Evaluating Logic-Based Scoring Functions on Uncertain Relational Data - Lehrack, Sebastian; Saretz, Sascha (Journal of Information and Data Management, 2012)
Nowadays, for many retrieval scenarios a strict query evaluation just returning a Boolean truth value is not sufficient anymore. We often rather need the support of a gradual query fulfilment expressed by a score value out of the interval [0,1]. ProQua is a new probabilistic database system which combines such information retrieval concepts with database technologies. In contrast to other state-of-the-art probabilistic database systems ProQua facilitates logic-based similarity conditions within its SQL-like query language by a generic similarity operator. In this work we formalise logic-based scoring functions as the underlying concept of the supported similarity conditions and introduce respective evaluation techniques implemented by relational query plans. Additionally, we report on their experimental verification on a probabilistic TPC-H database.