Mobile WEKA as Data Mining Tool on Android

被引:0
|
作者
Liu, Pengfei [1 ]
Chen, Yanhua [1 ]
Tang, Wulei [2 ]
Yue, Qiang [3 ]
机构
[1] South China Agr Univ, Coll Sci, Guangzhou 510642, Guangdong, Peoples R China
[2] SoftPk Guangdong, Guangzhou 510663, Guangdong, Peoples R China
[3] Guangdong Nortel Telecommun Co Ltd, Guangzhou 510665, Guangdong, Peoples R China
关键词
Mobile; Data mining; Machine learning;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile data mining is an exciting research area that aims at finding interesting patterns from datasets on mobile platform. Limited to the computing power and operating system of traditional mobile devices, mobile data mining lacks attention before. Nowadays mobile devices have a stronger and stronger computation power also the advanced operating system supporting the demand of data mining anywhere and anytime. This paper presents and implements a Java based framework to extend data mining tool Weka to mobile platform. It provides a friendly graphic user interface and simplifies the classification, clustering and associate rule mining functions on android platforms. As an example of usage, we test the model on some datasets and illustrate the feasibility of the proposed approach. A Java implementation of the model demonstrated in this article is available from mobileWeka project website. http://mohileweka.googlecode.com/files/MohileWeka.zip.
引用
收藏
页码:75 / +
页数:2
相关论文
共 50 条
  • [21] A Comparative Analysis of Data Mining Techniques on Breast Cancer Diagnosis Data using WEKA Toolbox
    Alshammari, Majdah
    Mezher, Mohammad
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2020, 11 (08) : 224 - 229
  • [22] Analyzing association rule mining and clustering on sales day data with xlminer and weka
    Khattak, A.M.
    Khan, A.M.
    Lee, Sungyoung
    Lee, Young-Koo
    International Journal of Database Theory and Application, 2010, 3 (01): : 13 - 22
  • [23] FlexDM: Simple, parallel and fault-tolerant data mining using WEKA
    Flannery, Madison
    Budden, David M.
    Mendes, Alexandre
    SOURCE CODE FOR BIOLOGY AND MEDICINE, 2015, 10
  • [24] Comprehensive Study of Data Analytics Tools (RapidMiner, Weka, R tool, Knime)
    Dwivedi, Shraddha
    Kasliwal, Paridhi
    Soni, Suryakant
    2016 SYMPOSIUM ON COLOSSAL DATA ANALYSIS AND NETWORKING (CDAN), 2016,
  • [25] Data Security Evaluation for Mobile Android Devices
    Khokhlov, Igor
    Reznik, Leon
    PROCEEDINGS OF THE 20TH CONFERENCE OF OPEN INNOVATIONS ASSOCIATION (FRUCT 2017), 2017, : 154 - 160
  • [26] Android Mobile Forensic Analyzer for Stegno data
    Mambodza, Walter T.
    Meeran, Nagoor A. R.
    2015 INTERNATIONAL CONFERENCED ON CIRCUITS, POWER AND COMPUTING TECHNOLOGIES (ICCPCT-2015), 2015,
  • [27] Another data mining tool
    Mason, RL
    Young, JC
    QUALITY PROGRESS, 2003, 36 (02) : 76 - 79
  • [28] Outcomes of educational interventions in type 2 diabetes: WEKA data-mining analysis
    Sigurdardottir, Arun K.
    Jonsdottir, Helga
    Benediktsson, Rafn
    PATIENT EDUCATION AND COUNSELING, 2007, 67 (1-2) : 21 - 31
  • [29] A tool for data mining support
    Hubal, M
    Bednár, P
    INTELLIGENT TECHNOLOGIES - THEORY AND APPLICATIONS: NEW TRENDS IN INTELLIGENT TECHNOLOGIES, 2002, 76 : 196 - 200
  • [30] DELTA: Data Extraction and Logging Tool for Android
    Spolaor, Riccardo
    Dal Santo, Elia
    Conti, Mauro
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2018, 17 (06) : 1289 - 1302