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Full-Text Articles in Physical Sciences and Mathematics
Answering Why-Not Questions On Reverse Top-K Queries, Yunjun Gao, Qing Liu, Gang Chen, Baihua Zheng, Linlin Zhou
Answering Why-Not Questions On Reverse Top-K Queries, Yunjun Gao, Qing Liu, Gang Chen, Baihua Zheng, Linlin Zhou
Research Collection School Of Computing and Information Systems
Why-not questions, which aim to seek clarifications on the missing tuples for query results, have recently received considerable attention from the database community. In this paper, we systematically explore why-not questions on reverse top-k queries, owing to its importance in multi-criteria decision making. Given an initial reverse top-k query and a missing/why-not weighting vector set Wm that is absent from the query result, why-not questions on reverse top-k queries explain why Wm does not appear in the query result and provide suggestions on how to refine the initial query with minimum penalty to include Wm in the refined query result. …
Probabilistic Inference Based Message-Passing For Resource Constrained Dcops, Supriyo Ghosh, Akshat Kumar, Pradeep Varakantham
Probabilistic Inference Based Message-Passing For Resource Constrained Dcops, Supriyo Ghosh, Akshat Kumar, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Distributed constraint optimization (DCOP) is an important framework for coordinated multiagent decision making. We address a practically useful variant of DCOP, called resource-constrained DCOP (RC-DCOP), which takes into account agents’ consumption of shared limited resources. We present a promising new class of algorithm for RC-DCOPs by translating the underlying co- ordination problem to probabilistic inference. Using inference techniques such as expectation- maximization and convex optimization machinery, we develop a novel convergent message-passing algorithm for RC-DCOPs. Experiments on standard benchmarks show that our approach provides better quality than previous best DCOP algorithms and has much lower failure rate. Comparisons against an …