Overview: Probabilistic query answering is a fundamental set of techniques that underlies several, very recent database applications: exploratory queries in databases, novel IR-style approaches to data integration, querying information extracted from the Web, queries over sensor networks, data acquisition, querying data sources that violate integrity constraints, controlling information disclosure in data exchange, and reasoning about privacy breaches in data mining. This is a surprisingly diverse range of applications, most of which have either emerged recently, or have seen a recent increased interest, and which all share a common fundamental abstraction: that an item being in the answer to a query is no longer a boolean value, but a probabilistic event. It this authors belief that this is a new paradigm in query answering, whose foundations lie in random graphs, and 0/1-laws in finite model theory. The results from these fields, and their relevance to the probabilistic query answering method, are very little known in the database research community, and the theoretical research papers or books that describe them are not very popular in the systems database research community.
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