University of Bremen – Center for Computing Technologies –
Abstract:
The number of web sites has increased drastically over the past few years.
Currently, billions of web pages supplying information to users. Modern
technology (e.g. multiagent systems) seem to be able to support the user
with his requests, browsing through the web automatically, returning answers.
However, the vast amount of web pages are unstructured or weakly structured,
which makes it impossible for machines to understand the semantics of the
content. The idea of the Semantic Web helps at this point: information
sources should be annotated with metadata following some kind of formalization.
Thus,
machines are able to “understand” the meaning of the information sources and
can deliver more accurate answers.
The Bremen Semantic Translator for Enhanced Retrieval (BUSTER) follows the
idea of the Semantic Web annotating information sources with metadata
following
some kind of formalization. It is an ontology-based prototype that helps
applications or users to (a) find the needed information and (b) integrate
and/or translate this information for further processes. So far, a
logic-based approach for terminological reasoning and a graph-based approach for
reasoning about place names have been developed.
Another important part of search is time-dependent: people are looking for
hotels in areas at a certain time (e.g. during summer vacation) but do not
want to specify time according to the user-unfriendly W3C standard. Therefore, we
developed a new time representation and a new reasoning machine based on
Allen’s time intervals and Freksa’s semi-intervals. This leads to another
new type of query, namely concept@location in time.
I will give an overview about the overall BUSTER approach and will then
focus on the temporal part in detail.
