Campus Event Calendar
Event Entry
What and Who
Towards a Statistically Semantic Web
Prof. Dr.-Ing. Gerhard Weikum
Ringvorlesung
AG 1, AG 2, AG 3, AG 4, AG 5
AG Audience
Note: We use this to send email in the morning.
Date, Time and Location
Thursday, 14 July 2005
13:00
-- Not specified --
45
016
Saarbrücken
Abstract
The envisioned Semantic Web aims to provide richly annotated
and explicitly structured Web pages in XML, RDF, or
description logics, based upon underlying ontologies and thesauri.
Ideally, this should enable a wealth of query processing
and semantic reasoning capabilities using XQuery and logical inference
engines.
However, I believe that the diversity and uncertainty of
terminologies and schema-like annotations will make precise
querying on a Web scale extremely elusive if not hopeless, and the
same argument holds for large-scale dynamic federations of
Deep Web sources.
Therefore, ontology-based reasoning and querying needs to be
enhanced by statistical means, leading to relevance-ranked lists as
query results.
This talk presents steps towards such a "statistically semantic" Web
and outlines technical challenges. I discuss how statistically
quantified ontological relations can be exploited in XML retrieval,
how statistics can help in making Web-scale search efficient, and
how statistical information extracted from users' query logs and click
streams
can be leveraged for better search result ranking.
I believe these are decisive issues for improving the quality of
next-generation
search engines for intranets, digital libraries, and the Web,
and they are crucial also for peer-to-peer collaborative Web search.
and explicitly structured Web pages in XML, RDF, or
description logics, based upon underlying ontologies and thesauri.
Ideally, this should enable a wealth of query processing
and semantic reasoning capabilities using XQuery and logical inference
engines.
However, I believe that the diversity and uncertainty of
terminologies and schema-like annotations will make precise
querying on a Web scale extremely elusive if not hopeless, and the
same argument holds for large-scale dynamic federations of
Deep Web sources.
Therefore, ontology-based reasoning and querying needs to be
enhanced by statistical means, leading to relevance-ranked lists as
query results.
This talk presents steps towards such a "statistically semantic" Web
and outlines technical challenges. I discuss how statistically
quantified ontological relations can be exploited in XML retrieval,
how statistics can help in making Web-scale search efficient, and
how statistical information extracted from users' query logs and click
streams
can be leveraged for better search result ranking.
I believe these are decisive issues for improving the quality of
next-generation
search engines for intranets, digital libraries, and the Web,
and they are crucial also for peer-to-peer collaborative Web search.
Contact
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Bahareh Kadkhodazadeh, 04/07/2005 16:02
Bahareh Kadkhodazadeh, 04/07/2005 15:58 -- Created document.
Bahareh Kadkhodazadeh, 04/07/2005 15:58 -- Created document.