• Aug 09, 2018 News![CFP] The annual meeting of IJFCC Editorial Board, ICCTD 2019, will be held in Prague, Czech Republic during March 2-4, 2019.   [Click]
  • Aug 09, 2018 News!IJFCC Vol. 6, No. 1-No. 3 has been indexed by EI (Inspec).   [Click]
  • Dec 24, 2018 News!The papers published in Vol.7, No.1-No.2 have all received dois from Crossref.
General Information
    • ISSN: 2010-3751
    • Frequency: Bimonthly (2012-2016); Quarterly (Since 2017)
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Cherry L. Chan
    • Abstracting/ Indexing: Google Scholar,  Crossref, Electronic Journals LibraryEI (INSPEC, IET), etc.
    • E-mail:  ijfcc@ejournal.net 
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2018 Vol.7(2): 32-36 ISSN: 2010-3751
DOI: 10.18178/ijfcc.2018.7.2.516

Human Activity Analysis and Prediction Using Google n-Grams

İlknur Dönmez
Abstract—There seems to be no compelling reason to argue that the importance of data is increasing. The huge data from social environments, internet of things and online books can be collected and processed easily via today technology. In social life and business the user and costumer oriented approaches become more important. User behavior, user features and user opinion are searched in different applications. In this paper the human activities are extracted and analyzed using Google-n grams. Google-n grams are generated from millions of books between 1500 to 2000 which can be an indicator for human specific feature and behavior. In this paper human specific main activities are analyzed and the human activities in near feature are predicted via Google n-grams and the functions which are generated via using n-grams.

Index Terms—Google n-grams, activity extraction, activity prediction, human activity mining.

The author is with the Computer Engineering Department, İstanbul Bilgi University in İstanbul, Turkey, (e-mail: ilknur.buyukkuscu@hotmail.com).


Cite: İlknur Dönmez, "Human Activity Analysis and Prediction Using Google n-Grams," International Journal of Future Computer and Communication vol. 7, no. 2, pp. 页码, 2018.

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