MystiQ

Description

This is the research page for MystiQ. The MystiQ prototype downloadable from here .

The MystiQ prototpye was redeveloped during 2006 using TGIF funds. If you'd like to obtain a copy, please send email to suciu@cs.washington.edu

MystiQ is a system that uses a probabilistic data model to find answers in large numbers of data sources exhibiting various kinds of imprecisions. Examples of imprecisions: the same data item may have different representation in different sources; the schema alignments needed by a query system are imperfect and noisy; different sources may contain contradictory information, and, in particular, their combined data may violate some global integrity constraints; fuzzy matches between objects from different sources may return false positives or negatives. Even in such environment, users sometimes want to ask complex, structurally rich queries, using query constructs typically found in SQL queries: joins, subqueries, existential/universal quantifiers, aggregate and group-by queries: for example scientists may use such queries to query multiple scientific data sources, or a law enforcement agency may use it in order to find rare associations from multiple data sources. If standard query semantics were applied to such queries, all but the most trivial queries will return an empty answer. The goal of MystiQ is to develop efficient query processing techniques for fining answers in large probabilistic databases.

A tutorial on probabilistic databases is here ; accompanying bibliography is here ;

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