DataLearner: A Data Mining and Knowledge Discovery Tool for Android Smartphones and Tablets

被引:2
|
作者
Yates, Darren [1 ]
Islam, Md Zahidul [1 ]
Gao, Junbin [2 ]
机构
[1] Charles Sturt Univ, Panorama Ave, Bathurst, NSW 2795, Australia
[2] Univ Sydney, Univ Sydney Business Sch, Sydney, NSW 2006, Australia
关键词
Knowledge discovery; Data mining; Smartphone; Tablet;
D O I
10.1007/978-3-030-35231-8_61
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Smartphones have become the ultimate 'personal' computer, yet despite this, general-purpose data mining and knowledge discovery tools for mobile devices are surprisingly rare. DataLearner is a new data mining application designed specifically for Android devices that imports the Weka data mining engine and augments it with algorithms developed by Charles Sturt University. Moreover, DataLearner can be expanded with additional algorithms. Combined, DataLearner delivers 40 classification, clustering and association rule mining algorithms for model training and evaluation without need for cloud computing resources or network connectivity. It provides the same classification accuracy as PCs and laptops, while doing so with acceptable processing speed and consuming negligible battery life. With its ability to provide easy-to-use data mining on a phone-size screen, DataLearner is a new portable, self-contained data mining tool for remote, personalised and educational applications alike. DataLearner features four elements - this paper, the app available on Google Play, the GPL3-licensed source code on GitHub and a short video on YouTube.
引用
收藏
页码:828 / 838
页数:11
相关论文
共 50 条
  • [21] Knowledge discovery and data mining in toxicology
    Helma, C
    Gottmann, E
    Kramer, S
    STATISTICAL METHODS IN MEDICAL RESEARCH, 2000, 9 (04) : 329 - 358
  • [22] Data mining and knowledge discovery in databases
    Fayyad, U
    Uthurusamy, R
    COMMUNICATIONS OF THE ACM, 1996, 39 (11) : 24 - 26
  • [23] Geographic data mining and knowledge discovery
    Tobón, C
    ENVIRONMENT AND PLANNING B-PLANNING & DESIGN, 2002, 29 (06): : 933 - 934
  • [24] Handbook of data mining and knowledge discovery
    Malthouse, EC
    Mulhern, FJ
    JOURNAL OF MARKETING RESEARCH, 2003, 40 (03) : 372 - 374
  • [25] Knowledge Discovery for Scalable Data Mining
    Chhabra, Indu
    Suri, Gunmala
    EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS, 2019, 6 (21) : 1 - 9
  • [26] Smartphones: A Potential Discovery Tool
    Starkweather, Wendy
    Stowers, Eva
    INFORMATION TECHNOLOGY AND LIBRARIES, 2009, 28 (04) : 187 - 188
  • [27] Data mining and knowledge discovery in databases: An overview
    Zhu, W
    RESEARCH QUARTERLY FOR EXERCISE AND SPORT, 2002, 73 (01) : A37 - A37
  • [28] Knowledge Discovery Processing and Data Mining in Karyometry
    Bartels, Peter H.
    Montironi, Rodolfo
    Scarpelli, Marina
    Bartels, Hubert G.
    Alberts, David S.
    ANALYTICAL AND QUANTITATIVE CYTOLOGY AND HISTOLOGY, 2009, 31 (03): : 125 - 136
  • [29] Cooperative Knowledge Discovery & Data Mining CKDD
    Kechadi, M-Tahar
    Savvas, Ilias K.
    2011 20TH IEEE INTERNATIONAL WORKSHOPS ON ENABLING TECHNOLOGIES: INFRASTRUCTURE FOR COLLABORATIVE ENTERPRISES (WETICE), 2011, : 143 - +
  • [30] Application of Ontologies for Knowledge discovery in data mining
    Branquinho, Lucelia Pinto
    Abrantes Baracho, Renata Maria
    Almeida, Mauricio Barcellos
    ABAKOS, 2015, 4 (01): : 20 - 33