Matches in SemOpenAlex for { <https://semopenalex.org/work/W2029237138> ?p ?o ?g. }
- W2029237138 endingPage "446" @default.
- W2029237138 startingPage "407" @default.
- W2029237138 abstract "Recent research has highlighted the practical benefits of subjective interestingness measures, which quantify the novelty or unexpectedness of a pattern when contrasted with any prior information of the data miner (Silberschatz and Tuzhilin, Proceedings of the 1st ACM SIGKDD international conference on Knowledge discovery and data mining (KDD95), 1995; Geng and Hamilton, ACM Comput Surv 38(3):9, 2006). A key challenge here is the formalization of this prior information in a way that lends itself to the definition of a subjective interestingness measure that is both meaningful and practical. In this paper, we outline a general strategy of how this could be achieved, before working out the details for a use case that is important in its own right. Our general strategy is based on considering prior information as constraints on a probabilistic model representing the uncertainty about the data. More specifically, we represent the prior information by the maximum entropy (MaxEnt) distribution subject to these constraints. We briefly outline various measures that could subsequently be used to contrast patterns with this MaxEnt model, thus quantifying their subjective interestingness. We demonstrate this strategy for rectangular databases with knowledge of the row and column sums. This situation has been considered before using computation intensive approaches based on swap randomizations, allowing for the computation of empirical p-values as interestingness measures (Gionis et al., ACM Trans Knowl Discov Data 1(3):14, 2007). We show how the MaxEnt model can be computed remarkably efficiently in this situation, and how it can be used for the same purpose as swap randomizations but computationally more efficiently. More importantly, being an explicitly represented distribution, the MaxEnt model can additionally be used to define analytically computable interestingness measures, as we demonstrate for tiles (Geerts et al., Proceedings of the 7th international conference on Discovery science (DS04), 2004) in binary databases." @default.
- W2029237138 created "2016-06-24" @default.
- W2029237138 creator A5076045275 @default.
- W2029237138 date "2010-12-11" @default.
- W2029237138 modified "2023-09-30" @default.
- W2029237138 title "Maximum entropy models and subjective interestingness: an application to tiles in binary databases" @default.
- W2029237138 cites W1537336823 @default.
- W2029237138 cites W1563743971 @default.
- W2029237138 cites W1584478757 @default.
- W2029237138 cites W1602023060 @default.
- W2029237138 cites W178392936 @default.
- W2029237138 cites W184371133 @default.
- W2029237138 cites W1898824936 @default.
- W2029237138 cites W1973996621 @default.
- W2029237138 cites W1978036582 @default.
- W2029237138 cites W1979943645 @default.
- W2029237138 cites W2008620264 @default.
- W2029237138 cites W2018490621 @default.
- W2029237138 cites W2026797055 @default.
- W2029237138 cites W2032558547 @default.
- W2029237138 cites W2042970816 @default.
- W2029237138 cites W2062749891 @default.
- W2029237138 cites W2080379754 @default.
- W2029237138 cites W2099111195 @default.
- W2029237138 cites W2102297485 @default.
- W2029237138 cites W2103187160 @default.
- W2029237138 cites W2103380375 @default.
- W2029237138 cites W2148606196 @default.
- W2029237138 cites W2153624566 @default.
- W2029237138 cites W2160268549 @default.
- W2029237138 cites W2160342152 @default.
- W2029237138 cites W37234579 @default.
- W2029237138 cites W4250589301 @default.
- W2029237138 cites W4252115301 @default.
- W2029237138 cites W4288080327 @default.
- W2029237138 doi "https://doi.org/10.1007/s10618-010-0209-3" @default.
- W2029237138 hasPublicationYear "2010" @default.
- W2029237138 type Work @default.
- W2029237138 sameAs 2029237138 @default.
- W2029237138 citedByCount "124" @default.
- W2029237138 countsByYear W20292371382012 @default.
- W2029237138 countsByYear W20292371382013 @default.
- W2029237138 countsByYear W20292371382014 @default.
- W2029237138 countsByYear W20292371382015 @default.
- W2029237138 countsByYear W20292371382016 @default.
- W2029237138 countsByYear W20292371382017 @default.
- W2029237138 countsByYear W20292371382018 @default.
- W2029237138 countsByYear W20292371382019 @default.
- W2029237138 countsByYear W20292371382020 @default.
- W2029237138 countsByYear W20292371382021 @default.
- W2029237138 countsByYear W20292371382022 @default.
- W2029237138 countsByYear W20292371382023 @default.
- W2029237138 crossrefType "journal-article" @default.
- W2029237138 hasAuthorship W2029237138A5076045275 @default.
- W2029237138 hasBestOaLocation W20292371382 @default.
- W2029237138 hasConcept C106301342 @default.
- W2029237138 hasConcept C11413529 @default.
- W2029237138 hasConcept C121332964 @default.
- W2029237138 hasConcept C124101348 @default.
- W2029237138 hasConcept C138885662 @default.
- W2029237138 hasConcept C154945302 @default.
- W2029237138 hasConcept C27206212 @default.
- W2029237138 hasConcept C2778738651 @default.
- W2029237138 hasConcept C41008148 @default.
- W2029237138 hasConcept C45374587 @default.
- W2029237138 hasConcept C49937458 @default.
- W2029237138 hasConcept C62520636 @default.
- W2029237138 hasConcept C9679016 @default.
- W2029237138 hasConceptScore W2029237138C106301342 @default.
- W2029237138 hasConceptScore W2029237138C11413529 @default.
- W2029237138 hasConceptScore W2029237138C121332964 @default.
- W2029237138 hasConceptScore W2029237138C124101348 @default.
- W2029237138 hasConceptScore W2029237138C138885662 @default.
- W2029237138 hasConceptScore W2029237138C154945302 @default.
- W2029237138 hasConceptScore W2029237138C27206212 @default.
- W2029237138 hasConceptScore W2029237138C2778738651 @default.
- W2029237138 hasConceptScore W2029237138C41008148 @default.
- W2029237138 hasConceptScore W2029237138C45374587 @default.
- W2029237138 hasConceptScore W2029237138C49937458 @default.
- W2029237138 hasConceptScore W2029237138C62520636 @default.
- W2029237138 hasConceptScore W2029237138C9679016 @default.
- W2029237138 hasIssue "3" @default.
- W2029237138 hasLocation W20292371381 @default.
- W2029237138 hasLocation W20292371382 @default.
- W2029237138 hasOpenAccess W2029237138 @default.
- W2029237138 hasPrimaryLocation W20292371381 @default.
- W2029237138 hasRelatedWork W1572523360 @default.
- W2029237138 hasRelatedWork W1969823381 @default.
- W2029237138 hasRelatedWork W203615609 @default.
- W2029237138 hasRelatedWork W2350005755 @default.
- W2029237138 hasRelatedWork W2751522903 @default.
- W2029237138 hasRelatedWork W3003088367 @default.
- W2029237138 hasRelatedWork W3038107571 @default.
- W2029237138 hasRelatedWork W4230289150 @default.
- W2029237138 hasRelatedWork W4290792893 @default.
- W2029237138 hasRelatedWork W94633634 @default.
- W2029237138 hasVolume "23" @default.
- W2029237138 isParatext "false" @default.