Approximate incremental big-data harmonization

Proceedings - 2013 IEEE International Congress on Big Data, BigData 2013

Volumn , Issue , 2013, Pages 118-125

  Agarwal, Puneet ^a   Shroff, Gautam ^a   Malhotra, Pankaj ^a  

^a TATA CONSULTANCY SERVICES   (India)

Author keywords

Approximate Join; BigData; ETL MR; Harmonization; Incremental ETL; Map Reduce

Indexed keywords

APPROXIMATE-JOIN; BIGDATA; ETL-MR; HARMONIZATION; INCREMENTAL ETL; MAP-REDUCE;

MOBILE DEVICES;

EID: 84886025371     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BigData.Congress.2013.24     Document Type: Conference Paper

References (15)

1. G. Shroff, P. Agarwal, and L. Dey, "Enterprise information fusion for real-time business intelligence," in Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on. IEEE, 2011, pp. 1-8.
2. S. Chaudhuri and U. Dayal, "An overview of data warehousing and olap technology," SIGMOD Rec., vol. 26, no. 1, pp. 65-74, Mar. 1997. Oonline. Available: http://doi.acm.org/10.1145/248603.248616
3. R. Kimball and J. Caserta, The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data, 1st ed. Wiley, 9 2004. Oonline. Available: http://amazon.com/o/ASIN/0764567578/
4. M. Stonebraker, D. Abadi, D. DeWitt, S. Madden, E. Paulson, A. Pavlo, and A. Rasin, "mapreduce and parallel dbmss: friends or foes?" Communications of the ACM, vol. 53, no. 1, pp. 64-71, 2010.
5. P. Agarwal, R. Vaithiyanathan, S. Sharma, and G. Shroff, "Catching the long-tail: Extracting local news events from twitter," in Proceedings of Intl. AAAI Conference on Weblogs and Social Media, ser. ICWSM '12, 2012.
6. L. Gravano, P. Ipeirotis, H. Jagadish, N. Koudas, S. Muthukrishnan, D. Srivastava et al., "Approximate string joins in a database (almost) for free," in Proceedings of the international conference on very large data bases, 2001.
7. W. W. Cohen, P. Ravikumar, and S. E. Fienberg, "A comparison of string distance metrics for name-matching tasks," in Proceedings of the IJCAI-2003 Workshop on Information Integration on the Web (IIWeb-03), ser. IIWeb-03, 2003, pp. 73-78.
8. T. Jörg and S. Deßloch, "Towards generating etl processes for incremental loading," in Proceedings of the 2008 international symposium on Database engineering & applications. ACM, 2008, pp. 101-110.
9. P. Vassiliadis and A. Simitsis, "Near real time etl," New Trends in Data Warehousing and Data Analysis, pp. 1-31, 2009.
10. P. Bhatotia, A. Wieder, R. Rodrigues, U. A. Acar, and R. Pasquin, "Incoop: Mapreduce for incremental computations," in Proceedings of the 2nd ACM Symposium on Cloud Computing, ser. SOCC '11. New York, NY, USA: ACM, 2011, pp. 7:1-7:14. Oonline. Available: http://doi.acm.org/10.1145/2038916. 2038923
11. A. Abelló, J. Ferrarons, and O. Romero, "Building cubes with mapreduce," in Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP. ACM, 2011, pp. 17-24.
12. M. Bilenko and R. Mooney, "Adaptive duplicate detection using learnable string similarity measures," in Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2003.
13. W. Cohen, P. Ravikumar, S. Fienberg et al., "A comparison of string distance metrics for name-matching tasks," in Proceedings of the IJCAI-2003 Workshop on Information Integration on the Web-IIWeb-03, 2003.
14. S. Tejada, C. Knoblock, and S. Minton, "Learning object identification rules for information integration," Information Systems, vol. 26, no. 8, 2001.
15. S. Chaudhuri, K. Ganjam, V. Ganti, and R. Motwani, "Robust and efficient fuzzy match for online data cleaning," in International Conference on Management of Data: Proceedings of the 2003 ACM SIGMOD international conference on Management of data, vol. 9, no. 12, 2003.