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The proposed approach\nconsists of two visualization techniques: classical\nmultidimensional scaling (CMDS) and KeyGraph.\nCMDS is for discovering clusters of players who behave\nsimilarly. KeyGraph is for interpreting action\nbehaviors of players in a cluster of interest. In order\nto reduce the dimension of matrices used in computation\nof the CMDS input, we exploit a time\u2010series reduction\ntechnique recently proposed by us. Our visualization\napproach is evaluated using log of an online\ngame where three\u2010player types according to Bartle\u2032s\ntaxonomy are found, that is, achievers, explorers, and socializers.<\/jats:p>","DOI":"10.1155\/2008\/906931","type":"journal-article","created":{"date-parts":[[2008,12,22]],"date-time":"2008-12-22T14:10:26Z","timestamp":1229955026000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Visualization of Online\u2010Game Players Based on  Their  Action Behaviors"],"prefix":"10.1155","volume":"2008","author":[{"given":"Ruck","family":"Thawonmas","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keita","family":"Iizuka","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2008,8,18]]},"reference":[{"key":"e_1_2_7_1_2","unstructured":"Harding-RollsP. 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