Preventing Groundings and Handling Evidence in the Lifted Junction Tree Algorithm

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10505)


For inference in probabilistic formalisms with first-order constructs, lifted variable elimination (LVE) is one of the standard approaches for single queries. To handle multiple queries efficiently, the lifted junction tree algorithm (LJT) uses a specific representation of a first-order knowledge base and LVE in its computations. Unfortunately, LJT induces unnecessary groundings in cases where the standard LVE algorithm, GC-FOVE, has a fully lifted run. Additionally, LJT does not handle evidence explicitly. We extend LJT (i) to identify and prevent unnecessary groundings and (ii) to effectively handle evidence in a lifted manner. Given multiple queries, e.g., in machine learning applications, our extension computes answers faster than LJT and GC-FOVE.


Probabilistic logical models Reasoning Lifting 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Information SystemsUniversität zu LübeckLübeckGermany

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