In this paper, we present an approach and a visual tool, called HWrap (Handle Based Wrapper), for creating web wrappers to extract data records from web pages. In our approach, we mainly rely on the visible page content to identify data regions on a web page. In our extraction algorithm, we inspired by the way a human user scans the page content for specific data. In particular, we use text fea...

In spite of extensive study of information extraction from web pages, the existing methods fail to extract all the data from the web pages. Also, the existing methods divide the data extraction into two phases, namely, record region detection and record segmentation. In this paper, we proposed a unified method for data extraction from a structured web page. We propose a new search structure Rec...

The World Wide Web has been extensively developed since its first appearance two decades ago. Various applications on the Web have unprecedentedly changed humans’ life. Although the explosive growth and spread of the Web have resulted in a huge information repository, yet it is still under-utilized due to the difficulty in automated information extraction (IE) caused by the heterogeneity of Web...

The vast amount of online information available has led to renewed interest in information extraction (IE) systems that analyze input documents to produce a structured representation of selected information from the documents. Information extraction from semistructured documents has been studied extensively recently. Most researches focus on supervised learning approaches where targets must be ...

AUTOMATING THE EXTRACTION OF DOMAIN SPECIFIC INFORMATION FROM THE WEB—A CASE STUDY FOR THE GENEALOGICAL DOMAIN Troy Walker Department of Computer Science Master of Science Current ways of finding genealogical information within the millions of pages on the Web are inadequate. In an effort to help genealogical researchers find desired information more quickly, we have developed GeneTIQS, a Genea...

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...

This paper studies the problem of identification and extraction of flat and nested data records from a given web page. With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright n...

Electronically available data on the Web is exploding at an ever increasing pace. Much of this data is unstructured, which makes searching hard and traditional database querying impossible. Many Web documents, however, contain an abundance of recognizable constants that together describe the essence of a document’s content. For these kinds of data-rich, multiple-record documents (e.g. advertise...

Existing template-independent web data extraction approaches adopt highly ineffective decoupled strategies—attempting to do data record detection and attribute labeling in two separate phases. In this paper, we propose an integrated web data extraction paradigm with hierarchical models. The proposed model is called Dynamic Hierarchical Markov Random Fields (DHMRFs). DHMRFs take structural uncer...