Mostrar el registro sencillo del ítem

An intelligent approach for the design and development of a personalized system of knowledge representation

dc.contributor.authorAmelec, Viloriaspa
dc.contributor.authorPineda Lezama, Omar Bonergespa
dc.date.accessioned2019-06-10T13:05:08Z
dc.date.available2019-06-10T13:05:08Z
dc.date.issued2019
dc.identifier.issn00002010spa
dc.identifier.urihttp://hdl.handle.net/11323/4829spa
dc.description.abstractThis article proposes a generic presentation system for hypermedia systems of adaptive teaching that is highly independent from the representation of domain knowledge and the application state maintenance. Generality is achieved by providing an application framework for the definition of ontologies that best fit a domain or a specific author. The presentation of the pages to be generated is described in terms of classes and relationships of the ontology. For this purpose, a web page ranking algorithm based on automatic learning is used, specifically, the algorithm for Advanced Cluster Vector Page Ranking (ACVPR). This algorithm provides the user a powerful meta-search tool that presents a ranking order of the web page to quickly meet custom needs, especially when the search is erroneous or incomplete.spa
dc.language.isoeng
dc.publisherProcedia Computer Sciencespa
dc.relation.ispartof10.1016/j.procs.2019.04.176spa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/spa
dc.subjectAdaptive hypermediaspa
dc.subjectOntologiesspa
dc.subjectKnowledge representationspa
dc.subjectUser modelingspa
dc.subjectInterface design toolsspa
dc.subjectTeaching on the webspa
dc.subjectAlgorithm for advanced cluster vector page rankingspa
dc.subjectHipermedia adaptativaspa
dc.titleAn intelligent approach for the design and development of a personalized system of knowledge representationspa
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] Alam, M. and Sadaf, K., 2015. Labeling of Web Search Result Clusters using Heuristic Search and Frequent Itemset. Procedia Computer Science, Elsevier,216-222. [2] Chen, C. P., & Zhang, C. Y., 2014. Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, Elsevier, 275, 314-347 [3] Zhu, H., Ou, C. X., Van den Heuvel, W. J. A. M., & Liu, H.,2017. Privacy calculus and its utility for personalization services in e- commerce: An analysis of consumer decision-making. Information & Management, Elsevier, 54(4), 427-437. [4] Ferretti, S., Mirri, S., Prandi, C., & Salomoni, P., 2016. Automatic web content personalization through reinforcement learning. Journal of Systems and Software, Elsevier, 121, 157-169. [5] Malhotra, D., & Rishi, O. P.,, 2018. An intelligent approach to design of E-Commerce metasearch and ranking system using next- generation big data analytics. Journal of King Saud University-Computer and Information Sciences, Elsevier [6] Malthankar, S. V., & Kolte, S., 2016. Client Side Privacy Protection Using Personalized Web Search. Procedia Computer Science, Elsevier, 79, 1029-1035. [7] Zhang, G., Li, C. and Xing, C., 2012. A Semantic++ Social Search Engine Framework in the Cloud. In Semantics, Knowledge and Grids (SKG), 2012 Eighth International Conference, IEEE, 270-278 [8] Xiang, B., Jiang, D., Pei, J., Sun, X., Chen, E., & Li, H., 2010. Context-aware ranking in web search. In Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, ACM, 451-458. [9] Malhotra, D. and Rishi, O.P., 2016. IMSS-E: An Intelligent Approach to Design of Adaptive Meta Search System for E-Commerce Website Ranking. Proceedings of the International Conference on Advances in Information Communication Technology & Computing, ACM, doi>10.1145/2979779.2979782. [10] Malhotra, D. and Rishi, O.P., 2017. IMSS: A Novel Approach to Design of Adaptive Search System Using Second Generation Big data Analytics. Proceedings of International Conference on Communication and Networks, Springer, 189-196. [11] Malhotra, D., Malhotra, M. and Rishi, O.P., 2017.An Innovative Approach of Web Page Ranking Using Hadoop- and Map Reduce- Based Cloud Framework. Proceedings of Advances in Intelligent Systems and Computing, Vol.654, CSI, Springer, 421-427. [12] Zhou, D., Zhao, W., Wu, X., Lawless, S., & Liu, J., 2018. An iterative method for personalized results adaptation in cross-language search. Information Sciences, Elsevier, 430, 200-215. [13] Liu, Y., Bi, J.W. and Fan, Z.P., 2017. Ranking products through online reviews: A method based on sentiment analysis technique and intuitionistic fuzzy set theory. Information Fusion, 36, 149-161. [14] Yang, Y. F., Hwang, S. L., & Schenkman, B.,2012. An improved Web search engine for visually impaired users. Universal Access in the Information Society, 11(2), 113-124. [15] Torres-Samuel M., Vásquez C.L., Viloria A., Varela N., Hernández-Fernandez L., Portillo-Medina R. 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. 2018 [16] Ahmad, M. W., Doja, M. N., & Ahmad, T., 2017. Enumerative feature subset based ranking system for learning to rank in presence of implicit user feedback. Journal of King Saud University-Computer and Information Sciences. Elsevier [17] Kamatkar S.J., Tayade A., Viloria A., Hernández-Chacín A. (2018) Application of Classification Technique of Data Mining for Employee Management System. 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] Bouadjenek, M. R., Hacid, H., Bouzeghoub, M., & Vakali, A., 2016. Persador: personalized social document representation for improving web search. Information Sciences, Elsevier, 369, 614-633. [19] Aoki, Y., Koshijima, R. and Toyama, M., 2015. Automatic Determination of Hyperlink Destination in Web Index. In Proceedings of the 19th International Database Engineering & Applications Symposium, ACM, 206-207. [20] Sanchez L., Vásquez C., Viloria A., Cmeza-estrada (2018) Conglomerates of Latin American Countries and Public Policies for the Sustainable Development of the Electric Power Generation Sector. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham [21] Adamopoulos, P., 2014. On discovering non-obvious recommendations: Using unexpectedness and neighborhood selection methods in collaborative filtering systems. Proceedings of the 7th ACM international conference on Web search and data mining, ACM, 655- 660. [22] Viloria A., Lis-Gutiérrez JP., Gaitán-Angulo M., Godoy A.R.M., Moreno G.C., Kamatkar S.J. (2018) Methodology for the Design of a Student Pattern Recognition Tool to Facilitate the Teaching - Learning Process Through Knowledge Data Discovery (Big Data). In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Chamspa
dc.title.translatedUn enfoque inteligente para el diseño y desarrollo de un sistema personalizado de representación del conocimiento.spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


Ficheros en el ítem

Thumbnail
Nombre:
An intelligent approach for the ...
Tamaño:
957.9Kb
Formato:
PDF
Ver/
Thumbnail
Nombre:
license_rdf
Tamaño:
1.006Kb
Formato:
application/rdf+xml
Ver/

Este ítem aparece en la(s) siguiente(s) colección(ones)

  • Artículos científicos [3154]
    Artículos de investigación publicados por miembros de la comunidad universitaria.

Mostrar el registro sencillo del ítem

http://creativecommons.org/licenses/by-nc-sa/4.0/
Excepto si se señala otra cosa, la licencia del ítem se describe como http://creativecommons.org/licenses/by-nc-sa/4.0/