Web Information Extraction

Living reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7993-3_459-2


Information extraction (IE) is the process of automatically extracting structured pieces of information from unstructured or semi-structured text documents. Classical problems in information extraction include named-entity recognition (identifying mentions of persons, places, organizations, etc.) and relationship extraction (identifying mentions of relationships between such named entities). Web information extraction is the application of IE techniques to process the vast amounts of unstructured content on the Web. Due to the nature of the content on the Web, in addition to named-entity and relationship extraction, there is growing interest in more complex tasks such as extraction of reviews, opinions, and sentiments.

Historical Background

Historically, information extraction was studied by the Natural Language Processing community in the context of identifying organizations, locations, and person names in news articles and...


Information Extraction Extraction Task Unstructured Text Entity Extraction Relationship Extraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Authors and Affiliations

  1. 1.IBM Almaden Research CenterSan JoseUSA

Section editors and affiliations

  • Cong Yu
    • 1
  1. 1.Google ResearchNew YorkUSA