Kizomba: An Unsupervised Heuristic-Based Web Information Extractor

摘要

The Web is an ever growing repository of valuable information. That information lacks semantics since it is buried into web documents that are represented using HTML. Information extractors are software components that help software engineers in the task of extracting structured information from web documents. The problem that we face is how to devise information extractors that can extract information from current web sites with high precision and recall. Our proposal is unsupervised and heuristic-based, which makes it appropriate for the Web.