Structured Data Extraction from the Deep Web

Structured Data Extraction from the Web

Unsupervised Structured Data Extraction from Template-generated Web Pages

This paper studies structured data extraction from template-generated Web pages. Such pages contain most of structured data on the Web. Extracted structured data can be later integrated and reused in very big range of applications, such as price comparison portals, business intelligence tools, various mashups and etc. It encourages industry and academics to seek automatic solutions. To tackle t...

Automatic Extraction of Semi-structured Web Data

As a huge data source the internet contains a large number of valuable information, and the data of information is usually in the form of semi-structured in HTML web pages. In order to extract the web data and organize the data with the relationships which are similar to the real world, this paper has proposed a method for automatic data extraction from the web. With the combination of keywords...

Towards Automatic Structured Web Data Extraction System

Automatic extraction of structured data from web pages is one of the key challenges for the Web search engines to advance into the more expressive semantic level. Here we propose a novel data extraction method, called ClustVX. It exploits visual as well as structural features of web page elements to group them into semantically similar clusters. Resulting clusters reflect the page structure and...

Vision-Based Deep Web Data Extraction for Web Document Clustering

The design of web information extraction systems becomes more complex and time-consuming. Detection of data region is a significant problem for information extraction from the web page. In this paper, an approach to vision-based deep web data extraction is proposed for web document clustering. The proposed approach comprises of two phases: 1) Vision-based web data extraction, and 2) web documen...