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).
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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.
