Stratification-Based Outlier Detection over the Deep Web.
For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web.
Department of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215002, China; School of Computer Engineering, Suzhou Vocational University, Suzhou, Jiangsu 215104, China.
Xuefeng
X
Xian
Department of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215002, China.
Pengpeng
P
Zhao
Computer Science Department, University of Central Arkansas, Conway, AR 72035, USA.
Victor S
VS
Sheng
School of Computer Engineering, Suzhou Vocational University, Suzhou, Jiangsu 215104, China.
Ligang
L
Fang
School of Computer Engineering, Suzhou Vocational University, Suzhou, Jiangsu 215104, China.
Caidong
C
Gu
School of Computer Engineering, Suzhou Vocational University, Suzhou, Jiangsu 215104, China.
Yuanfeng
Y
Yang
Department of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215002, China; School of Computer Engineering, Suzhou Vocational University, Suzhou, Jiangsu 215104, China.
Zhiming
Z
Cui
D000465:Algorithms; D003132:Commerce; D003628:Database Management Systems; D006801:Humans; D016247:Information Storage and Retrieval; D020407:Internet