the knowledge discovery quest
TRANSCRIPT
Knowledge Discovery Quest
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After the immense loss of knowledge that humanity
underwent when the Ancient Library of Alexandria was
destroyed by fire, the next biggest loss
is the one that happens due to inefficient content management and
Information retrieval.
All the data sources around us remain locked and useless
without elaborate tools to navigate and explore the
relationships between data.
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The potential of data forknowledge discovery is only as big as the capacity to intelligently search through these data.
And there’s no blunter reminder for this fact than the message: “Sorry, no content matched your criteria”
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A lot of content will be very much likely not “match the search criteria” of someone looking for, if there isn’t a more sophisticated way to navigate the vast lands of interconnected resources, different than the “dumb” matching of keywords.
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Fortunately, there is a way to intelligently search content and it is called semantic search.
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While traditional information retrieval systems rely hard on keywords and links,
semantic search goes deeper and beyond
the mere textual representation of the content. It magnifies a lot more relations
otherwise invisible by traditional search.
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If semantic search had a separate icon from the one traditional search has (the ubiquitous magnifying glass),it would probably have been a microscope.
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Magnifying large amounts of systems and the connections between them, semantic search sharpens our ability to join the dots and enhances the way we track relationships, look for clues, comparecorrelations.
As any contentis a lot more
than the mere sumof the exact words
and phrases it contains or is
described by. It is more of
a network ofconnected
entities.
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Semantic search analyzes the relational aspects of these entities as to address complex queries and thus foster knowledge discovery.
Showing the dependencies between 10 classes
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Leveraging Semantic Web technologies,
specifically, data represented in RDF
and organized in formal collections of related entities
(ontologies), semantic search
takes information retrieval to the
next level.
The way we access information transcends from a list of results, solely based on keyword matching to a set of connections, pertinent to the intent and the context of our specific query.
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With semantic search we are able to thoroughly look up all kinds of relationships. Instead of more
links, which are only a single kind of relation,a semantic approach to information
retrieval leads to a networkedview of relations, facts,
information,we mightnot know
even existed.
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With smarter algorithms that understand the semantics, that is the meaning of our searches,
and pick the most relevant result quickly and accurately, our potential to turn information
into knowledge is maximized.
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M a k i n g s e n s e o f t e x t a n d d a t a
We are able to blend our creative forces with the analytical power of machines and use semantic search
as yet another smart tool to use throughout our knowledge discovery quest.
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