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Recovery of scientific data using Intelligent Distributed Data Warehouse

dc.contributor.authorViloria, Amelecspa
dc.contributor.authorNeira Rodado, Dioniciospa
dc.contributor.authorPineda Lezama, Omar Bonergespa
dc.date.accessioned2019-06-10T14:17:27Z
dc.date.available2019-06-10T14:17:27Z
dc.date.issued2019
dc.identifier.issn0000-2010spa
dc.identifier.urihttp://hdl.handle.net/11323/4842spa
dc.description.abstractA Retrieval System requires several components that define its functionality and behavior. In the case of a meta-search engine for the retrieval of scientific data, a schema that defines the way to store such data is considered a necessary element for its evolution. Unified profiles have been developed for the data storage of the entities involved in the scientific data management, generated from the fact of publishing a scientific paper. Such profiles are considered the beginning of the generation of new components for the meta-search engine that, using the proprietary information, can deliver information relevant for the user of the tool. To this end, the use of an intelligent distributed data warehouse is proposed.spa
dc.language.isoeng
dc.publisherProcedia Computer Sciencespa
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subjectscientific dataspa
dc.subjectmeta-dataspa
dc.subjectmeta-search enginespa
dc.subjectrecovery of informationspa
dc.subjectintelligent distributed data warehousespa
dc.titleRecovery of scientific data using Intelligent Distributed Data Warehousespa
dc.typeArtículo de revistaspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.relation.references[1] Garciarena Ucelay, M.J., Villegas, M.P., Cagnina, L., Errecalde, M.L.: Cross domain author profiling task in spanish language: an experimental study. J. Comput. Sci. Technol. 15, no. 2, (2015). [2] Bose, R., Frew, J.: Lineage retrieval for scientific data processing: a survey. ACM Computing. Surveys. CSUR. 37, 1–28 (2005). [3] Bhaduri K., Wolf R., Giannella C., and Kargupta H., “Distributed decision-tree induction in peer-to-peer systems.”, Statistical Analysis and Data Mining, Vol. 1, Issue 2, pp. 85–103, 2008. [4] Duan L., Xu L., Liu Y. and Lee J., “Cluster-based outlier detection.”, Annals of Operations Research 168, pp. 151–168, 2009. [5] Abhay Kumar Agarwal and Neelendra Badal “Data Storing in Intelligent and Distributed Data Warehouse using Unique Identification Number” published in International Journal of Grid and Distributed Computing, Publisher: SERSC Australia, (ISSN: 2005-4262 (Print) ISSN: 2207-6379 (Online)), Volume 10, No. 9, pp. 13-32, September 2017. [6] Agrawal R. and Srikant R., “Fast algorithms for mining association rules in large databases.”, In J. B. Bocca, M. Jarke, and C. Zaniolo, editors, VLDB, Chile, pp. 487–499, 1994. [7] Chiang D., Lin C. and Chen M., “The adaptive approach for storage assignment by mining data of warehouse management system for distribution centre’s.”, Enterp. Inf. Syst, Vol. 5, Issue 2, pp. 219–234, 2001. [8] Abhay Kumar Agarwal and N. Badal “A Novel Approach for Intelligent Distribution of Data Warehouses” published in Egyptian Informatics Journal-Elsevier, Egypt, (ISSN: 1110-8665), http://dx.doi.org/10.1016/j.eij.2015.10.002, Volume 17, pp. 147-159, October, 2015. [9] Savasere A., Omiecinski E. and Navathe S., “An efficient algorithm for data mining association rules in large databases”, In Proceedings of 21st Very Large Data Base Conference, pp. 432- 444, 1995. [10] Stolfo S., Prodromidis A. L., Tselepis S., Lee W. and Fan D. W., “Jam: Java agents for meta- learning over distributed databases.”, In Proceedings of 3rd International Conference on Knowledge Discovery and Data Mining., pp. 74-81, 1997. [11] Prodromidis A., Chan P. K., Stolfo S. J., “Meta learning in distributed data mining systems: Issues and approaches.”, In Kargupta H., Chan P. (eds) Book on Advances in Distributed and Parallel Knowledge Discovery, AAAI/MIT Press, 2000. [12] Grossman R. l., Bailey S. M., Sivakumar H. and Turinsky A. L., “papyrus: A system for data mining over local and wide area clusters and super-clusters.”, In Proceedings of ACM/IEEE Conference on Supercomputing, Article No. 63, 1999. [13] Chattratichat J., Darlington J., Guo Y., Hedvall S., Kohler M. and Syed J.“An architecture for distributed enterprise data mining.”, In Proceedings of 7th International Conference on High- Performance Computing and Networking, Netherlands, pp. 573-582, 1999. [14] Wang L., et. al., "G-Hadoop: MapReduce across Distributed Data Centers for Data-Intensive Computing.", Future Generation Computer Systems, Vol. 29, Issue 3, pp. 739-750, 2013. [15] Butenhof D. R., “Programming with POSIX threads.”, Addison-Wesley Longman Publishing Company, USA, 1997. [16] Gaitán-Angulo M., Cubillos Díaz J., Viloria A., Lis-Gutiérrez JP., Rodríguez-Garnica P.A. (2018) Bibliometric Analysis of Social Innovation and Complexity (Databases Scopus and Dialnet 2007–2017). In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham [17] Torres-Samuel M., Vásquez C.L., Viloria A., Varela N., Hernández-Fernandez L., Portillo-Medina R. (2018)a Analysis of Patterns in the University World Rankings Webometrics, Shanghai, QS and SIR-SCimago: Case Latin America. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham [18] Torres-Samuel M, Carmen Vásquez, Amelec Viloria, Tito Crissien Borrero, Noel Varela, Danelys Cabrera, Mercedes Gaitán-Angulo, JennyPaola Lis-Gutiérrez. (2018)b Efficiency Analysis of the Visibility of Latin American Universities and Their Impact on the Ranking Web. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham [19] Torres-Samuel M., Vásquez C., Viloria A., Lis-Gutiérrez JP., Borrero T.C., Varela N. (2018)c Web Visibility Profiles of Top100 Latin American Universities. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham [20] Vásquez C, Maritza Torres-Samuel, Amelec Viloria, Tito Crissien Borrero, Noel Varela, Jenny-Paola Lis-Gutiérrez, Mercedes GaitánAngulo. (2018) Visibility of Research in Universities: The Triad Product-Researcher-Institution. Case: Latin American Countries. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Chamspa
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