An intelligent approach for the design and development of a personalized system of knowledge representation
This 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...
- Autores:
-
Amelec, Viloria
Pineda Lezama, Omar Bonerge
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/4829
- Acceso en línea:
- https://hdl.handle.net/11323/4829
https://repositorio.cuc.edu.co/
- Palabra clave:
- Adaptive hypermedia
Ontologies
Knowledge representation
User modeling
Interface design tools
Teaching on the web
Algorithm for advanced cluster vector page ranking
Hipermedia adaptativa
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-sa/4.0/
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| dc.title.spa.fl_str_mv |
An intelligent approach for the design and development of a personalized system of knowledge representation |
| dc.title.translated.spa.fl_str_mv |
Un enfoque inteligente para el diseño y desarrollo de un sistema personalizado de representación del conocimiento. |
| title |
An intelligent approach for the design and development of a personalized system of knowledge representation |
| spellingShingle |
An intelligent approach for the design and development of a personalized system of knowledge representation Adaptive hypermedia Ontologies Knowledge representation User modeling Interface design tools Teaching on the web Algorithm for advanced cluster vector page ranking Hipermedia adaptativa |
| title_short |
An intelligent approach for the design and development of a personalized system of knowledge representation |
| title_full |
An intelligent approach for the design and development of a personalized system of knowledge representation |
| title_fullStr |
An intelligent approach for the design and development of a personalized system of knowledge representation |
| title_full_unstemmed |
An intelligent approach for the design and development of a personalized system of knowledge representation |
| title_sort |
An intelligent approach for the design and development of a personalized system of knowledge representation |
| dc.creator.fl_str_mv |
Amelec, Viloria Pineda Lezama, Omar Bonerge |
| dc.contributor.author.spa.fl_str_mv |
Amelec, Viloria Pineda Lezama, Omar Bonerge |
| dc.subject.spa.fl_str_mv |
Adaptive hypermedia Ontologies Knowledge representation User modeling Interface design tools Teaching on the web Algorithm for advanced cluster vector page ranking Hipermedia adaptativa |
| topic |
Adaptive hypermedia Ontologies Knowledge representation User modeling Interface design tools Teaching on the web Algorithm for advanced cluster vector page ranking Hipermedia adaptativa |
| description |
This 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. |
| publishDate |
2019 |
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2019-06-10T13:05:08Z |
| dc.date.available.none.fl_str_mv |
2019-06-10T13:05:08Z |
| dc.date.issued.none.fl_str_mv |
2019 |
| dc.type.spa.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Text |
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http://purl.org/redcol/resource_type/ART |
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00002010 |
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https://hdl.handle.net/11323/4829 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
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00002010 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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| dc.language.iso.none.fl_str_mv |
eng |
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eng |
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10.1016/j.procs.2019.04.176 |
| dc.relation.references.spa.fl_str_mv |
[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, Cham |
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Amelec, ViloriaPineda Lezama, Omar Bonerge2019-06-10T13:05:08Z2019-06-10T13:05:08Z201900002010https://hdl.handle.net/11323/4829Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/This 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.Amelec, Viloria-orcid-0000-0003-2673-6350-0Pineda Lezama, Omar Bonerge-365a03a0-145e-4df5-9abe-f5ccf9d96612-0engProcedia Computer Science10.1016/j.procs.2019.04.176[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, Chamhttp://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Adaptive hypermediaOntologiesKnowledge representationUser modelingInterface design toolsTeaching on the webAlgorithm for advanced cluster vector page rankingHipermedia adaptativaAn intelligent approach for the design and development of a personalized system of knowledge representationUn enfoque inteligente para el diseño y desarrollo de un sistema personalizado de representación del conocimiento.Artículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionPublicationORIGINALAn intelligent approach for the design and development of a personalized system of knowledge representation.pdfAn intelligent approach for the design and development of a personalized system of knowledge representation.pdfapplication/pdf980942https://repositorio.cuc.edu.co/bitstreams/83a1beca-e984-4223-a635-4826fa159a82/download1a4b84d4e85fffc1b141941bfaf74dbdMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81031https://repositorio.cuc.edu.co/bitstreams/38ef963a-698e-42a7-87ec-550d501d9ecb/download934f4ca17e109e0a05eaeaba504d7ce4MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/ba92d6aa-9080-4d21-9188-172b69cdb459/download8a4605be74aa9ea9d79846c1fba20a33MD53THUMBNAILAn intelligent approach for the design and development of a personalized system of knowledge representation.pdf.jpgAn intelligent approach for the design and development of a personalized system of knowledge representation.pdf.jpgimage/jpeg46977https://repositorio.cuc.edu.co/bitstreams/62882481-f979-4cf0-bef2-42a73b218ddd/downloadbdb7e370b88328af7a7f9e30448ac502MD55TEXTAn intelligent approach for the design and development of a personalized system of knowledge representation.pdf.txtAn intelligent approach for the design and development of a personalized system of knowledge representation.pdf.txttext/plain21594https://repositorio.cuc.edu.co/bitstreams/6bd40f47-63c6-41bd-90bb-60677df1c978/downloade452e3a184a5a6a0e52371d6f036784bMD5611323/4829oai:repositorio.cuc.edu.co:11323/48292024-09-17 10:14:59.985http://creativecommons.org/licenses/by-nc-sa/4.0/open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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 |