NDLI: Layered and Weighted Tree Matching Algorithm for Automatic Web Data Records Recognition

Content Provider	IEEE Xplore Digital Library
Author	Shengsheng Shi Fuliang Quan Tao Xie Chunfeng Yuan Yihua Huang
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Technol., Nanjing Univ., Nanjing, China (Shengsheng Shi; Fuliang Quan; Tao Xie; Chunfeng Yuan; Yihua Huang)
Abstract	Automated web data record analysis and recognition is an important issue for improving the automation of web information extraction. Some typical methods perform similar data record analysis based on Simple Tree Matching (STM) algorithm. However, STM assigns elements the same weight and neglects the different impacts of different types of elements. Thus much noise would be induced during data record analysis, which eventually decreases the precision of data record recognition. This paper proposes a Layered and Weighted Tree Matching (LWTM) algorithm. First, we propose a layered filtering strategy to filter out potential noise elements. Then, we propose a weighted tree matching algorithm which assigns different weights for different types of HTML elements in terms of their importance for data record analysis. Further we combine the layered filtering strategy and the weighted tree matching algorithm to further improve the analysis results. Experimental results show that the proposed LWTM algorithm outperforms the STM-based methods.
Starting Page	55
Ending Page	60
File Size	816437
Page Count	6
File Format	PDF
ISBN	9781479932184
e-ISBN	9781479932191
DOI	10.1109/WISA.2013.19
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Filtering HTML tag tree Web pages Weighted tree matching Vegetation Layered filtering strategy HTML Layered and weighted tree matching Data mining Data record recognition Simple tree matching
Content Type	Text
Resource Type	Article

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