The work on probabilistic DB technology led to results that feed into DB+IR technology. The talk will browse 2 decades of probabilistic DB and reasoning including Cavallo/Pitarelli:VLDB:87 (theory of probabilistic DB), Barbara/etal:90/92, Fagin/Halpern:JACM:94 (reasoning about knowledge), Fuhr/Roelleke:TOIS:97, Chaudhuri...Weikum:04/06 (probabilistic ranking of tuples), Dalvi/Suciu:04/05 (efficient processing of safe expressions), and our recent contribution, the relational Bayes.
The relational Bayes is a new probabilistic relational operator. Traditional database technology is based on five operators. Probabilistic extensions based on those five only captured probability aggregation, but not estimation. The Bayes operator embeds probability estimation conceptually into the probabilistic relational paradigm.
Through the relational Bayes, IR models such as tf-idf, binary-independent retrieval, and language modelling can be expressed in probabilistic logical models. This will be illustrated in a system demo. The outlook addresses optimisation, design and verification of probabilistic logical programs, and RSS retrieval.
Last modified: Monday, 10-Mar-2008 14:50:12 NZDT
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