The following are the key innovations of the On-To-Knowledge
project w.r.t. the state of the art:
- going beyond key-word based search
- enabling automated information extraction
- supporting information maintenance
Beyond key-word based search
There are numerous approaches on information retrieval, text extraction or agent-based
information access. However, nearly all of them work at the keyword level. It is well
known from information retrieval that keyword-based information access has principal
limitations (concerning precision and recall).
Enable automated information extraction
Another main limitation of these approaches is that they usually deliver raw documents (in
case of Web search engines these documents are URLs). This requires human effort to
extract the required answer (i.e. browse and read the delivered documents until the
information has been found). This burdens the human user and drastically hampers automated
information extraction by agents.
On-To-Knowledge will provide a query answering mechanim for unstructured,
weakly structured and formalized documents. Besides query answering facilities (used by
humans or software agents).
On-To-Knowledge will provide means for creating user-specific views on
information documents, for maintaining information content, and for automatically
generating new documents from existing.
Exploit ontologies
We will use ontologies to mediate information access and will provide an integrated tool
environment that covers acquisition, maintenance, and access to online information based
on ontologies. To our knowledge no such project already exists.
Ontologies can provide more complex definitions (ranging as far as logical
axioms) than is possible with thesauri used in information retrieval. They are our key
asset in automating query answering, maintenance, and automatic document generation. The
integration of ontologies and automated information retrieval (IR) approaches (as support
for ontology generation) are investigated.
Where some approaches from IR exist that deal with text analysis, the
novelty here is the way in which such techniques are integrated in ontology creation,
maintenance, comparison and visualization.
Support for information maintenance
The issue of maintenance, as mentioned in the proposal, clearly goes beyond existing work
in information retrieval. We will provide tool support enabling automatic maintenance and
view definitions on this knowledge. That is, we will provide systematic support for
information providers which is essential in a knowledge management environment.
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