Koji Hino

951 citations
12 papers · 631 indexed · h-index 8
Topics
Complex Network Analysis Techniques (5 papers)Web Data Mining and Analysis (3 papers)Peer-to-Peer Network Technologies (2 papers)
Partner nations
United StatesJapan

In The Last Decade

Koji Hino

10 papers receiving 598 citations

Peers

Koji Hino
Comparison fields: 5 of 57
  • Statistical and Nonlinear Physics 443
  • Artificial Intelligence 272
  • Information Systems 144
  • Sociology and Political Science 79
  • Computer Networks and Communications 78
Replace Nicola Barbieri with:
Nicola Barbieri Spain
Karthik Subbian United States
Rongjing Xiang United States
Marco Rosa Italy
Ramasuri Narayanam India
Lujun Fang China
Amin Mantrach Spain
Saša Petrović United Kingdom
Venu Satuluri United States
Adrien Guille France
Koji Hino relative to Nicola Barbieri Spain Nicola Barbieri's profile →
Citations per field
00.5×1.5×
Nicola Barbieri · 1×
Citations per year

Countries citing papers authored by Koji Hino

Since Specialization
Citations

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

Fields of papers citing papers by Koji Hino

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Koji Hino

This figure shows the co-authorship network connecting the top 25 collaborators of Koji Hino. A scholar is included among the top collaborators of Koji Hino 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 Koji Hino. Koji Hino is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
#WorkIndexed citations
1 11
2 94
3 0
4 1
5
Monitoring RSS Feeds Based on User Browsing Pattern
14
6 160
7 239
8 91
9
Summarization System by Identifying Influential Blogs.
0
10
The Splog Detection Task and A Solution Based on Temporal and Link Properties.
9
11 5
12 7

About Koji Hino

Koji Hino is a scholar working on Statistical and Nonlinear Physics, Information Systems and Artificial Intelligence, having authored 12 papers that have together received 631 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (5 papers), Web Data Mining and Analysis (3 papers) and Peer-to-Peer Network Technologies (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (443 citations), Artificial Intelligence (272 citations) and Computational Mathematics (5 citations). Koji Hino has collaborated with scholars based in United States and Japan. Frequent co-authors include Yün Chi, Belle L. Tseng, Xiaodan Song, Dengyong Zhou, Shenghuo Zhu, Taro Hino, Junghoo Cho, Yihong Gong, Yi Zhang and Junichi Tatemura. Their work appears in journals such as Thin Solid Films, Japanese Journal of Applied Physics and IEEE Transactions on Multimedia.

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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