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Non-Negative Tensor Factorization for Human Behavioral Pattern Mining in Online Games
- Source :
- Information, Vol 9, Iss 3, p 66 (2018), Information; Volume 9; Issue 3; Pages: 66
- Publication Year :
- 2018
- Publisher :
- MDPI AG, 2018.
-
Abstract
- Multiplayer online battle arena has become a popular game genre. It also received increasing attention from our research community because they provide a wealth of information about human interactions and behaviors. A major problem is extracting meaningful patterns of activity from this type of data, in a way that is also easy to interpret. Here, we propose to exploit tensor decomposition techniques, and in particular Non-negative Tensor Factorization, to discover hidden correlated behavioral patterns of play in a popular game: League of Legends. We first collect the entire gaming history of a group of about one thousand players, totaling roughly $100K$ matches. By applying our methodological framework, we then separate players into groups that exhibit similar features and playing strategies, as well as similar temporal trajectories, i.e., behavioral progressions over the course of their gaming history: this will allow us to investigate how players learn and improve their skills.<br />Comment: 9 pages, 6 figures, submitted to KDD'17
- Subjects :
- FOS: Computer and information sciences
Physics - Physics and Society
Non-negative Tensor Factorization
Computer science
Computer Science - Human-Computer Interaction
FOS: Physical sciences
Physics and Society (physics.soc-ph)
02 engineering and technology
League
Machine learning
computer.software_genre
01 natural sciences
Machine Learning (cs.LG)
Human-Computer Interaction (cs.HC)
Research community
0202 electrical engineering, electronic engineering, information engineering
Leverage (statistics)
Social and Information Networks (cs.SI)
multiplayer online game
Tensor factorization
lcsh:T58.5-58.64
lcsh:Information technology
business.industry
Group (mathematics)
010401 analytical chemistry
ComputingMilieux_PERSONALCOMPUTING
Behavioral pattern
Computer Science - Social and Information Networks
human behavior
0104 chemical sciences
Computer Science - Learning
020201 artificial intelligence & image processing
Artificial intelligence
business
computer
temporal and topological pattern mining
Information Systems
Cognitive psychology
Subjects
Details
- ISSN :
- 20782489
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Information
- Accession number :
- edsair.doi.dedup.....62d80d85e8295c3b0ac02201660fbdb3