Neighborhood systems and relational databases
Tzu‐Yu Lin · 1988
Queries in database can be classified roughly into two types: specific targets and fuzzy targets. Many queries are in effect fuzzy targets, however, because of lacking the supports, the user has been emulating them with specific targets by retiring a query repeatedly with minor changes. In this paper, we augment the relational database, with neighborhood systems, so the database can answer a fuzzy query. There have been many works to combine relational databases and fuzzy theory. Bucklles and Petry replaced attributes values by sets of values. Zemankova-Leech, Kandel, and Zviell used fuzzy logic. The formalism of present work is quite general, it allows numerical or nonnumerical measurements of fuzziness in relational databases. The fuzzy theory present here is quite different from the usual theory. Our basic assumption here is that: the data are not fuzzy, the queries are.