DocumentCode :
3280921
Title :
A feature selection method for comparision of each concept in big data
Author :
Nakanishi, Takafumi
Author_Institution :
Center for Global Commun. (GLOCOM), Int. Univ. of Japan, Tokyo, Japan
fYear :
2015
fDate :
June 28 2015-July 1 2015
Firstpage :
229
Lastpage :
234
Abstract :
In this paper, we present a new feature selection method for comparison of each event in big data. The method selects appropriate features for comparing or evaluating each event when we prepare an event set. There are massive data on the Internet as big data. We have been able to retrieve appropriate data sets from them by using given keywords. However, it is still difficult to use these data to compare some concepts. For example, when you would like to compare the difference between your company and a rival company, it is difficult to compare them, because evaluation axes are needed to compare them. This method extracts evaluation axes as features in a data-driven manner. We can compare them by using the extracted axes as the features. This means that the system automatically selects the appropriate features which we should focus on when we compare them.
Keywords :
Big Data; Internet; Internet; big data; data-driven manner; evaluation axes; feature selection method; keywords; massive data; rival company; Aggregates; Big data; Companies; Context; Estimation; Feature extraction; Internet; big data; context-dependent; data-driven; feature selection; semantic computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on
Conference_Location :
Las Vegas, NV
Type :
conf
DOI :
10.1109/ICIS.2015.7166598
Filename :
7166598
Link To Document :
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