学会全国大会(第26回)文化,科学技術と未来) -- (International Organized Session「Application Oriented Principles of Machine Learning and Data Mining」)
1
13
Cluster-based similarity aggregation for ontology matching
22
14
LiDDM: A data mining system for linked data
9
15
Aggregation of similarity measures in ontology matching
3
16
ACTION-ORIENTED WEBLOG TO SUPPORT ACADEMIC CONFERENCE PARTICIPANTS
1
17
Integrating multiple internet directories by instance-based learning
30
18
Learning hierarchical skills from observation
0
19 0
20
Inductive Logic Programming and Genetic Programming.
1

About Ryutaro Ichise

Ryutaro Ichise is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 111 papers that have together received 1.1k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (42 papers), Topic Modeling (21 papers) and Advanced Graph Neural Networks (18 papers). The work is most often cited by research in Artificial Intelligence (840 citations), Statistical and Nonlinear Physics (201 citations) and Management Science and Operations Research (177 citations). Ryutaro Ichise has collaborated with scholars based in Japan, Vietnam and United States. Frequent co-authors include Lihua Zhao, Natthawut Kertkeidkachorn, Hideaki Takeda, Shinichi Honiden, Khai T. Nguyen, Yutaka Sasaki, Hirotaka Ōsawa, Hiromitsu Hattori, Arisa Ema and T. Kõyama. Their work appears in journals such as Proceedings of the IEEE, Expert Systems with Applications and IEEE Access.

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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