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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wojtowicz, R.L. |
| Copyright Year | 2009 |
| Description | Author affiliation: Metron, Inc., 1818 Library Street, Suite 600, Reston, VA, U.S.A. (Wojtowicz, R.L.) |
| Abstract | First-order languages express properties of entities and their relationships in rich models of heterogeneous network phenomena. Markov logic is a set of techniques for estimating the probabilities of truth values of such properties. This article generalizes Markov logic in order to allow non-classical sets of truth values. The new methods directly support uncertainties in both data sources and values. The concepts and methods of categorical logic give precise guidelines for selecting sets of truth values based on the form of a network model. Applications to alias detection, cargo shipping, insurgency analysis, and other problems are given. Open problems include complexity analysis and parallelization of algorithms. |
| Starting Page | 938 |
| Ending Page | 947 |
| File Size | 446086 |
| Page Count | 10 |
| File Format | |
| ISBN | 9780982443804 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-07-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | ISIF |
| Subject Keyword | Markov random fields Uncertainty Guidelines Information analysis Libraries Algorithm design and analysis Equations Computer networks Probabilistic logic History Markov network network analysis entity resolution alias detection categorical logic |
| Content Type | Text |
| Resource Type | Article |
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