Remarks on a Fuzzy Approach to Flexible Database Querying, Its Extension and Relation to Data Mining and Summarization - Advanced Database Query Systems - page 134

related elements of Halliday's systemic functional linguistics (SFL). We think that these new directions
of research will play a considerable role to find better tools and techniques for linguistic data summari-
zation that will better take into account an intrinsic imprecision of natural language.
SOME FUTURE RESEARCH DIRECTIONS AND CONCLUSION
We briefly presented the concept of, a rationale for and various approaches to the use of fuzzy logic in
flexible querying. We discussed first some historical developments, then the main issues related to fuzzy
querying. Next, we concentrated on fuzzy queries with linguistic quantifiers, and discussed in more detail
our FQUERY for Access fuzzy querying system. We indicated not only the straightforward power of
that fuzzy querying system but its great potential as a tool to implement linguistic data summaries that
may provide an ultimately human consistent way of data mining and data summarization. We briefly
mentioned also the concept of bipolar queries that may reflect positive and negative preferences of
the user, and may be a breakthrough in fuzzy querying. In the context of fuzzy querying and linguistic
summarization we mentioned a considerable potential of our new recent proposals to explicitly use in
linguistic data summarization some elements of natural language generation (NLG), and some natural
language generation related elements of Halliday's systemic functional linguistics (SFL). We argue that
this may be a promising direction for future research.
There may still be many other promising research directions in this area. First, an interesting future
line of research may be the incorporation of bipolar queries as an element of flexible (fuzzy) querying to
be used in the linguistic summarization context. Second, the inclusion of (fuzzy) ontologies, and maybe
even their combination with protoforms of linguistic summaries, may also be a useful paradigm for
the human-computer interaction (HCI) in the context of fuzzy logic based data mining and knowledge
discovery.
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