Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 453-457.

• Big Data & Data Mining • Previous Articles     Next Articles

Next Place Prediction of Massively Multiplayer Online Role-playing Games

TONG Zhen-ming1, LIU Zhi-peng2   

  1. College of Computer Science and Engineering,Sanjiang University,Nanjing 210012,China1
    School of Modern Posts and Institute of Modern Posts,Nanjing University of Posts and Telecommunications,Nanjing 210003,China2
  • Online:2019-02-26 Published:2019-02-26

Abstract: In recent years,massively multiplayer online role-playing games (MMORPG) has become one of the most popular Internet recreational activities.MMORPG creates virtual societies,in which each user plays a fictional character,and controls most of its activities.With rapid development of MMORPG,it has accumulated massive data,which contain semantic as well as topological information of virtual societies.Researchers have already carried out manystu-dies,such as player departure prediction and server consolidation.The task of next place prediction is crucial to enhance gaming experience,improve game design and game bot detection,and most of next place prediction methods are based on statistical analysis.However,it is difficult to apply these methods in practice due to the characteristic of large scale of game data,and an automatic computation method to be developed.This paper proposed a next place prediction algorithm based on hidden Markov model (HMM).The model considers location characteristics as unobservable parameters,and takes the effects of previous actions of each game character into consideration.Experimental results with real MMORPG dataset show that our approach is intuitive and has better performance in dense distributed data than other existing methods for the task of next place prediction of MMORPG.

Key words: Game data mining, Hidden Markov model, MMORPG, Next place prediction

CLC Number: 

  • TP391
[1]NARDI B,HARRIS J.Strangers and friends:Collaborative play in World of Warcraft[C]∥International Handbook of Internet Research.Springer,2010:395-410.
[2]LEE Y T,CHEN K T,CHENG Y M,et al.World of Warcraft avatar history dataset[C]∥Proceedings of the Second Annual ACM Conference on Multimedia Systems.ACM,2011:123-128.
[3]TARNG P Y,CHEN K T,HUANG P.On prophesying online gamer departure[C]∥2009 8th Annual Workshop on Network and Systems Support for Games (NetGames).IEEE,2009:1-2.
[4]LEE Y T,CHEN K T.Is server consolidation beneficial to MMORPG? A case study of World of Warcraft[C]∥2010 IEEE 3rd International Conference on Cloud Computing (CLOUD).IEEE,2010:435-442.
[5]CHEN K T,PAO H K K,CHANG H C.Game bot identification based on manifold learning[C]∥Proceedings of the 7th ACM SIGCOMM Workshop on Network and System Support for Games.ACM,2008:21-26.
[6]CHEN K T,LIAO A,PAO H K K,et al.Game bot detection based on avatar trajectory[C]∥Entertainment Computing-ICEC 2008. Springer,2009:94-105.
[7]DUCHENEAUT N,YEE N,NICKELL E,et al.The life and death of online gaming communities:a look at guilds in world of warcraft[C]∥Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.ACM,2007:839-848.
[8]DUCHENEAUT N,YEE N,NICKELL E,et al.Building an MMO with mass appeal a look at gameplay in world of warcraft[J].Games and Culture,2006,1(4):281-317.
[9]MITTERHOFER S,PLATZER C,KRUEGEL C,et al.Server-side bot detection in massive multiplayer online games[J].IEEE Security and Privacy,2009,7(3):29-36.
[10]PLATZER C.Sequence-based bot detection in massive multi-player online games[C]∥2011 8th International Conference on Information,Communications and Signal Processing (ICICS).IEEE,2011:1-5.
[11]ETTER V,KAFSI M,KAZEMI E.Been there,done that:What your mobility traces reveal about your behavior[C]∥Mobile Data Challenge by Nokia Workshop,in Conjunction with Int Conf on Pervasive Computing.2012.
[12]WANG J,PRABHALA B.Periodicity based next place prediction[C]∥Nokia Mobile Data Challenge 2012 Workshop Dedicated Task.Citeseer,2012.
[13]GAO H,TANG J,LIU H.Mobile location prediction in spatio-temporal context[C]∥Nokia Mobile Data Challenge Workshop.Citeseer,2012.
[14]BAUMANN P,KLEIMINGER W,SANTINI S.The influence of temporal and spatial features on the performance of next-place prediction algorithms[C]∥Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing.ACM,2013:449-458.
[15]TRAN L H,CATASTA M,MCDOWELL L K,et al.Next Place Prediction using Mobile Data[C]∥Proceedings of the Mobile Data Challenge Workshop (MDC 2012).2012.
[16]NOULAS A,SCELLATO S,LATHIA N,et al.Mining User Mobility Features for Next Place Prediction in Location-Based Services[C]∥ICDM.Citeseer,2012:1038-1043.
[17]DUDA R O,HART P E,STORK D G.Pattern classification[M].John Wiley & Sons,1999.
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