Frequent pattern mining in mobile devices: A feasibility study
作者： Muhammad Habib ur Rehman , Chee Sun Liew , Teh Ying Wah
DOI: 10.1109/ICIMU.2014.7066658
关键词:
摘要: The availability of computational power in mobile devices is key-enabler for Mobile Data Mining (MDM) at user-premises. Alternately, resource-constraints like limited energy, narrow bandwidth, and small screens challenge adoption MDM. Currently, MDM based on light-weight algorithms that are adaptive resource-constrained environments but a study to evaluate the performance general still lacks literature. To this end, we have studied six Frequent Pattern (FPM) deployed them feasibility highlighted associated challenges. experiments were performed real synthetic data sets strictly android-based device compared with PC-based setup. experimental results show FPM can leverage after tuning some basic parameters.
sci-hub.se 参考文章(22)
M. Harbach, P. Haghighi, M. Gaber, S. Krishnaswamy, A. Sinha, C. Hugues, A. Zaslavsky, B. Gillick, Open Mobile Miner: a toolkit for mobile data stream mining knowledge discovery and data mining. ,(2009)
Frederic Stahl, Mohamed Medhat Gaber, Paul Aldridge, David May, Han Liu, Max Bramer, Philip S. Yu, Homogeneous and heterogeneous distributed classification for pocket data mining Transactions on Large-Scale Data- and Knowledge-Centered Systems V. ,vol. 5, pp. 183- 205 ,(2012) , 10.1007/978-3-642-28148-8_8
Pengfei Liu, Yanhua Chen, Wulei Tang, Qiang Yue, Mobile WEKA as Data Mining Tool on Android Springer, Berlin, Heidelberg. pp. 75- 80 ,(2012) , 10.1007/978-3-642-27951-5_11
Mohamed Medhat Gaber, Frederic Stahl, João Bártolo Gomes, Pocket Data Mining Framework Springer International Publishing. pp. 23- 40 ,(2014) , 10.1007/978-3-319-02711-1_3
Ramakrishnan Srikant, Rakesh Agrawal, Fast algorithms for mining association rules very large data bases. pp. 580- 592 ,(1998)
João Bártolo Gomes, Shonali Krishnaswamy, Mohamed M. Gaber, Pedro A. C. Sousa, Ernestina Menasalvas, Mobile activity recognition using ubiquitous data stream mining data warehousing and knowledge discovery. pp. 130- 141 ,(2012) , 10.1007/978-3-642-32584-7_11
Wanita Sherchan, Prem P. Jayaraman, Shonali Krishnaswamy, Arkady Zaslavsky, Seng Loke, Abhijat Sinha, Using On-the-Move Mining for Mobile Crowdsensing mobile data management. pp. 115- 124 ,(2012) , 10.1109/MDM.2012.58
Henar Martín, Ana M. Bernardos, Josué Iglesias, José R. Casar, Activity logging using lightweight classification techniques in mobile devices ubiquitous computing. ,vol. 17, pp. 675- 695 ,(2013) , 10.1007/S00779-012-0515-4
Héctor Solar, Erik Fernández, Gennaro Tartarisco, Giovanni Pioggia, Božidara Cvetković, Simon Kozina, Mitja Luštrek, Jure Lampe, A Non Invasive, Wearable Sensor Platform for Multi-parametric Remote Monitoring in CHF Patients Impact Analysis of Solutions for Chronic Disease Prevention and Management. pp. 140- 147 ,(2012) , 10.1007/978-3-642-30779-9_18
Zhung-Xun Liao, Shou-Chung Li, Wen-Chih Peng, Philip S. Yu, Te-Chuan Liu, On the Feature Discovery for App Usage Prediction in Smartphones international conference on data mining. pp. 1127- 1132 ,(2013) , 10.1109/ICDM.2013.130