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TF-IDF, BM25, language modelling (LM), and divergence-fromrandomness (DFR) are popular ranking models. Providing logical abstraction for information search is important, but the implementation of ranking algorithms in logical abstraction layers such as probabilistic Datalog leads to many challenges regarding expressiveness and scalability. Though the ranking algorithms have probabilistic roots, the ranking score often is not probabilistic, leading to unsafe programs from a probabilistic pointdoi:10.1145/2524828.2524832 dblp:conf/vldb/RoellekeBM13 fatcat:li56czzxsbcmna4kvbw24khvru