Evidence to support common application switching behaviour on smartphones
暂无分享,去创建一个
Don Towsley | Jian Li | Roger M Whitaker | Stuart M Allen | Liam D. Turner | Kun Tu | S. M. Allen | David E J Linden | Liam D Turner | D. Towsley | Jian Li | S. Allen | R. Whitaker | Kun Tu | D. E. Linden
[1] Stefano Mossa,et al. Truncation of power law behavior in "scale-free" network models due to information filtering. , 2002, Physical review letters.
[2] René Mayrhofer,et al. Diversity in locked and unlocked mobile device usage , 2014, UbiComp Adjunct.
[3] Walid Maalej,et al. Understanding usage states on mobile devices , 2015, UbiComp.
[4] Kimberly Young,et al. Internet Addiction: The Emergence of a New Clinical Disorder , 1998, Cyberpsychology Behav. Soc. Netw..
[5] Donald F. Towsley,et al. Network Classification in Temporal Networks Using Motifs , 2018, ArXiv.
[6] Alla Mashanova,et al. Evidence for intermittency and a truncated power law from highly resolved aphid movement data , 2010, Journal of The Royal Society Interface.
[7] H. Triandis. Cognitive Similarity and Communication in a Dyad , 1960 .
[8] Li Jingwen,et al. Mobile phone addiction , 2015 .
[9] M AllenStuart,et al. Reachable but not receptive , 2017 .
[10] Martin Pielot,et al. When attention is not scarce - detecting boredom from mobile phone usage , 2015, UbiComp.
[11] S. Shen-Orr,et al. Superfamilies of Evolved and Designed Networks , 2004, Science.
[12] A. Baddeley. Working memory: looking back and looking forward , 2003, Nature Reviews Neuroscience.
[13] Azer Bestavros,et al. Self-similarity in World Wide Web traffic: evidence and possible causes , 1996, SIGMETRICS '96.
[14] Saeed Moghaddam,et al. MobileMiner: mining your frequent patterns on your phone , 2014, UbiComp.
[15] Robin I. M. Dunbar,et al. Social network size in humans , 2003, Human nature.
[16] Yunxin Liu,et al. MoodScope: building a mood sensor from smartphone usage patterns , 2013, MobiSys.
[17] Roger M Whitaker,et al. Timing rather than user traits mediates mood sampling on smartphones , 2017, BMC Research Notes.
[18] Jorge Gonçalves,et al. Revisitation analysis of smartphone app use , 2015, UbiComp.
[19] Sriram Subramanian,et al. Proceedings of the 16th international conference on Human-computer interaction with mobile devices & services , 2014, MobileHCI 2014.
[20] Anind K. Dey,et al. ProactiveTasks: the short of mobile device use sessions , 2014, MobileHCI '14.
[21] Zhi-Dan Zhao,et al. Emergence of scaling in human-interest dynamics , 2013, Scientific Reports.
[22] Stuart M. Allen,et al. Pervasive and Mobile Computing , 2022 .
[23] Susan T. Dumais,et al. Large scale analysis of web revisitation patterns , 2008, CHI.
[24] Alessandro Vespignani,et al. The Architecture of Complex Weighted Networks: Measurements and Models , 2007 .
[25] Qiang Xu,et al. Identifying diverse usage behaviors of smartphone apps , 2011, IMC '11.
[26] Yaneer Bar-Yam,et al. Global patterns of synchronization in human communications , 2017, Journal of The Royal Society Interface.
[27] King-Sun Fu,et al. A distance measure between attributed relational graphs for pattern recognition , 1983, IEEE Transactions on Systems, Man, and Cybernetics.
[28] Zhaohui Wu,et al. Discovering different kinds of smartphone users through their application usage behaviors , 2016, UbiComp.
[29] Rosario N. Mantegna,et al. A comparative analysis of the statistical properties of large mobile phone calling networks , 2014, Scientific Reports.
[30] Deborah Estrin,et al. Diversity in smartphone usage , 2010, MobiSys '10.
[31] Jin-Hyuk Hong,et al. Understanding and prediction of mobile application usage for smart phones , 2012, UbiComp.
[32] Albert-László Barabási,et al. Understanding individual human mobility patterns , 2008, Nature.
[33] Albert,et al. Emergence of scaling in random networks , 1999, Science.
[34] H E Stanley,et al. Classes of small-world networks. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[35] Wen-Chih Peng,et al. On mining mobile apps usage behavior for predicting apps usage in smartphones , 2013, CIKM.
[36] Tao Zhou,et al. Diversity of individual mobility patterns and emergence of aggregated scaling laws , 2012, Scientific Reports.
[37] Wen-Chih Peng,et al. Mining Temporal Profiles of Mobile Applications for Usage Prediction , 2012, 2012 IEEE 12th International Conference on Data Mining Workshops.
[38] Johannes Schöning,et al. Falling asleep with Angry Birds, Facebook and Kindle: a large scale study on mobile application usage , 2011, Mobile HCI.
[39] Jure Leskovec,et al. Friendship and mobility: user movement in location-based social networks , 2011, KDD.
[40] Xiaoxiao Ma,et al. Predicting mobile application usage using contextual information , 2012, UbiComp.
[41] Karen Church,et al. An In-Situ Study of Mobile App & Mobile Search Interactions , 2015, CHI.
[42] Dietmar Plenz,et al. powerlaw: A Python Package for Analysis of Heavy-Tailed Distributions , 2013, PloS one.
[43] Francesco Picciolo,et al. Reciprocity of weighted networks , 2012, Scientific Reports.
[44] Sasu Tarkoma,et al. Explaining the power-law distribution of human mobility through transportation modality decomposition , 2014, Scientific Reports.
[45] Stuart M. Allen,et al. Interruptibility prediction for ubiquitous systems: conventions and new directions from a growing field , 2015, UbiComp.
[46] S. Shen-Orr,et al. Networks Network Motifs : Simple Building Blocks of Complex , 2002 .
[47] A Díaz-Guilera,et al. Self-similar community structure in a network of human interactions. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[48] Harry Eugene Stanley,et al. Calling patterns in human communication dynamics , 2013, Proceedings of the National Academy of Sciences.
[49] Antti Oulasvirta,et al. Habits make smartphone use more pervasive , 2011, Personal and Ubiquitous Computing.
[50] S. Shen-Orr,et al. Network motifs: simple building blocks of complex networks. , 2002, Science.
[51] Filip De Turck,et al. Mobile application usage prediction through context-based learning , 2013, J. Ambient Intell. Smart Environ..