[Paleopsych] PhysOrg: Going from a 'Web of links' to a 'Web of meaning'

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Going from a 'Web of links' to a 'Web of meaning'
    October 08, 2004

    Computer scientist Jeff Heflin and others are building the Semantic
    Web, which they hope will handle more data, resolve contradictions and
    draw inferences from users' queries. The new improved Web will also
    combine pieces of information from multiple sites in order to find
    answers to questions.
    To sports car enthusiasts, football fans and wildlife specialists, the
    word jaguar connotes highly discrete entities.
    Real-estate agents and home buyers argue over titles and plots - as do
    book lovers and moviegoers.
    If the English language, with millions of shades of meaning, can
    baffle the wisest of scholars, how much more does it confound an
    artificially intelligent computer search engine that must find links
    to thousands of Web sites in an eyeblink?
    Especially, says Jeff Heflin, when the Web's frontiers expand hourly
    by leaps and bounds and are governed by no standard rules of
    Heflin, an assistant professor of computer science and engineering at
    Lehigh University, is part of an international effort to build a
    "Semantic Web," a term coined by Tim Berners-Lee, inventor of the
    World Wide Web.
    By developing languages and tools that make it easier for computers to
    understand web pages, says Heflin, computer scientists hope to upgrade
    the Web from a "web of links" to a "web of meaning."
    Heflin recently received a five-year, $500,000 CAREER Award from the
    National Science Foundation to study distributed ontologies that could
    bring the Semantic Web closer to reality.
    Ontology is defined in the dictionary as a theory concerning the kinds
    of entities, specifically abstract entities, that should be admitted
    into a language system.
    Researchers in artificial intelligence have proposed to make
    ontologies explicit, says Heflin. In computer science, an ontology
    encodes knowledge about the world, and can thus determine what is
    implied and find answers without explicit instructions. Ontologies can
    be used by people, and by databases and other applications that need
    to share information about domains, or specific subject or knowledge
    areas, such as cars, medicine or real estate.
    But because the Web is such a vast network, with so many people
    posting and searching for so many different kinds of information,
    achieving one single ontology that applies to everyone would require
    too huge a standardization effort. Instead, the Web overflows with
    overlapping and often contradictory ontologies.
    "No formal theory," Heflin wrote in his proposal to NSF, "has
    considered how ontologies can be integrated and how they may change,
    or the role of trust in integration."
    This, he says, can frustrate those who are conducting a search on the
    "Searching can be difficult if you're a novice," says Heflin, "if
    you're looking for really hard-to-find things, or if you're looking
    for an answer that does not exist on one single page."
    Search engines on the Semantic Web, says Heflin, can better infer from
    a query the site that would be most helpful to the user. They will
    also be able to combine different pieces of information from multiple
    sites in order to find an answer to a question.
    Heflin is an invited expert in the Web Ontology Working Group, which
    was formed by the World Wide Web Consortium (W3C). Directed by
    Berners-Lee, the W3C develops standards for the Web. The working group
    designed the Web Ontology Language, or OWL. Although this name is not
    an accurate acronym, its inventors decided that OWL rolls off the
    tongue more readily, and connotes more wisdom, than does WOL.
    The success of a web search, says Heflin, now depends on the rarity of
    a name or topic or on how popular a web page is. Google, for example,
    takes into account the number of pages that point to a given page when
    ranking the results of a search.
    "We have a language in which to write an ontology," says Heflin, "but
    we don't know how to properly combine [distributed] ontologies, or
    what to do when ontologies are contradictory. We need an environment
    that people can search in that resolves contradictions meaningfully."
    Heflin wants to look at ways of partitioning the Web into useful
    subsets so users can determine which ontology to use when they have a
    query and can find an ontology that will point them to the web page
    that is most suited to the perspective of their search.
    "I want to develop an underlying theory so we can understand and build
    a system that can handle large amounts of data," says Heflin. "That
    system should be able to look at medicine from the point of view of a
    patient, a doctor or a pharmaceutical manufacturer, or to search
    universities from a professor's or a student's point of view."

    Source: Lehigh University

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