메뉴 건너뛰기




Volumn , Issue , 2013, Pages 637-648

Simulation of database-valued Markov chains using SimSQL

Author keywords

Databases; Machine learning; Markov chains

Indexed keywords

BAYESIAN; BUILDING BLOCKES; DATA VALUES; IS-ENABLED; MAP-REDUCE; TIME STEP;

EID: 84880568698     PISSN: 07308078     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2463676.2465283     Document Type: Conference Paper
Times cited : (79)

References (38)
  • 1
    • 84878806200 scopus 로고    scopus 로고
    • 20Newsgroups Dataset. Available at: http://people.csail.mit.edu/jrennie/ 20newsgroups/.
    • 20Newsgroups Dataset
  • 2
    • 79957809015 scopus 로고    scopus 로고
    • HadoopDB: An architectural hybrid of MapReduce and DBMS technologies for analytical workloads
    • A. Abouzeid, K. Bajda-Pawlikowski, D. Abadi, A. Silberschatz, and A. Rasin. HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads. PVLDB, 2(1):922-933, 2009.
    • (2009) PVLDB , vol.2 , Issue.1 , pp. 922-933
    • Abouzeid, A.1    Bajda-Pawlikowski, K.2    Abadi, D.3    Silberschatz, A.4    Rasin, A.5
  • 3
    • 79959919123 scopus 로고    scopus 로고
    • Fast personalized pagerank on MapReduce
    • B. Bahmani, K. Chakrabarti, and D. Xin. Fast Personalized Pagerank on MapReduce. In SIGMOD, 2011.
    • (2011) SIGMOD
    • Bahmani, B.1    Chakrabarti, K.2    Xin, D.3
  • 5
    • 0141607824 scopus 로고    scopus 로고
    • Latent dirichlet allocation
    • D. M. Blei, A. N. Ng, and M. I. Jordan. Latent Dirichlet Allocation. JMLR, 3:993-1022, 2003.
    • (2003) JMLR , vol.3 , pp. 993-1022
    • Blei, D.M.1    Ng, A.N.2    Jordan, M.I.3
  • 6
    • 79956351190 scopus 로고    scopus 로고
    • Haloop: Efficient iterative data processing on large clusters
    • Y. Bu, B. Howe, M. Balazinska, and M. D. Ernst. Haloop: efficient iterative data processing on large clusters. PVLDB, 3(1-2):285-296, 2010.
    • (2010) PVLDB , vol.3 , Issue.1-2 , pp. 285-296
    • Bu, Y.1    Howe, B.2    Balazinska, M.3    Ernst, M.D.4
  • 7
    • 84860560293 scopus 로고    scopus 로고
    • SCOPE: Easy and efficient parallel processing of massive data sets
    • R. Chaiken, B. Jenkins, P. Larson, B. Ramsey, D. Shakib, S. Weaver, and J. Zhou. SCOPE: easy and efficient parallel processing of massive data sets. PVLDB, 1(2):1265-1276, 2008.
    • (2008) PVLDB , vol.1 , Issue.2 , pp. 1265-1276
    • Chaiken, R.1    Jenkins, B.2    Larson, P.3    Ramsey, B.4    Shakib, D.5    Weaver, S.6    Zhou, J.7
  • 13
    • 77954729163 scopus 로고    scopus 로고
    • On probabilistic fixpoint and Markov chain query languages
    • D. Deutch, C. Koch, and T. Milo. On probabilistic fixpoint and markov chain query languages. In PODS, pages 215-226, 2010.
    • (2010) PODS , pp. 215-226
    • Deutch, D.1    Koch, C.2    Milo, T.3
  • 15
    • 0034829234 scopus 로고    scopus 로고
    • Optimizing queries using materialized views: A practical, scalable solution
    • J. Goldstein and P. Larson. Optimizing Queries Using Materialized Views: A practical, scalable solution. In SIGMOD, 2001.
    • (2001) SIGMOD
    • Goldstein, J.1    Larson, P.2
  • 16
    • 34548770803 scopus 로고    scopus 로고
    • Models for incomplete and probabilistic information
    • T. J. Green and V. Tannen. Models for incomplete and probabilistic information. IEEE Data Eng. Bull., 29(1):17-24, 2006.
    • (2006) IEEE Data Eng. Bull. , vol.29 , Issue.1 , pp. 17-24
    • Green, T.J.1    Tannen, V.2
  • 17
    • 0027872183 scopus 로고
    • Optimal histograms for limiting worst-case error propagation in the size of join results
    • Y. E. Ioannidis and S. Christodoulakis. Optimal histograms for limiting worst-case error propagation in the size of join results. TODS, 18(4):709-748, 1993.
    • (1993) TODS , vol.18 , Issue.4 , pp. 709-748
    • Ioannidis, Y.E.1    Christodoulakis, S.2
  • 18
    • 80052344771 scopus 로고    scopus 로고
    • The Monte Carlo database system: Stochastic analysis close to the data
    • R. Jampani, F. Xu, M. Wu, L. L. Perez, C. Jermaine, and P. J. Haas. The Monte Carlo Database System: Stochastic analysis close to the data. TODS, 36(3):1-41, 2011.
    • (2011) TODS , vol.36 , Issue.3 , pp. 1-41
    • Jampani, R.1    Xu, F.2    Wu, M.3    Perez, L.L.4    Jermaine, C.5    Haas, P.J.6
  • 19
    • 77951152705 scopus 로고    scopus 로고
    • Pegasus: A peta-scale graph mining system - Implementation and observations
    • U. Kang, C. E. Tsourakakis, and C. Faloutsos. Pegasus: A peta-scale graph mining system - implementation and observations. In ICDM, 2009.
    • (2009) ICDM
    • Kang, U.1    Tsourakakis, C.E.2    Faloutsos, C.3
  • 20
    • 79959942894 scopus 로고    scopus 로고
    • Jigsaw: Efficient optimization over uncertain enterprise data
    • O. Kennedy and S. Nath. Jigsaw: Efficient optimization over uncertain enterprise data. In SIGMOD, 2011.
    • (2011) SIGMOD
    • Kennedy, O.1    Nath, S.2
  • 21
    • 63749084566 scopus 로고    scopus 로고
    • On query algebras for probabilistic databases
    • C. Koch. On query algebras for probabilistic databases. SIGMOD Record, 37(4):78-85, 2008.
    • (2008) SIGMOD Record , vol.37 , Issue.4 , pp. 78-85
    • Koch, C.1
  • 23
    • 79955694310 scopus 로고    scopus 로고
    • Plda+: Parallel latent dirichlet allocation with data placement and pipeline processing
    • Z. Liu, Y. Zhang, E. Y. Chang, and M. Sun. Plda+: Parallel Latent Dirichlet Allocation with Data Placement and Pipeline Processing. ACM TIST, 2(3):26:1-26:18, 2011.
    • (2011) ACM TIST , vol.2 , Issue.3 , pp. 261-2618
    • Liu, Z.1    Zhang, Y.2    Chang, E.Y.3    Sun, M.4
  • 25
    • 84880564635 scopus 로고    scopus 로고
    • A. Mahout. Available at: http://mahout.apache.org/.
    • Mahout, A.1
  • 26
    • 84863448825 scopus 로고    scopus 로고
    • Efficiently compiling efficient query plans for modern hardware
    • T. Neumann. Efficiently compiling efficient query plans for modern hardware. PVLDB, 4(9):539-550, 2011.
    • (2011) PVLDB , vol.4 , Issue.9 , pp. 539-550
    • Neumann, T.1
  • 27
    • 77955032649 scopus 로고    scopus 로고
    • Planet: Massively parallel learning of tree ensembles with mapreduce
    • B. Panda, J. S. Herbach, S. Basu, and R. J. Bayardo. Planet: Massively parallel learning of tree ensembles with mapreduce. PVLDB, 2(2):1426-1437, 2009.
    • (2009) PVLDB , vol.2 , Issue.2 , pp. 1426-1437
    • Panda, B.1    Herbach, J.S.2    Basu, S.3    Bayardo, R.J.4
  • 28
    • 67149126890 scopus 로고    scopus 로고
    • DisCo: Distributed co-clustering with map-reduce: A case study towards petabyte-scale end-to-end mining
    • S. Papadimitriou and J. Sun. DisCo: Distributed co-clustering with map-reduce: A case study towards petabyte-scale end-to-end mining. In ICDM, 2008.
    • (2008) ICDM
    • Papadimitriou, S.1    Sun, J.2
  • 33
    • 80052119994 scopus 로고    scopus 로고
    • An architecture for parallel topic models
    • A. J. Smola and S. Narayanamurthy. An Architecture for Parallel Topic models. PVLDB, 3(1):703-710, 2010.
    • (2010) PVLDB , vol.3 , Issue.1 , pp. 703-710
    • Smola, A.J.1    Narayanamurthy, S.2
  • 36
    • 79961186434 scopus 로고    scopus 로고
    • Scalable probabilistic databases with factor graphs and MCMC
    • M. Wick, A. McCallum, and G. Miklau. Scalable probabilistic databases with factor graphs and MCMC. In VLDB, 2010.
    • (2010) VLDB
    • Wick, M.1    McCallum, A.2    Miklau, G.3
  • 37
    • 70350591395 scopus 로고    scopus 로고
    • Dryadlinq: A system for general-purpose distributed data-parallel computing using a high-level language
    • Y. Yu, M. Isard, D. Fetterly, M. Budiu, U. Erlingsson, P. K. Gunda, and J. Currey. Dryadlinq: A system for general-purpose distributed data-parallel computing using a high-level language. In OSDI, 2008.
    • (2008) OSDI
    • Yu, Y.1    Isard, M.2    Fetterly, D.3    Budiu, M.4    Erlingsson, U.5    Gunda, P.K.6    Currey, J.7


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.