TY - JOUR
T1 - A considerate application prediction system with artificial neural network
AU - Hasumi, Daichi
AU - Kamioka, Eiji
N1 - Publisher Copyright:
© 2014 The Authors. Published by Elsevier B.V.
PY - 2014
Y1 - 2014
N2 - Personal computer is one of the indispensable tools at work and in everyday life. Some of application programs in the computer are habitually used or launched in a particular time. Even though their invocations can be predicted in advance, they are executed manually in each time, hence, this results in a deterioration of the usability in computer operation. In this paper, a considerable application prediction system with Artificial Neural Network, which recommends a useful application for the user at the time, will be proposed. It refers to an application ontology and uses an application log obtained from the user's personal computer. Moreover, the effectiveness of the proposed system will be discussed showing the prediction accuracy of about 90% in recommending useful applications when the user utilizes the computer in daily life.
AB - Personal computer is one of the indispensable tools at work and in everyday life. Some of application programs in the computer are habitually used or launched in a particular time. Even though their invocations can be predicted in advance, they are executed manually in each time, hence, this results in a deterioration of the usability in computer operation. In this paper, a considerable application prediction system with Artificial Neural Network, which recommends a useful application for the user at the time, will be proposed. It refers to an application ontology and uses an application log obtained from the user's personal computer. Moreover, the effectiveness of the proposed system will be discussed showing the prediction accuracy of about 90% in recommending useful applications when the user utilizes the computer in daily life.
KW - Application Log
KW - Artificial Neural Network
KW - Machine Learning
KW - Recommendation System
UR - http://www.scopus.com/inward/record.url?scp=84924146963&partnerID=8YFLogxK
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U2 - 10.1016/j.procs.2014.08.238
DO - 10.1016/j.procs.2014.08.238
M3 - Conference article
AN - SCOPUS:84924146963
SN - 1877-0509
VL - 35
SP - 1547
EP - 1556
JO - Procedia Computer Science
JF - Procedia Computer Science
IS - C
T2 - International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2014
Y2 - 15 September 2014 through 17 September 2014
ER -