A Study of Content-aware Classification of POI

被引:1
|
作者
Chiu, Chieh-Chi [1 ]
Xie, Zhong-Xing [1 ]
Wei, Hsin-Wen [1 ]
Lee, Wei-Tsong [1 ]
机构
[1] Tamkang Univ, Dept Elect & Comp Engn, New Taipei, Taiwan
来源
2017 31ST IEEE INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS (IEEE WAINA 2017) | 2017年
关键词
Classification; machine learning; web crawler; similarity; SVM; kNN;
D O I
10.1109/WAINA.2017.24
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
With the rise of Internet technology and development of mobile application, more and more data and information are around us. However, it is not always easy to find the needed information that people want. Therefore, a good recommendation system is required for giving useful or interesting information. To provide useful information for user, a good classification of data is needed for recommendation system. Good classification of data allows system to process users' requests easily and efficiently, on the other hand, poor classification of data makes recommendation useless and time-consumed. This paper proposes a content-aware classification methodology to clearly classify point of interests (POI) into four different categories, which includes food, clothing, accommodations, and education. The simulation results of different categories show that the accuracy of the proposed classification technique can achieve 90%, 82%, 94%, and 97%, respectively.
引用
收藏
页码:591 / 596
页数:6
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