文章基本信息

标题：Data Extraction Based on Page Structure Analysis
本地全文：下载
作者：Yichao Ren ; Jiayin Tian
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2017
卷号：139
页码：1-6
DOI：10.1051/matecconf/201713900118
语种：English
出版社：EDP Sciences
摘要：The information we need has some confusing problems such as dispersion and different organizational structure. In addition, because of the existence of unstructured data like natural language and images, extracting local content pages is extremely difficult. In the light of of the problems above, this article will apply a method combined with page structure analysis algorithm and page data extraction algorithm to accomplish the gathering of network data. In this way, the problem that traditional complex extraction model behave poorly when dealing with large-scale data is perfectly solved and the page data extraction efficiency is also boosted to a new level. In the meantime, the article will also make a comparison about pages and content of different types between the methods of DOM structure based on the page and HTML regularities of distribution. After all of those, we may find a more efficient extract method.
关键词：enPage Structure AnalysisData ExtractionJSON