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Zbigniew W. Raś
Knowledge-Discovery Based
Flexible Query Answering Systems
963
Abstract
Query answering systems are strictly dependent on models used to store the
data. If these models are table-based and objects stored in them are
described by weighted values of attributes, then query languages linked with
these table-based models should be based on alphabets containing
non-weighted values of these attributes and some logical connectives
including: or, and, not. In this paper, we also give two examples of models
used to store the data which are not table-based. The first one, introduced
by Ras in [1] and called po-system, is hierarchical one with attributes and
their values hidden. Ras shows in [1] how to reconstruct these hidden
attributes and their values. The second one, called information tree, was
introduced by Chen and Ras [16,17]. Since information trees are constructed
from table based systems, attributes and their values are known a priori and
they can be naturally used when constructing query languages for information
trees. One way to make query answering systems flexible is to assume a
hierarchical structure of their attributes [9,12,13,14,15]. The resulting
query answering systems based on hierarchical attributes are often called
cooperative [12,13,14,15]. One way to develop knowledge based query
answering systems is to discover rules either locally or at remote sites (if
system is distributed) and use these rules in a query answering process.
There are two classical situations when it can be done. The first one is
when attributes are incomplete so we may need rules to approximate the null
values and the same way change the answer to a query. The second one is when
users want to ask queries based on some attributes which are not listed in a
local domain. Since these attributes are locally not available, we can only
search for their definitions at remote sites and use them to approximate
given queries [7,8,9,10]. This paper gives mainly an overview of the results
presented in [1,5,6,7,8,9,10] with a goal to present new foundations for
knowledge-discovery based query answering systems in a distributed scenario
.
Keywords : Information Systems, Flexible Query Answering, Cooperative and
Collaborative Systems, Knowledge Discovery, Ontologies, Rough Sets.
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