RoadRunner: Towards Automatic Data Extraction from Large Web Sites

By Valter Crescenzi, Giansalvatore Mecca, Paolo Merialdo. 2001

1,172 citations recorded by the source corpus.

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Citations in the corpus

A Survey on Data Collection for Machine Learning: A Big Data - AI Integration Perspective (2018, methodology): “Early work include RoadRunner [139], which compares HTML pages to generates wrappers and KnowItAll [140], which uses extraction rules and a search engine to identify and rank facts.”
Trafilatura: A Web Scraping Library and Command-Line Tool for Text Discovery and Extraction (2021, methodology): “Data extraction has ﬁrst been based on “wrappers” (now called “scrapers”) which were mostly relying on manual design and tended to be brittle and hard to maintain (Crescenzi et al., 2001).”
Structured databases on the web: observations and implications (2004, methodology): “References [26, 27, 28] discuss data extraction techniques (or “wrappers”), targeting at HTML pages generated by backend databases.”
A Survey of Web Information Extraction Systems (2006, background): “Matching the first two pages of the running example (taken from [22]).”
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).”
ViDE: A Vision-Based Approach for Deep Web Data Extraction (2010, methodology): “RoadRunner, IEPAD, MDR, DEPTA, Omini, and the method in [9] do not generate wrappers, i.e., they identify patterns and perform extraction for each Web page directly without using previously derived extraction rules.”
Web data extraction based on partial tree alignment (2005, methodology): “We do not compare with the systems in [1][12] as they require multiple pages and all of them contain similar data records to find patterns from the pages to extract data items.”
Fully automatic wrapper generation for search engines (2005, methodology): “Several automated or nearly automated IE methods have been proposed recently and the most representative ones are Omini [5], the method in [12], IEPAD [6], MDR [20], RoadRunner [10], EXALG [2], DeLa [26], PickUp [8].”
Automatic web news extraction using tree edit distance (2004, background): “For complex schemas with optional attributes, the algorithm execution can explode and thus it is considered as having exponential cost [7].”
Extracting structured data from Web pages (2003, background): “These pages are typically generated dynamically from an underlying structured source like a relational database.”
Automatic Wrappers for Large Scale Web Extraction (2011, background): “There are several work that model the web publication process [2, 5], and try to infer the grammar that generated the given set of webpages.”
Web Data Extraction System (2009, background): “Some other projects focused on specific issues such as automatic generation of structured data sets from web pages [3] and particular aspects of navigating and interacting with web pages [1].”
Web Data Extraction, Applications and Techniques: A Survey (2012, methodology): “The first example of hybrid system is provided by RoadRunner [28, 27].”
Semi-supervised multi-task learning of structured prediction models for web information extraction (2011, methodology): “As we indicated in section 1, unsupervised learning techniques such as RoadRunner [11], DEPTA [39], and clustering based techniques [3, 25] are useful for extracting records from list pages via repetitive patterns in the HTML tags of one or more pages.”