Journal Articles


  1. Wellington Cabrera, Carlos Ordonez.
    Scalable parallel graph algorithms with matrix vector multiplication evaluated with queries,
    Distributed and Parallel Databases (DAPD),
    [PDF] [Elsevier]
  2. Carlos Ordonez, Wellington Cabrera, Achyuth Gurram.
    Comparing Columnar, Row and Array DBMSs to Process Recursive Queries on Graphs,
    Information Systems (IS),
    [PDF] [Elsevier]
  3. Carlos Garcia-Alvarado, Carlos Ordonez, Il-Yeol Song.
    Evolving data warehousing and OLAP cubes to big data analytics,
    Information Systems (IS),
    editorial article for DOLAP special issue, 2017. [PDF] [Elsevier]
  4. 2016

  5. Sofian Maabout, Carlos Ordonez, Patrick K. Wanko, Nicolas Hanusse.
    Skycube Materialization Using the Topmost Skyline or Functional Dependencies,
    ACM Transactions on Database Systems (TODS),
    accepted, 2016. [PDF] [ACM]
  6. Carlos Ordonez, Yiqun Zhang, Wellington Cabrera.
    The Gamma Matrix to Summarize Dense and Sparse Data Sets for Big Data Analytics,
    IEEE Transactions on Knowledge and Data Engineering (TKDE),
    28(7):1905-1918, 2016. [PDF] [IEEE]
  7. David Sergio Matusevich, Wellington Cabrera, Carlos Ordonez.
    Accelerating a Gibbs Sampler for Variable Selection on Genomics Data with Summarization and Variable Pre-selection combining an Array DBMS and R,
    Machine Learning (ML Journal),
    102(3):483-504, 2016. [PDF] [Springer]
  8. 2015

  9. Nicolas Hanusse, Patrick Kamnang Wanko, Sofian Maabout, Carlos Ordonez.
    Dependances fonctionnelles et requetes skyline multidimensionnelles.
    Ingenierie des Systemes d'Information
    20(5): 9-26 (2015) [Lavoisier, Revue des sciences et technologies de l'information].
  10. Carlos Garcia-Alvarado, Carlos Ordonez.
    Clustering Binary Cube Dimensions to Compute Relaxed GROUP BY Aggregations,
    Information Systems (IS),
    53:41-59, 2015. [Elsevier].
  11. 2014

  12. Carlos Ordonez, Carlos Garcia-Alvarado, Veerabhadran Baladandayuthapani.
    Bayesian Variable Selection in Linear Regression in One Pass for Large Data Sets,
    ACM Transactions on Knowledge Discovery from Data (TKDD),
    9(1):3, 2014, ACM. [PDF] [ACM]
  13. Carlos Ordonez, Naveen Mohanam, Carlos Garcia-Alvarado.
    PCA for Large Data Sets with Parallel Data Summarization,
    Distributed and Parallel Databases (DAPD),
    32(3):377-403, 2014, Springer, special issue on Big Data Analytics. [PDF] [Springer]
  14. Carlos Ordonez, Sofian Maabout, David Sergio Matusevich, Wellington Cabrera.
    Extending ER Models to Capture Database Transformations to Build Data Sets for Data Mining,
    Data & Knowledge Engineering (DKE),
    89: 38-54, 2014, Elsevier. [PDF] [Elsevier]
  15. Amira Kerkad, Ladjel Bellatreche, Pascal Richard, Carlos Ordonez, Dominique Geniet.
    A Query Beehive Algorithm for Data Warehouse Buffer Management and Query Scheduling,
    International Journal of Data Warehousing and Mining (IJDWM),
    10(3):34-58, 2014, IGI Global. [IGI Global]
  16. 2013

  17. Sanvesh Srivastava, Wenyi Wang, Ganiraju Manyam, Carlos Ordonez, Veerabhadran Baladandayuthapani.
    Integrating multi-platform genomic data using hierarchical Bayesian relevance vector machines.
    EURASIP J. Bioinformatics and Systems Biology 2013: 9 (2013), Springer. [Springer]
  18. Carlos Ordonez, Zhibo Chen.
    Discovering Frequent Pattern Pairs,
    Intelligent Data Analysis (IDA),
    17(6):943-963, 2013, IOS Press. [PDF] [IOS Press]
  19. Javier Garcia-Garcia, Carlos Ordonez, Predrag Tosic.
    Efficiently Repairing and Measuring Replica Consistency in Distributed Databases,
    Distributed and Parallel Databases (DAPD),
    2013:31(3): 377-411, Springer. [PDF] [Springer]
  20. 2012

  21. Carlos Ordonez, Zhibo Chen.
    Horizontal aggregations in SQL to prepare data sets for data mining analysis,
    IEEE Transactions on Knowledge and Data Engineering (TKDE),
    24(4):678-691 , 2012, IEEE Computer Society. [PDF] [IEEE]
  22. 2011

  23. Carlos Ordonez.
    Data set preprocessing and transformation in a database system,
    Intelligent Data Analysis (IDA),
    15(4):613-631, 2011, IOS Press. [PDF] [IOS Press]
  24. Carlos Ordonez, Kai Zhao.
    Evaluating association rules and decision trees to predict multiple target attributes,
    Intelligent Data Analysis (IDA),
    15(2):173-192, 2011, IOS Press. [PDF] [IOS Press]
  25. Carlos Ordonez, Mario Navas, Carlos Garcia-Alvarado.
    Parallel multithreaded processing for data set summarization on multicore CPUs,
    Journal of Computing Science and Engineering (JCSE),
    5(2):111-120, 2011, KIISE. [JCSE]
  26. 2010

  27. Carlos Ordonez.
    Optimization of linear recursive queries in SQL,
    IEEE Transactions on Knowledge and Data Engineering (TKDE),
    22(2):264-277, 2010, IEEE Computer Society. [PDF] [IEEE]
  28. Carlos Ordonez, Sasi K. Pitchaimalai.
    Bayesian classifiers programmed in SQL,
    IEEE Transactions on Knowledge and Data Engineering (TKDE),
    22(1):139-144, 2010, IEEE Computer Society. [PDF] [IEEE]
  29. Carlos Ordonez.
    Statistical model computation with UDFs,
    IEEE Transactions on Knowledge and Data Engineering (TKDE),
    22(12):1752-1765, 2010, IEEE Computer Society. [PDF] [IEEE]
  30. Carlos Ordonez, Sasi K. Pitchaimalai.
    Fast UDFs to compute sufficient statistics on large data sets exploiting caching and sampling,
    Data & Knowledge Engineering (DKE),
    69(4):383-398, 2010, Elsevier. [Elsevier]
  31. Javier Garcia-Garcia, Carlos Ordonez.
    Extended aggregations for databases with referential integrity issues,
    Data & Knowledge Engineering (DKE),
    69(1):63-95, 2010, Elsevier. [Elsevier]
  32. Carlos Ordonez, Javier Garcia-Garcia.
    Evaluating join performance on relational database systems,
    Journal of Computing Science and Engineering (JCSE),
    4(4):276-290, 2010, KIISE. [JCSE]
  33. 2009

  34. Carlos Ordonez, Zhibo Chen.
    Evaluating statistical tests on OLAP cubes to compare degree of disease,
    IEEE Transactions on Information Technology in Biomedicine (TITB),
    13(5):756-765, 2009, IEEE Computer Society. [PDF]
  35. Carlos Ordonez.
    Models for association rules based on clustering and correlation,
    Intelligent Data Analysis (IDA),
    13(2):337-358, 2009, IOS Press. [PDF]
  36. 2008

  37. Carlos Ordonez, Javier Garcia-Garcia.
    Referential integrity quality metrics,
    Decision Support Systems (DSS),
    44(2):495-508, 2008, Elsevier. [PDF]
  38. 2006

  39. Carlos Ordonez.
    Integrating K-means clustering with a relational DBMS using SQL,
    IEEE Transactions on Knowledge and Data Engineering (TKDE),
    18(2): 188-201, 2006, IEEE Computer Society. [PDF]
  40. Carlos Ordonez.
    Association rule discovery with the train and test approach for heart disease prediction,
    IEEE Transactions on Information Technology in Biomedicine (TITB),
    10(2):334-343, 2006, IEEE Computer Society. [PDF]
  41. Carlos Ordonez, Norberto Ezquerra, Cesar A. Santana.
    Constraining and summarizing association rules in medical data,
    Knowledge and Information Systems (KAIS),
    9(3):259-283, 2006, Springer. [PDF]
  42. 2005

  43. Carlos Ordonez, Edward Omiecinski.
    Accelerating EM clustering to find high quality solutions,
    Knowledge and Information Systems (KAIS),
    7(2):135-157, 2005, Springer. [PDF]
  44. 2004

  45. Carlos Ordonez, Edward Omiecinski.
    Efficient disk-based K-means clustering for relational databases,
    IEEE Transactions on Knowledge and Data Engineering (TKDE),
    16(8):909-921, 2004, IEEE Computer Society. [PDF]
  46. 2001

  47. Cooke, D., Santana CA, de Braal L, Ordonez, C., Omiecinski E, Elyzabeth Krawczynska, Ezquerra N, Garcia EV.
    Using Data Mining Techniques to Improve the Accuracy of Interpreting Myocardial Perfusion SPECT Studies by an Expert System.
    Journal of Nuclear Medicine,
    42(5), p. 188, 2001.
  48. 2000

  49. Cooke, D., Santana, C.A., Morris, T., de Braal, L., Ordonez, C., Omiecinski, E., Ezquerra N, Ernest V. Garcia.
    Data Mining of Large Myocardial Perfusion SPECT (MPS) Databases: Validation of Expert System Rule Confidences.
    Journal of Nuclear Medicine,
    41(5), p. 187, 2000.
  50. 1999

  51. Cooke CD, Ordonez C, Garcia EV, et al.
    Data mining of large myocardial perfusion SPECT databases to improve diagnostic decision making.
    Journal of Nuclear Medicine,
    40(1):292, 1999.