Mayu Iwata

414 citations
21 papers · 260 · h-index 9

Impact in

Papers in

Mayu Iwata

21 papers receiving 242 citations

Peers

Mayu Iwata
Comparison fields: 5 of 49
  • Computer Science Applications 59
  • Transportation 55
  • Artificial Intelligence 176
  • Information Systems 50
  • Computer Vision and Pattern Recognition 43
Replace Guoxing Zhan with:
Guoxing Zhan United States
Yavuz Selim Yilmaz United States
Wei Tong China
Stylianos Gisdakis Sweden
Dario Freni Italy
Darakhshan Mir United States
Mathieu Cunche France
Toby Xu United States
Honglu Jiang China
Valerio Luconi Italy
Mayu Iwata relative to Guoxing Zhan United States Guoxing Zhan's profile →
Citations per field
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Guoxing Zhan · 1×
Citations per year

Countries citing papers authored by Mayu Iwata

Since Specialization
Citations

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

Fields of papers citing papers by Mayu Iwata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201678
2 201250
3 201037
4 201214
5 201310
6
Overview of the NTCIR-10 1CLICK-2 Task.
20139
7 20129
8 20129
9 20128
10 20227
11 20127
12 20115
13 20114
14 20143
15 20133
16 20142
17
Human Activity Recognition for Content Searching Using a Smartphone
20121
18 20111
19
The wisdom of advertisers: Mining subgoals via query clustering
20121
20 20101

About Mayu Iwata

Mayu Iwata is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing and Sociology and Political Science, having authored 21 papers that have together received 260 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (7 papers), Recommender Systems and Techniques (6 papers), Data Management and Algorithms (5 papers), Context-Aware Activity Recognition Systems (5 papers), Information Retrieval and Search Behavior (5 papers), Privacy-Preserving Technologies in Data (4 papers), Privacy, Security, and Data Protection (3 papers) and Human Mobility and Location-Based Analysis (3 papers). The work is most often cited by research in Computer Science Applications (59 citations), Transportation (55 citations), Artificial Intelligence (176 citations), Information Systems (50 citations) and Computer Vision and Pattern Recognition (43 citations). Mayu Iwata has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Takahiro Hara, Yuki Arase, Xing Xie, Shojiro Nishio, Ryo Kato, Takehiro Yamamoto, Tetsuya Sakai, Makoto P. Kato, Haruo Takemura and Tomohiro Mashita. Their work appears in journals such as Personal and Ubiquitous Computing, IEEE Access, Clinical and Experimental Nephrology, International Journal of Web Information Systems and IEICE Technical Report; IEICE Tech. Rep..

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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