Countries citing papers authored by Masayuki Numao
Since
Specialization
Citations
This map shows the geographic impact of Masayuki Numao'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 Masayuki Numao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masayuki Numao more than expected).
This network shows the impact of papers produced by Masayuki Numao. 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 Masayuki Numao. The network helps show where Masayuki Numao may publish in the future.
Co-authorship network of co-authors of Masayuki Numao
This figure shows the co-authorship network connecting the top 25 collaborators of Masayuki Numao.
A scholar is included among the top collaborators of Masayuki Numao 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 Masayuki Numao. Masayuki Numao is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Numao, Masayuki, et al.. (2018). IoT-based Emotion Recognition Robot to Enhance Sense of Community in Nursing Home.. National Conference on Artificial Intelligence.1 indexed citations
6.
Numao, Masayuki, et al.. (2017). Sensor-Based Detection of Invisible Changes in Activities towards Visualizing Disuse Syndrome.. National Conference on Artificial Intelligence.1 indexed citations
7.
Numao, Masayuki, et al.. (2016). Non-Restrictive Continuous Health Monitoring by Integration of RFID and Microwave Sensor.. National Conference on Artificial Intelligence.1 indexed citations
Inventado, Paul Salvador, et al.. (2013). An analysis of affective state transitions in survival horror game with the aid of player self-reports and physiological signals. 27. 1–6.
Inventado, Paul Salvador, et al.. (2011). Investigating the transitions between learning and non-learning activities as students learn online. Educational Data Mining. 367–368.1 indexed citations
13.
Li, Wen‐Syan, et al.. (2007). Deadline and QoS aware data warehouse. Very Large Data Bases. 1418–1421.2 indexed citations
14.
Numao, Masayuki, et al.. (2005). Active mining : second International Workshop, AM 2003, Maebashi, Japan, October 28, 2003 : revised selected papers. Springer eBooks.1 indexed citations
15.
Tsumoto, Shusaku, Takahira Yamaguchi, Masayuki Numao, & Hiroshi Motoda. (2005). Active Mining: Second International Workshop, AM 2003, Maebashi, Japan, October 28, 2003, Revised Selected Papers (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence). Springer eBooks.4 indexed citations
Numao, Masayuki, et al.. (2000). Ordered Estimation of Missing Values for Propositional Learning. 15(1). 162–168.6 indexed citations
20.
Numao, Masayuki, et al.. (1997). Acquisition of human feelings in music arrangement. International Joint Conference on Artificial Intelligence. 268–273.11 indexed citations
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.