[Source: News from The Herbert Wertheim College of Engineering] In today’s increasingly connected world, the sheer volume of messages we receive on any subject, including speech, images, video and metadata, as well as text imbedded in images and videos, is mind-boggling. When something unexpected happens, government policy analysts need to inform and advise our nation’s
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Interactive Inference for Information Extraction
sean Comment Closed Uncategorized
Introduction In order to keep up with the enormous pace of data being produced on the web, we need automatic methods for converting it into a more structured form for analyzing and querying. For text data this amounts to generating labels which describe the underlying semantic concept and is known as Information Extraction (IE). Examples
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SigmaKB VLDB16 Demo System and TAC KBP Slot Filling Validation 2016
Miguel Rodriguez Comment Closed Uncategorized
Miguel Rodriguez The amount of information available on the web has motivated a number of efforts in creating large-scale knowledge bases (KBs), each with their own methods of automatically extracting relevant information from unstructured text. Despite sharing the same data model, each project is unique, displaying their own strengths and weaknesses related to the size
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Streaming Fact Extraction for Wikipedia Entities at Web-Scale
Morteza Shahriari Nia No Comment Uncategorized
Morteza Shahriari Nia, Christan Grant, Yang Peng Wikipedia.org (WP) is the largest and most popular general reference work on the Internet. Presently, there is considerable time lag between the publication of an event and its citation in WP. The median time lag for a sample of about 60K web pages cited by WP articles in
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