A dynamic attribute-based data filtering and recovery scheme for web information processing

Knowledge and Information Systems

Volumn 18, Issue 3, 2009, Pages 263-291

  Ahuja, Amit ^a   Ng, Yiu Kai ^a  

^a 3361 TMCB   (United States)

Author keywords

Adaptive scheme; Data filtering; Data recovery; Dynamic approach; Informative attribute

Indexed keywords

DATA HANDLING; RECOVERY; WEBSITES;

ADAPTIVE SCHEME; DATA FILTERING; DATA RECOVERY; DYNAMIC APPROACHES; INFORMATIVE ATTRIBUTES;

INFORMATION FILTERING;

EID: 62149124690     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-008-0140-8     Document Type: Article

References (25)

1. Ahuja A (2006) A dynamic attribute-based load shedding and data recovery scheme for data stream management systems. Master Thesis, Computer Science Department, Brigham Young University
2. Almuallim H, Dietterich T (1991) Learning with many irrelevant features. In: Proceedings of the ninth national conference on artificial intelligence. AAAI Press, Anaheim, pp 547-552
3. Ananthakrishna R, Chaudhuri S, Ganti V (2002) Eliminating fuzzy duplicates in data warehouses. In: Proceedings of the 28th international conference on very large databases, Hong Kong, 20-23 August 2002, pp 586-597
4. Babcock B, Datar M, Motwani R (2004) Load shedding for aggregation queries over data streams, In: Proceedings of the 20th international conference on data engineering, Bostern, 30 March-2 April 2004, pp 350-361
5. Bai Y, Wang F, Liu P (2006) Efficiently filtering RFID data streams. In: Proceedings of the first international VLDB workshop on clean databases (CleanDB'06), Seoul, Septermber 2006
6. Bhattacharya I, Getoor L (2004) Iterative record linkage for cleaning and integration. In: Proceedings of the 9th ACM SIGMOD workshop on research issues in data mining and knowledge discovery, Paris, 13 June 2004, pp 11-18
7. Bilenko M, Mooney R (2003) Adaptive duplicate detection using learnable string similarity measures. In: Proceedings of the international conference on knowledge discover and data mining (KDD), Washigton, DC, August 2003, pp 39-48
8. Bouras C, Konidaris A (2005) Estimating and eliminating redundant data transfers over the web: A fragment based approach. Int J Commun Syst 18(2):119-142
9. Chandola V, Kumar V (2007) Summarization - compressing data into an informative representation. Knowl Inf Syst 12(3):355-378
10. Chaudhuri S, Ganti V, Motwani R (2005) Robust Identification of Fuzzy Duplicates. In: Proceedings of the 21st international conference on data engineering (ICDE'05), Tokyo, 5-8 April 2005, pp 865-876
11. Floratos A, Rigoutsos I, Parida L, Gao Y (2001) DELPHI: A pattern-based method for detecting sequence similarity. IBM J Res Deve 45(3/4):455-474
12. Garcia I, Ng Y-K (2006) Eliminating redundant and less-informative RSS news articles based on word similarity and a fuzzy equivalence relation. In: Proceedings of the 18th IEEE international conference on tools with artificial intelligence (ICTAI-2006), Washington, DC, 13-15 November 2006, pp 465-473
13. Hamming R (1950) Error detecting and error correcting codes. Bell Syst Tech J 29:147-160
14. Hernandez M, Stolfo S (1995) The merge/purge problem for large databases. In: Proceedings of the 1995 ACM SIGMOD international conference on management of data, San Jose, May 1995, pp 127-138
15. Kira K, Rendell L (1992) A practical approach to feature selection. In: Proceedings of the ninth international workshop on machine learning (ML92), Aberdeen, 1-3 July 1992, pp 249-256
16. Monge A, Elkan C (1997) An efficient domain-independent algorithm for detecting approximately duplicate database records. In: Proceedings of the SIGMOD 1997 workshop on research issues on data mining and knowledge discovery, Tucson, 11 May 1997, pp 23-29
17. Pantel P, Philpot A, Hovy E (2005) An information theoretic model for database alignment. In: Proceedings of the 17th international conference on scientific and statistical database management, Santa Barbara, CA, 27-29 June 2005 pp 14-23
18. Richardson R, Smeaton A, Murphy J (1994) Using WordNet as a knowledge base for measuring semantic similarity between words. In: Proceedings of AICS conference, Trinity College, Dubkin, Septermber 1994, pp 179-192
19. Sarawagi S, Bhamidipaty A (2002) Interactive deduplication using active learning. In: Proceedings of the 8th ACM SIGKDD conference on knowledge discovery and data mining (KDD), Edmoton, Canada, 23-26 July 2002, pp 269-278
20. Shannon C (1949) The mathematical theory of information. University of Illinois Press, Urbana (Reprinted 1998)
21. Spiegel M, Schiller J, Srinivasan R (2000) Schaum's outline of probability and statistics. McGraw-Hill, New York
22. Tobita M, Horiuchi K, Araki K (2003) BirdsAnts: Bringing informative rules from a database system, aimed at novel targets search. Genome Inf 14:286-287
23. Tsai T, Lee S (2003) Simsearcher: A local similarity search engine for biological sequence databases, In: Proceedings of the international symposium on multimedia software engineering (ISMSE'03), Taichung Taiwan, December 2003, pp 305-312
24. Van Hulse J, Khoshgoftaar T, Huang H (2007) The pairwise attribute noise detection algorithm. Knowl Inf Syst 11(2):171-190
25. Wei L, Keogh E, Van Herle H, Mafra-Neto A, Abbott R (2007) Efficient query filtering for streaming time series with applications to semisupervised learning of time series classifiers. Knowl Inf Syst 11(3):313-344