Vision Based Important Change Detection Method for Web Pages
SHI Cunhui1,2, YU Xiaoming1, LIU Yue1, JIN Xiaolong1,2, CHENG Xueqi1,2
1. Key Laboratory of Network Data Science and Technology,Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190; 2. School of Computer Science and Technology,University of Chinese Academy of Sciences,Beijing 100049
Abstract：Duplicate Web indexes of Web crawling can be reduced effectively by detecting important changes and determining changes of essential content in Web pages.Therefore,a vision based detection method is proposed to detect changes in different semantic regions of the page and compress the page into a low dimensional vector representation.The proposed method is utilized to understand the difference of semantic importance in different regions from the perspective of users.Compared with the existing methods,the proposed method is independent of the analysis of HTML,and thus it is suitable for new media,such as mobile Internet.Experiments show the effectiveness of the proposed method.
史存会, 俞晓明, 刘悦, 靳小龙, 程学旗. 基于视觉的网页重要变化检测方法[J]. 模式识别与人工智能, 2020, 33(11): 1004-1012.
SHI Cunhui, YU Xiaoming, LIU Yue, JIN Xiaolong, CHENG Xueqi. Vision Based Important Change Detection Method for Web Pages. , 2020, 33(11): 1004-1012.
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2020, Vol. 33 
