Functional Dependencies Over Possibilistic Databases: An Interpretation Based on the Possible Worlds Semantics.
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[1] R. Nichol,et al. On Departures from a Power Law in the Galaxy Correlation Function , 2003, astro-ph/0301280.
[2] Weak-lensing halo numbers and dark-matter profiles , 2001, astro-ph/0103465.
[3] T. S. Jayram,et al. Efficient allocation algorithms for OLAP over imprecise data , 2006, VLDB.
[4] Christopher Ré,et al. Efficient Evaluation of , 2007, DBPL.
[5] Neta A. Bahcall,et al. The Dependence on Environment of the Color-Magnitude Relation of Galaxies , 2003, astro-ph/0307336.
[6] Jingren Zhou,et al. SCOPE: easy and efficient parallel processing of massive data sets , 2008, Proc. VLDB Endow..
[7] David J. DeWitt,et al. Parallel algorithms for the execution of relational database operations , 1983, TODS.
[8] M. Giavalisco,et al. Photometric redshifts of galaxies in COSMOS , 2006 .
[9] M. Postman,et al. The morphology-density relation - The group connection , 1984 .
[10] Dan Olteanu,et al. Fast and Simple Relational Processing of Uncertain Data , 2007, 2008 IEEE 24th International Conference on Data Engineering.
[11] Ravi Kumar,et al. Pig latin: a not-so-foreign language for data processing , 2008, SIGMOD Conference.
[12] T. S. Jayram,et al. Efficient aggregation algorithms for probabilistic data , 2007, SODA '07.
[13] Padova,et al. On the environmental dependence of halo formation , 2004 .
[14] Yuri Gurevich,et al. The complexity of query reliability , 1998, PODS.
[15] Raghav Kaushik,et al. Efficient exact set-similarity joins , 2006, VLDB.
[16] R. Ellis,et al. The 2dF Galaxy Redshift Survey: the dependence of galaxy clustering on luminosity and spectral type , 2001, astro-ph/0112043.
[17] A. Mazure,et al. The VIMOS-VLT deep survey - galaxy luminosity function per morphological type up to z = 1.2 , 2006 .
[18] David J. DeWitt,et al. Parallel database systems: the future of high performance database systems , 1992, CACM.
[19] Prithviraj Sen,et al. Representing and Querying Correlated Tuples in Probabilistic Databases , 2007, 2007 IEEE 23rd International Conference on Data Engineering.
[20] Jennifer Widom,et al. Databases with uncertainty and lineage , 2008, The VLDB Journal.
[21] Rahul Gupta,et al. Creating probabilistic databases from information extraction models , 2006, VLDB.
[22] Dan Suciu,et al. Management of probabilistic data: foundations and challenges , 2007, PODS '07.
[23] Andrew J. Connolly,et al. Marked correlations in galaxy formation models , 2005 .
[24] Andrew W. Moore,et al. A multiple tree algorithm for the efficient association of asteroid observations , 2005, KDD '05.
[25] Christopher Ré,et al. Materialized Views in Probabilistic Databases for Information Exchange and Query Optimization , 2007, VLDB.
[26] A. Hamilton,et al. Evidence for biasing in the CfA survey , 1988 .
[27] Rob Pike,et al. Interpreting the data: Parallel analysis with Sawzall , 2005, Sci. Program..
[28] Peter J. Haas,et al. MCDB: a monte carlo approach to managing uncertain data , 2008, SIGMOD Conference.
[29] Dan Suciu,et al. Efficient query evaluation on probabilistic databases , 2004, The VLDB Journal.
[30] Christopher Ré,et al. Event queries on correlated probabilistic streams , 2008, SIGMOD Conference.
[31] Christopher Ré,et al. Efficient Top-k Query Evaluation on Probabilistic Data , 2007, 2007 IEEE 23rd International Conference on Data Engineering.
[32] Wayne Hu,et al. Effects of Photometric Redshift Uncertainties on Weak-Lensing Tomography , 2005 .
[33] Sanjay Ghemawat,et al. MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.
[34] Yuan Yu,et al. Dryad: distributed data-parallel programs from sequential building blocks , 2007, EuroSys '07.
[35] Dan Suciu,et al. The Boundary Between Privacy and Utility in Data Publishing , 2007, VLDB.