Evaluation and Functionality Stems Extraction for App Categorization on Apple iTunes Store by Using Mixed Methods : Data Mining for Categorization Improvement

논문상세정보
    • 저자 Zhang, Chao Lili Wan
    • 제어번호 105429603
    • 학술지명 한국IT서비스학회지
    • 권호사항 Vol. 17 No. 2 [ 2018 ]
    • 발행처 한국IT서비스학회
    • 발행처 URL http://www.itservice.or.kr
    • 자료유형 학술저널
    • 수록면 111-128
    • 언어 English
    • 출판년도 2018
    • 등재정보 KCI등재
    • 판매처
    유사주제 논문( 0)

' Evaluation and Functionality Stems Extraction for App Categorization on Apple iTunes Store by Using Mixed Methods : Data Mining for Categorization Improvement' 의 참고문헌

  • Wise mobile icons organization : Apps taxonomy classification using functionality mining to ease apps finding
  • Using supervised learning to classify clothing brand styles
  • Sentiment Analysis on Unstructured Review
    Nithya, R. [2014]
  • Persuasive Design Principles of Car Apps
    Zhang C. [2016]
  • Numeric rating of Apps on Google Play Store by sentiment analysis on user reviews
  • Naive Bayes Modeling with Proper Smoothing for Information Extraction
    Gu, Z. [2006]
  • Multi-store metadata-based supervised mobile app classification
    Berardi, G. [2015]
  • Modern information retrieval vol. 9.
  • Mobile app classification with enriched contextual information
    Zhu, H. [2014]
  • Medical Data Classification with Naive Bayes Approach
  • Machine learning for information extraction in informal domains
    Freitag, D. [2000]
  • Low Cost Portability for Statistical Machine Translation based on N-gram Frequency and TF-IDF
    Eck, M. [2005]
  • Learning Weighted Naive Bayes with Accurate Ranking
    Zhang, H. [2004]
  • Exploiting enriched contextual information for mobile app classification
    Zhu, H. [2012]
  • Checking app behavior against app descriptions
    Gorla, A. [2014]
  • Categorizing Software Applications for Maintenance
  • Car App's Persuasive Design Principles and Behavior Change
    Zhang C. [2016]
  • Bug report, feature request, or simply praise? On automatically classifying app reviews
    Maalej, W. [2015]
  • Applying Naïve Bayes Classification to Google Play Apps Categorization
  • App Miscategorization Detection : A Case Study on Google Play
    Surian, D. [2017]
  • An Effective Algorithm for Improving the Performance of Naive Bayes for Text Classification
    Guo, Q. [2010]
  • An Approach to Spam Detection by Naive Bayes Ensemble Based on Decision Induction
    Yang, Z. [2006]
  • A Classification of Car-related Mobile Apps: For App Development from a Convergence Perspective
    Zhang, Chao [2017]