Database Reference
In-Depth Information
INTRODUCTION
Databases are a crucial element of all kinds of information systems that are in turn the “backbone” of
virtually all kinds of nontrivial human activities. The growing power, and falling prices of computer
hardware and software, including those that have a direct impact on database technology, have implied
an avalanche growth of data volume stored all over the world. That huge volume makes an effective and
efficient use of information resources in databases difficult. On the other hand, the use of databases is
not longer an area where database professionals are only active and, in fact, nowadays most of the users
are novice. This implies a need for a proper human-computer (database) interaction which would adapt
to the specifics of the human being, mainly - in our context - to the fact that for the human user the only
fully natural means of articulation and communication is natural language with its inherent imprecision.
The aspects mentioned above, the importance of which has been growing over the lasts decades or
years, have triggered many research efforts, notably related to what is generally termed
flexible
query-
ing, and some human consistent approaches to data mining and knowledge discovery, including the use
of natural langue, for instance in linguistic data summarization.
Basically, the construction of a database query consists in spelling out conditions that should be met
by the data sought. Very often, the meaning of these conditions is deeply rooted in natural language,
i.e., their original formulation is available in the form of natural language utterances. It is then, often
with difficulty, translated into mathematical formulas requested by the traditional query languages. For
example, looking for a suitable house in a real estate agency database one may prefer a
cheap
one. In
order to pose a query, the concept of “cheap” has to be expressed by an interval of prices. The bounds
of such an interval will usually be rather difficult to assess. Thus, a tool to somehow define the notion of
“being cheap” may essentially ease the construction of a query. The same definition may be then used,
in other queries referring to this concept, also in the context of other words, as, e.g.,
very
. The words of
this kind, interpreted as so-called
modifiers
, modify the meaning of the original concept in a way that
may be assumed context-independent and expressed by a strict mathematical formula.
It seems obvious that a condition referring to such terms as “cheap”, “large” etc. should be consid-
ered, in general, to be satisfied to
a degree
rather than as satisfied or not satisfied - as it is assumed
in the classical approach to database querying. Thus, the notion of the
matching degree
is one of the
characteristic features of flexible fuzzy queries.
Moreover, usually, a query comprises more than just one condition. In such a case, the user may
require various combinations of conditions to be met. Classically, directly only the satisfaction of
all
conditions may be required or the satisfaction of
any one
condition may be required. However, these
are in fact only some extreme cases of conceivable
aggregation
requirements. For instance, a user may
be completely satisfied with the data satisfying
most
of the his or her conditions.
The study of modeling of such natural language terms as “cheap”, “very” or “most” for the purposes
of database querying is the most important part of the agenda of the flexible fuzzy querying research.
In this paper we will present a focused overview of the main research results on the development of
flexible querying techniques that are based on fuzzy set theory (Zadeh, 1965). The scope of the chapter
is further limited to an overview of those techniques that aim to enhance database querying by introduc-
ing various forms of user specified fuzzy preferences (Bosc, Kraft & Petry, 2005). We will not consider
other techniques that are relevant in this area, exemplified by self-correcting, navigational, cooperative,
etc. querying systems.
