XWRAP: an XML-enabled wrapper construction system for Web information sources

By Ling Liu, Calton Pu, Wei Han. Proceedings / International Conference on Data Engineering, 2000

527 citations recorded by the source corpus.

Subfields: Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/7430414e85f9b85095a716b68bea98b30ebaab30

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Citations in the corpus

Extracting structured data from Web pages (2003, methodology): “More recent systems like XWRAP [18], WIEN [15], STALKER [19], and SOFTMEALY [13] use human generated training examples that identify data in a small number of pages, to learn knowledge of the template.”
Fully automatic wrapper generation for search engines (2005, methodology): “Earlier works are mainly semiautomatic or even manual [1, 3, 9, 15, 18, 21, 23].”
A Survey of Web Information Extraction Systems (2006, methodology): “In the first phase, XWrap fetches, cleans up, and generates a tree-like structure for the page.”
ViDE: A Vision-Based Approach for Deep Web Data Extraction (2010, background): “The latter, such as W4F [24] and XWrap [19], parses the document into a hierarchical tree (DOM tree), based on which they perform the extraction process.”
Web Data Extraction System (2009, unknown): “While the academic projects such as XWRAP [11], Lixto [2], Wargo [13], and the commercial systems RoboMaker of Kapow technologies1 and WebQL of QL2 Software2 focused on methods of strongly supervised “semi-automatic” wrapper generation, providing a wrapper designer with visual and interactive suppor”
A brief survey of web data extraction tools (2002, methodology): “Recently, many tools have been proposed to better address the issue of generating wrappers for Web data extraction [3, 4, 8, 9, 10, 11, 14, 16, 18, 20, 23 , 28, 30, 31].”
Data extraction and label assignment for web databases (2003, methodology): “Since such information only exists in the back-end databases of the various notebook vendors, the user has to go to the web site of each notebook vendor, send his/her queries, extract the relevant information from the result web pages and compare or integrate the results manually.”
Zero-shot Entity Extraction from Web Pages (2014, methodology): “We represent each web page w as a DOM tree, a common representation among wrapper induction and web information extraction systems (Sahuguet and Azavant, 1999; Liu et al., 2000; Crescenzi et al., 2001).”