DIADEM: Self-supervised Extraction of Complex Web Objects.
- Speaker: Dr Giorgio Orsi, Department of Computer Science, Oxford.
- Date: Wednesday, 6 February 2013 from 16:30 to 17:30
- Location: Room 160, Birkbeck Main Building
Abstract: Search engines are the sinews of the web. These sinews have become strained, however: Where the web's function once was a mix of library and yellow pages, it has become the central marketplace for information of almost any kind. We search more and more for objects with specific characteristics, a car with a certain mileage, an affordable apartment close to a good school, or the latest accessory for our phones. Search engines all too often fail to provide reasonable answers, making us sift through dozens of websites with thousands of offers--never to be sure a better offer isn't just around the corner. What search engines are missing is understanding of the objects and their attributes published on websites.
Automatically identifying and extracting these objects is akin toalchemy: transforming unstructured web information into highly structured data with near perfect accuracy. With DIADEM we present a formula for this transformation, but at a price: we need to provide DIADEM with extensive knowledge about the ontology and phenomenology of the domain, i.e., about entities (and relations) and about the representation of these entities in the textual, structural, and visual language of a website of this domain. We will demonstrate that, in contrast to alchemists, DIADEM has developed a viable formula.
Bio: Giorgio Orsi is a post-doctoral research fellow at the Department of Computer Science of the University of Oxford and a junior James Martin fellow at the Institute for the Future of Computing of the Oxford-Martin School. His research is concerned with the investigation of problems in "Big Data" management on the Web. In particular, large-scale web data extraction and ontological reasoning.