Sistema híbrido para la búsqueda de objetos de aprendizaje textuales en repositorios, basado en metadatos y contenido

dc.contributorDuque Méndez, Néstor Darío
dc.contributorGAIA
dc.creatorOsorio-Zuluaga, Germán A.
dc.date.accessioned2022-06-08T21:18:26Z
dc.date.available2022-06-08T21:18:26Z
dc.date.created2022-06-08T21:18:26Z
dc.date.issued2022
dc.identifierhttps://repositorio.unal.edu.co/handle/unal/81542
dc.identifierUniversidad Nacional de Colombia
dc.identifierRepositorio Institucional Universidad Nacional de Colombia
dc.identifierhttps://repositorio.unal.edu.co/
dc.description.abstractEl vertiginoso avance de la Web ha promovido el desarrollo de la educación a distancia. En este sentido, numerosas organizaciones ofrecen y comparten recursos educativos en diferentes formatos a los alumnos a nivel local y global. Algunos de estos recursos se denominan objetos de aprendizaje (LO) y generalmente se almacenan en repositorios. Además, LO se pueden etiquetar a través de metadatos para facilitar su búsqueda y recuperación. Estas actividades se basan principalmente en metadatos. En otros contextos web, se utilizan búsquedas de texto completo. Además, según la revisión de la literatura realizada para apoyar esta investigación, las búsquedas de metadatos y texto completo en repositorios presentan varias problemáticas que persisten y producen una baja precisión en los resultados de búsqueda de objetos de aprendizaje en repositorios. Por ello, para intentar superar este problema planteado anteriormente, ha ido ganando importancia el uso de métodos híbridos, en los que se integran varios métodos para conseguir mejores resultados de búsqueda. A partir de la investigación realizada para el desarrollo de esta tesis, fue posible demostrar que, al integrar el texto completo y los metadatos en las búsquedas de objetos de aprendizaje en un sistema híbrido, se logran mejoras significativas en los resultados de búsqueda. Adicionalmente, el modelo híbrido propuesto para la búsqueda de objetos de aprendizaje en repositorios puede ser implementado en otros contextos de isoformas, como gestores bibliográficos. En este sentido, puede convertirse en una herramienta adicional que ayude a los investigadores a explorar su documentación, que, con el tiempo, crece en gran medida.
dc.description.abstractThe vertiginous advance of the Web has promoted the development of distance education. In this sense, numerous organizations offer and share educational resources in different formats to learners locally and globally. Some of these resources are called learning objects (LO) and are usually stored in repositories. Additionally, LO can be tagged through metadata to facilitate their search and retrieval. These activities are mainly based on metadata. In other web contexts, full-text searches are used. Furthermore, according to the literature review carried out to support this research, metadata and full-text searches in repositories present several problematics that persist and produce a low precision in the search results of learning objects in repositories. Therefore, to try to overcome this problem raised above, the use of hybrid methods has been gaining importance, in which several methods are integrated to achieve better search results. Based on the research carried out for the development of this thesis, it was possible to demonstrate that, by integrating the full-text and the metadata in the searches for learning objects in a hybrid system, significant improvements are achieved in the search results. Additionally, the hybrid model proposed for the search for learning objects in repositories can be implemented in other isoform contexts, such as bibliographic managers. In this sense, it can become an additional tool that helps researchers to explore their documentation, which, over time, grows to a great extent.
dc.languageeng
dc.publisherUniversidad Nacional de Colombia
dc.publisherManizales - Ingeniería y Arquitectura - Doctorado en Ingeniería - Industria y Organizaciones
dc.publisherDepartamento de Ingeniería Industrial
dc.publisherFacultad de Ingeniería y Arquitectura
dc.publisherManizales, Colombia
dc.publisherUniversidad Nacional de Colombia - Sede Manizales
dc.relationManal Abdullah and Nashwa Abdel Aziz Ali. E-learning Standards. In Communication, Management and Information Technology:, pages 639–648. CRC Press, Leiden, The Netherlands, 2017.
dc.relationEntisar Abolkasim, Lydia Lau, and Vania Dimitrova. A Semantic-Driven Model for Ranking Digital Learning Objects Based on Diversity in the User Comments. In European Conference on Technology Enhanced Learning EC-TEL 2016, pages 3–15, Lyon, France, 2016. Springer Cham.
dc.relationHadhemi Achour and Maroua Zouari. Multilingual Learning Objects Indexing and Retrieving Based on Ontologies. In 2013 World Congress on Computer and Information Technology (WCCIT), Sousse, Tunisia, 2013. IEEE Xplore.
dc.relationCharu C Aggarwal. Recommender Systems: The Textbook. Springer, 2016.
dc.relationJose Aguilar, Camilo Salazar, Henry Velasco, Julian Monsalve-Pulido, and Edwin Montoya. Comparison and evaluation of different methods for the feature extraction from educational contents. Computations, 8(2):1–20, 2020.
dc.relationRachid Ahmed-Ouamer and Arezki Hammache. Ontology-based information retrieval for e-learning of computer science. In 2010 International Conference on Machine and Web Intelligence, ICMWI 2010, pages 250–257, Algiers, Algeria, 2010. IEEE.
dc.relationAli Alharbi, Frans Henskens, and Michael Hannaford. Student-Centered Learning Objects to Support the Self-Regulated Learning of Computer Science. Creative Education, 03(26):773–783, 2012.
dc.relationNasir Ali, Yann-Gaël Guéhénueuc, and Giuliano Antoniol. Trustrace: Mining Software Repositories to Improve the Accuracy of Requirement Traceability Links. IEEE Transactions on Software Engineering, 39(5):725–741, 2013.
dc.relationOmar Alonso and Ricardo Baeza-Yates. An Analysis of Crowdsourcing Relevance Assessments in Spanish. In Actas del I Congreso Español de Recuperación de Información, CERI 2010, pages 243–250, 2010.
dc.relationOmar Alonso and Ricardo Baeza-Yates. Design and implementation of relevance assessments using crowdsourcing. In Advances in information retrieval, pages 153–164. Springer Berlin Heidelberg, 2011.
dc.relationOmar Alonso and Stefano Mizzaro. Using crowdsourcing for TREC relevance assessment. Information Processing and Management, 48(6):1053–1066, 2012.
dc.relationGustavo Javier Astudillo. Análisis del estado del arte de los objetos de aprendizaje. Revisión de su definición y sus posibilidades. Technical report, Universidad Nacional de La Plata, 2011.
dc.relationCh Aswani Kumar, M Radvansky, and J Annapurna. Analysis of a vector space model, latent semantic indexing and formal concept analysis for information retrieval. Cybernetics and Information Technologies, 12(1):34–48, 2012.
dc.relationJohn Atkinson, Andrea Gonzalez, Mauricio Munoz, and Hernán Astudillo. Web metadata extraction and semantic indexing for learning objects extraction. Applied Intelligence, 41(2):649–664, 2014.
dc.relationRicardo Baeza-Yates and Berthier Ribeiro-Neto. Modern Information retrieval - the concepts and technology behind search. Addison Wesley, Essex, 2011.
dc.relationMiri Barak and Shani Ziv. Wandering: A Web-based platform for the creation of locationbased interactive learning objects. Computers & Education, 62:159–170, mar 2013.
dc.relationA Barbagallo and Anna Formica. ELSE: an ontology-based system integrating semantic search and e-learning technologies. Interactive Learning Environments, 25(5):650–666, 2017.
dc.relationCarla Fillmann Barcelos, João Carlos Gluz, and Rosa Maria Vicari. An Agent-based Federated Learning Object Search Service. Interdisciplinary Journal of E-Learning and Learning Objects, 7, 2011.
dc.relationJeffrey Beall. Metadata and Data Quality Problems in the Digital Library. Journal of Digital Information, 6(3), 2006.
dc.relationJeffrey Beall. TheWeaknesses of Full-Text Searching. The Journal of Academic Librarianship, 34(5):438–444, sep 2008.
dc.relationCarlos Becerra, Hernán Astudillo, and Marcelo Mendoza. Improving Learning Objects Recommendation Processes by Using Domain Description Models. LACLO, 3(1), 2012.
dc.relationStefano Bianchi, Christian Mastrodonato, Gianni Vercelli, and Giuliano Vivanet. Use of ontologies to annotate and retrieve educational contents: The AquaRing approach. Journal of E-Learning and Knowledge Society, 5(1):211–220, 2009.
dc.relationYevgen Biletskiy, Hamidreza Baghi, Igor Keleberda, and Michael Fleming. An adjustable personalization of search and delivery of learning objects to learners. Expert Systems with Applications, 36(5):9113–9120, 2009.
dc.relationJ. Bobadilla, F. Ortega, A. Hernando, and A. Gutiérrez. Recommender systems survey. Knowledge-Based Systems, 46:109–132, 2013.
dc.relationPaolo Bolettieri, Fabrizio Falchi, Claudio Gennaro, and Fausto Rabitti. Automatic metadata extraction and indexing for reusing e-learning multimedia objects. In The ACM International Multimedia Conference and Exhibition, pages 21–28, 2007.
dc.relationMarkus Borg, Per Runeson, and Anders Ardo. Recovering from a decade: a systematic mapping of information retrieval approaches to software traceability. Empirical Software Engineering, 19(6):1565–1616, 2014.
dc.relationSergey Brin and Lawrence Page. The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems, 30(1/7):107–117, 1998.
dc.relationRobin Burke. Hybrid Recommender Systems : Survey and Experiments. User Modeling and UserAdapted Interaction, 12(4):331–370, 2002.
dc.relationVannevar Bush. As we May Think. The atlantic monthly, 176(1):101–108, 1945.
dc.relationStefan Buttcher, Charles L. A. Clarke, and Gordon V. Cormack. Information Retrieval: Implementing and Evaluating Search Engines. MIT Press, Cambridge, Massachusetts, 2010.
dc.relationFidel Cacheda Seijo, Juan Manuel Fernández Luna, and Juan Francisoc Huete Guadix. Recuperación de Información: Un enfoque práctico y disciplinar. RA-MA S.A. Editorial y Publicaciones, 2011.
dc.relationLuca Cagliero, Paolo Garza, and Elena Baralis. ELSA: A Multilingual Document Summarization Algorithm Based on Frequent Itemsets and Latent Semantic Analysis. ACM Transactions on Information Systems, 37(2):1–33, mar 2019.
dc.relationAlberto Camaraza Monserrate. Recuperación de información: reflexiones epistémicas de una ciencia en su estado embrionario. Acimed, 13(6):1–26, 2005.
dc.relationGiovanni Capobianco, Andrea De Lucia, Rocco Oliveto, Annibale Panichella, and Sebastiano Panichella. Improving IR-based traceability recovery via noun-based indexing of software artifacts. Software-Evolution and Process, 25(7):743–762, jul 2013.
dc.relationJorge Castro Gallardo. Novel Models in Recommender Systems and Group Recommender Systems for Improving Recommendations. PhD thesis, Universidad de Granada, 2018.
dc.relationCristian Cechinel, Sandro Silva Da Camargo, Xavier Ochoa, Salvador Sánchez Alonso, and Miguel Ángel Sicilia. Populating learning object repositories with hidden internal quality information. In CEUR Workshop Proceedings, volume 896, pages 11–22, 2012.
dc.relationDoina Ana Cernea, Esther Del Moral, and Jose E Labra Gayo. SOAF: Semantic Indexing System Based on Collaborative Tagging. Interdisciplinary Journal of E-Learning and Learning Objects, 4(1):137–150, 2008.
dc.relationW. Bruce Croft, Donald Metzler, and Trevor Strohman. Search Engines: Information retrieval in practice. 2015.
dc.relationAnupam Das and Mohammad Al Akour. Intelligent Recommendation System for ELearning using Membership Optimized Fuzzy Logic Classifier. In 2020 IEEE Pune Section International Conference, PuneCon 2020, pages 1–10, 2020.
dc.relationAndrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella, and Sebastiano Panichella. Labeling source code with information retrieval methods: an empirical study. Empirical Software Engineering, pages 1–38, 2013.
dc.relationScott Deerwester, Susan Dumais, GeorgeWFurnas, Thomas Landauer, and Richard Harshman. Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science, 41(6):391–407, 1990.
dc.relationLuis Guillermo Díaz M. Estadística Multivariada: Inferencia y Métodos. Universidad Nacional de Colombia, Bogotá, 2007.
dc.relationChris DiBona, Sam Ockman, and Mark Stone. OpenSources: Voices from the open source revolution. O’Reilly, 1999.
dc.relationBogdan Dit, Meghan Revelle, Malcom Gethers, and Denys Poshyvanyk. Feature location in source code: a taxonomy and survey. Journal of Software-Evolution and Process, 25(1):53– 95, 2013.
dc.relationNhon V. Do, Hien D. Nguyen, and Long N. Hoang. Some techniques for intelligent searching on ontology-based knowledge domain in e-learning. In IC3K 2020 - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, volume 2, pages 313–320, 2020.
dc.relationNéstor Darío Duque-Méndez, Demetrio Arturo Ovalle, and Julián Moreno Cadavid. Objetos de Aprendizaje, Repositorios y Federaciones: Conocimiento para Todos. Universidad Nacional de Colombia, Manizales, 2014.
dc.relationNicholas Evangelopoulos, Xiaoni Zhang, and Victor R. Prybutok. Latent Semantic Analysis : Five methodological recommendations. European Journal of Information Systems, 21(1):70–86, 2012.
dc.relationTránsito Ferreras-Fernández, Helena Martín-Rodero, Francisco J. García-Peñalvo, and José A. Merlo-Vega. The systematic review of literature in LIS: An approach. Proceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality - TEEM ’16, pages 291–296, 2016.
dc.relationAnna Formica, Michele Missikoff, Elaheh Pourabbas, and Francesco Taglino. Semantic search for matching user requests with profiled enterprises. Computers in Industry, 64(3):191–202, 2013.
dc.relationBoris Forthmann, Oluwatosin Oyebade, Adebusola Ojo, Fritz Günther, and Heinz Holling. Application of Latent Semantic Analysis to Divergent Thinking is Biased by Elaboration. The Journal of Creative Behavior, 53(4):559–575, dec 2019.
dc.relationFabio Gasparetti, Carlo De Medio, Carla Limongelli, Filippo Sciarrone, and Marco Temperini. Prerequisites between learning objects: Automatic extraction based on a machine learning approach. Telematics and Informatics, 35(3):595–610, 2018.
dc.relationOuafia Ghebghoub, Marie Hélène Abel, and Claude Moulin. Learning Object Indexing Tool Based on a LOM Ontology. In IEEE International Conference on Advanced Learning Technologies, pages 576–578, Santander, Spain, 2008. IEEE Computer Society.
dc.relationAna Belén Gil, Fernando De la Prieta, and Vivian F López. Hybrid Multiagent System for Automatic Object Learning Classification. In E S Corchado Rodriguez, editor, Hybrid Artificial Intelligency Systems, pages 61–68. Springer, San Sebastián, Spain, 2010.
dc.relationJoão Carlos Gluz, Ederson Luis Silveira, Luiz Rodrigo Jardim da Silva, and Jorge Luis Victoria Barbosa. Towards a semantic repository for learning objects: Design and evaluation of core services. Journal of Universal Computer Science, 22(1):16–36, 2016.
dc.relationA. Gordillo, E. Barra, and J. Quemada. A Hybrid Recommendation Model for Learning Object Repositories. IEEE Latin America Transactions, 15(3):462–473, 2017.
dc.relationJuan-Miguel Gracia. Álgebra Lineal tras los buscadores de Internet. Technical report, 2002.
dc.relationHany M Harb, Khaled Fouad, and Nagdy M. Nagdy. Semantic Retrieval Approach for Web Documents. International Journal of Advanced Computer Science and Applications, 2(9):67–76, 2011.
dc.relationSamer Hassan and Rada Mihalcea. Learning to identify educational materials. ACM Transactions on Speech and Language Processing, 8(2):1–18, 2008.
dc.relationI-Ching Hsu. Intelligent Discovery for Learning Objects Using SemanticWeb Technologies. Educational Technology & Society, 15(1):298–312, 2012.
dc.relationIEEE. Standard for Learning Object Metadata. Technical report, Institute of Electrical and Electronics Engineers, New York, 2002.
dc.relationAmirah Ismail and Mike Joy. Semantic Searches for Extracting Similarities in a Content Management System. In IEEE International Conference on Semantic Technology and Information Retrieval, number June, pages 113–118, Putrajaya (Malaysia), 2011. IEEE.
dc.relationDietmar Jannach, Markus Zanker, Alexander Felfernig, and Gerhard Friedrich. Recommender Systems An Introduction. Cambridge University Press, New York, 2011.
dc.relationYuri Kagolovsky and Jochen R. Moehr. Terminological Problems in Information Retrieval. Journal of Medical Systems, 27(5):399–408, 2003.
dc.relationP Kalyanaraman and S Margret Anouncia. Nature inspired clustering and indexing of learning objects based on learners cognitive skills. International Journal of Knowledge-Based and Intelligent Engineering Systems, 23(1):41–53, 2019.
dc.relationGabriella Kazai, Natasa Milic-Frayling, and Jamie Costello. Towards Methods for the Collective Gathering and Quality Control of Relevance Assessments. In Proceedings of the 32Nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’09, pages 452–459, New York, NY, USA, 2009. ACM.
dc.relationChih-Kun Ke, Kai-Ping Liu, and Wen-Chin Chen. Building a Smart E-Portfolio Platform for Optimal E-Learning Objects Acquisition. Mathematical Problems in Engineering, 2013.
dc.relationSabrina Keenan, Alan F. Smeaton, and Gary Keogh. The effect of pool depth on system evaluation in TREC. Journal of the American Society for Information Science and Technology, 52(7):570–574, 2001.
dc.relationIgor Keleberda, Victoria Repka, and Yevgen Biletskiy. Building learner’s ontologies to assist personalized search of learning objects. In International conference on electronic commerce, pages 569–573. ACM, 2006.
dc.relationMohamed Koutheaïr Khribi, Mohamed Jemni, and Olfa Nasraoui. Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval. Educational Technology & Society, 12(4):30–42, 2009.
dc.relationSuhyeon Kim, Haecheong Park, and Junghye Lee. Word2vec-based latent semantic analysis (W2V-LSA) for topic modeling: A study on blockchain technology trend analysis. Expert Systems with Applications, 152:113401, aug 2020.
dc.relationJon M. Kleinberg. Authoritative Sources in a Hyperlinked Environment. Journal of the ACM, 46(May 1997):668–677, 1999.
dc.relationDimitrios A Koutsomitropoulos, Andreas D Andriopoulos, and Spiridon D Likothanassis. Semantic Classification and Indexing of Open Educational Resources with Word Embeddings and Ontologies. Cybernetics and Information Technologies, 20(5):95–116, 2020.
dc.relationDimitrios A Koutsomitropoulos and Georgia Solomou. A learning object ontology repository to support annotation and discovery of educational resources using semantic thesauri. IFLA Journal, 44(1):4–22, 2018.
dc.relationDimitrios A Koutsomitropoulos, Georgia Solomou, and Katerina Kalou. Federated semantic search using terminological thesauri for learning object discovery. Journal of Enterprise Information Management, 30(5), 2017.
dc.relationAlberto H F Laender, Marcos André Gonçalves, Ricardo G. Cota, Anderson A Ferreira, Rodrygo L T Santos, and Allan J C Silva. Keeping a Digital Library Clean : New Solutions to Old Problems. In Eighth ACM symposium on Document engineering, pages 257–262, New York, 2008. ACM.
dc.relationThomas Landauer and Susan Dumais. Latent semantic analysis. Scholarpedia, 3(11):4356, 2008.
dc.relationThomas Landauer, Peter W. Foltz, and Darrell Laham. An introduction to latent semantic analysis. Discourse Processes, 25(2-3):259–284, jan 1998.
dc.relationArash Habibi Lashkari, Fereshteh Mahdavi, and Vahid Ghomi. A Boolean Model in Information Retrieval for Search Engines. In 2009 International Conference on Information Management and Engineering, pages 385–389, 2009.
dc.relationMing Che Lee, Kun Hua Tsai, and Tzone I Wang. An Ontological Approach for Semantic- Aware Learning Object Retrieval. In IEEE International Conference on Advanced Learning Technologies (ICALT’06), pages 208–210, Kerkrade, The Netherlands, 2006. IEEE Xplore.
dc.relationMing Che Lee, Kun Hua Tsai, and Tzone I Wang. A practical ontology query expansion algorithm for semantic-aware learning objects retrieval. Computers&Education, 50(4):1240– 1257, may 2008.
dc.relationSangno Lee, Jaeki Song, and Yongjin Kim. An Empirical Comparison of Four Text Mining Methods. Journal of Computer Information Systems, pages 1–10, 2010.
dc.relationLothar Lemnitzer, Kiril Simov, Petya Osenova, Eelco Mossel, and Paola Monachesi. Using a domain-ontology and semantic search in an e-learning environment. In Innovative Techniques in Instruction Technology, E-Learning, E-Assessment, and Education, pages 279– 284. Springer, 2008.
dc.relationVivian F López, Fernando De La Prieta, Mitsunori Ogihara, and Ding Ding Wong. A model for multi-label classification and ranking of learning objects. Expert Systems with Applications, 39:8878–8884, 2012.
dc.relationClara López Guzmán. Los Repositorios de Objetos de Aprendizaje como soporte a un entorno e-learning. PhD thesis, Universidad de Salamanca, 2005.
dc.relationZohair Malki. Comprehensive Study and Comparison of Information Retrieval Indexing Techniques. International Journal of Advanced Computer Science and Applications, 7(1):132–140, 2016.
dc.relationJ. Mannar Mannan, K. Sindhanai Selvan, and R. Mohemmed Yousuf. Independent document ranking for E-learning using semantic-based document term classification. Journal of Intelligent and Fuzzy Systems, 40(1):893–905, 2021.
dc.relationChristopher D Manning, Prabhakar Raghavan, and Hinrich Schutze. An Introduction to Information Retrieval. Cambridge University Press, Cambridge, England, 2009.
dc.relationM. E. Maron and J. L. Kuhns. On Relevance, Probabilistic Indexing and Information Retrieval. Journal of the ACM, 7(3):216–244, 1960.
dc.relationDian I Martin and Michael W Berry. Mathematical Foundations Behind Latent Semantic Analysis. In Handbook of Latent Semantic Analysis, chapter 2, pages 35–55. RoutLedge, New York, 2007.
dc.relationLuis Javier Martínez Rodríguez. Cómo buscar y usar información científica: Guía para estudiantes universitarios 2013. Universidad de Cantabria, Santander, España, 2013.
dc.relationLuciana A Martinez Zaina and Graça Bressan. Learning Objects Retrieval From Contextual Analysis of User Preferences To Enhance E- Learning Personalization. In IADIS International Conference WWW/Internet, pages 237–244, Algarve, Portugal, 2009
dc.relationKaiz Merchant and Yash Pande. NLP Based Latent Semantic Analysis for Legal Text Summarization. In 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pages 1803–1807. IEEE, sep 2018.
dc.relationRada Mihalcea and Dragomir Radev. Graph-Based Natural Language Processing and Information Retrieval. Cambridge University Press, New York, 2011.
dc.relationColombia Ministerio_de_Educación_Nacional. Recursos Educativos Digitales Abiertos - Colombia. MEN, Bogotá, 2012.
dc.relationDavid Moher, Alessandro Liberati, Jennifer Tetzlaff, Douglas G Altman, and Group PRISMA. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. Annals of Internal Medicine, 151(4):264–269, 2009.
dc.relationMohammadreza Molavi, Mohammadreza Tavakoli, and Gábor Kismihók. Extracting topics from open educational resources. In European Conference on Technology Enhanced Learning, volume 12315 LNCS, pages 455–460. Springer Cham, 2020.
dc.relationJosé A. Moral-Muñoz, Enrique Herrera-Viedma, Antonio Santisteban-Espejo, and Manuel J. Cobo. Software tools for conducting bibliometric analysis in science: An upto- date review. Profesional de la Informacion, 29(1):1–20, 2020.
dc.relationOlfa Nasraoui and Leyla Zhuhadar. Improving recall and precision of a personalized semantic search engine for E-learning. In 4th International Conference on Digital Society, ICDS 2010, volume 4, pages 216–221. IEEE Computer Society, 2010.
dc.relationAndreia Dal Ponte Novelli and José Maria Parente De Oliveira. Simple Method for Ontology Automatic Extraction from Documents. International Journal of Advanced Computer Science and Applications, 3(12):44–51, 2012.
dc.relationXavier Ochoa and Erik Duval. Towards Automatic Evaluation of Learning Object Metadata Quality. In Advances in Conceptual Modeling-Theory and Practice, pages 372–381. Springer Berlin Heidelberg, 2006.
dc.relationXavier Ochoa and Erik Duval. Use of contextualized attention metadata for ranking and recommending learning objects. In The 1st international workshop on Contextualized attention metadata collecting managing and exploiting of rich usage information CAMA 06, pages 9–16, 2006
dc.relationXavier Ochoa and Erik Duval. Relevance Ranking Metrics for Learning Objects. IEEE Transactions on Learning Technologies, 1(1):34–48, 2008.
dc.relationXavier Ochoa and Erik Duval. Quantitative Analysis of Learning Object Repositories. IEEE Transactions on Learning Technologies, 2(3):226–238, jul 2009.
dc.relationXavier Ochoa, Joris Klerkx, Bram Vandeputte, and Erik Duval. On the Use of Learning Object Metadata: The GLOBE Experience. In Lecture Notes in Computer Science, pages 271–284. Springer-Verlag Berlin Heidelberg, 2011.
dc.relationGermán A Osorio-Zuluaga and Néstor Darío Duque-Méndez. Recuperación de objetos de aprendizaje en repositorios: Una aplicación con búsqueda semántica. Revista Gerencia Tecnológica Informática, 14(40):43–54, 2015.
dc.relationGermán A Osorio-Zuluaga and Néstor Darío Duque-Méndez. Collaborative construction of metadata and full-text dataset. In Proceedings - 2016 11th Latin American Conference on Learning Objects and Technology, LACLO 2016, San Carlos, Costa Rica, 2016. IEEE Xplore.
dc.relationGermán A Osorio-Zuluaga and Néstor Darío Duque-Méndez. Search and selection of learning objects in repositories : a review. In XIII Conferência Latino-americana de Tecnologias de Aprendizagem - LACLO 2018, pages 1–8, Sao Paulo, 2018. IEEE Xplore.
dc.relationNikolaos Palavitsinis, Nikos Manouselis, and Salvador Sanchez-Alonso. Metadata quality in Learning Object Repositories: A case study. Electronic Library, 32(1), 2014.
dc.relationDaniel Peña. Análisis de datos multivariados. McGraw Hill, Madrid, 2002.
dc.relationRoberto Pérez-Rodríguez, Luis Anido-Rifón, Miguel Gómez-Carballa, and Marcos Mouriño-García. Architecture of a concept-based information retrieval system for educational resources. Science of Computer Programming, 129:72–91, 2016.
dc.relationLaura Plaza Morales. Uso de Grafos Semánticos en la Generación Automática de Resúmenes y Estudio de su Aplicación en Distintos Dominios: Biomedicina , Periodismo y Turismo. PhD thesis, Universidad Complutense de Madrid, 2011.
dc.relationPithamber R Polsani. Use and Abuse of Reusable Learning Objects. Journal of Digital Information, 3(4), 2003.
dc.relationMartin F Porter. An algorithm for suffix stripping, 1980
dc.relationDenys Poshyvanyk, Yann-Gael Guéhéneuc, Andrian Marcus, Giuliano Antoniol, and Vaclav Rajlich. Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval. IEEE Transactions on Software Engineering, 33(6):420–432, 2007.
dc.relationMohammad Mustaneer Rahman and Nor Aniza Abdullah. A personalized group-based recommendation approach for web search in E-learning. IEEE Access, 6:34166–34178, 2018.
dc.relationMohammad Mustaneer Rahman, Nor Aniza Abdullah, and Fnu Aurangozeb. A Framework for Designing a Personalised Web-based Search Assistant Tool for eLearning. In International Conference on Information and Communication Technology (ICoICT), Malacca, Malaysia, 2017. IEEE Xplore.
dc.relationAldo Ramirez-Arellano, Juan Bory-Reyes, and Luis Manuel Hernández-Simón. Learning Object Assembly Based on Learning Styles. Journal of Educational Computing Research, 55(6):757–788, 2017.
dc.relationStephen Robertson. The probability ranking principle in IR. Journal of documentation, 33(4):281–286, 1977.
dc.relationStephen Robertson and K Sparck Jones. Relevance Weighting of Search Terms. Journal of the American Society for Information Science, 27(3):129–146, 1976.
dc.relationStephen Robertson, S Walker, S Jones, M M Hancock-Beaulieu, and M Gatford. Okapi at TREC-3. In Overview of the Third Text REtrieval Conference (TREC-3), pages 109–126. 1995.
dc.relationRonaldo Lima Rocha Campos, Rafaela Lunardi Comarella, and Ricardo Azumbuja Silveira. Multiagent Based Recommendation System Model for Indexing and Retrieving Learning Objects. In PAAMS 2013: International Conference on Practical Applications of Agents and Multi-Agent Systems, pages 328–339. Springer Berlin Heidelberg, 2013.
dc.relationPaula Andrea Rodríguez M, Gustavo Isaza, and Néstor Darío Duque-Méndez. Búsqueda personalizada en Repositorios de Objetos de Aprendizaje a partir del perfil del estudiante. Avances Investigación en Ingeniería, 9(1):73–83, 2012.
dc.relationL. Antony Rosewelt and J. Arokia Renjit. A content recommendation system for effective elearning using embedded feature selection and fuzzy DT based CNN. Journal of Intelligent and Fuzzy Systems, 39(1):795–808, 2020.
dc.relationA Sai Sabitha and Deepti Mehrotra. A push strategy for delivering of Learning Objects using meta data based association analysis (FP-Tree). In 2013 International Conference on Computer Communication and Informatics, pages 1–4. IEEE, 2013.
dc.relationA Sai Sabitha, Deepti Mehrotra, and Abhay Bansal. Delivery of learning knowledge objects using fuzzy clustering. Education and Information Technologies, 21(5):1329–1349, 2016.
dc.relationGerard Salton and Christopher Buckley. Term-weighting approaches in automatic text retrieval. Information processing & management, 24(5):513–523, 1988.
dc.relationGerard Salton, A Wong, and C S Yang. A Vector Space Model for Automatic Indexing. Magazine Communications of the ACM, 18(11):613–620, 1975.
dc.relationJosé Antonio Salvador Oliván and Rosario Arquero Avilés. Una aproximación al concepto de recuperación de información en el marco de la ciencia de la documentación. Investigación Bibliotecológica, 20(41):13–43, 2006.
dc.relationSalvador Sánchez-Alonso, Ramón Ovelar, and Miguel Ángel Sicilia. Estándares de elearning. In Ana Landeta Etxeberría, editor, Buenas Prácticas de e-learning. 2007.
dc.relationMark Sanderson. Test Collection Based Evaluation of Information Retrieval Systems. Foundations and Trends in Information Retrieval, 4(4):247–375, 2010.
dc.relationMark Sanderson and W. Bruce Croft. The history of information retrieval research. Proceedings of the IEEE, 100(Special Centennial Issue):1444–1451, 2012.
dc.relationCamila Sanz, Federico Zamberlan, Earth Erowid, Fire Erowid, and Enzo Tagliazucchi. The Experience Elicited by Hallucinogens Presents the Highest Similarity to Dreaming within a Large Database of Psychoactive Substance Reports. Frontiers in Neuroscience, 12, jan 2018.
dc.relationRobert R Saum. An Abridged History of Learning Objects. In Learning Objects for Instruction: Design and Evaluation. Idea Group Inc (IGI), 2007.
dc.relationNajmus Saher Shah. Review of Indexing Techniques Applied in Information Retrieval. Pakistan Journal of Engineering and Applied Sciences, 5(1):27–47, 2015.
dc.relationChien-wen Shen and Jung-tsung Ho. Technology-enhanced learning in higher education: A bibliometric analysis with latent semantic approach. Computers in Human Behavior, 104:106177, mar 2020.
dc.relationWen-Chung Shih and Shian-Shyong Tseng. A Knowledge-based Approach to Retrieving Teaching Materials for Context-aware Learning. Educational Technology & Society, 12(1):82–106, 2009.
dc.relationWen-Chung Shih, Shian-Shyong Tseng, and Chao-Tung Yang. Using taxonomic indexing trees to efficiently retrieve SCORM-compliant documents in e-learning grids. Educational Technology & Society, 11(2):206–226, 2008.
dc.relationWen-Chung Shih, Chao-Tung Yang, and Shian-Shyong Tseng. Ontology-based content organization and retrieval for SCORM-compliant teaching materials in data grids. Future Generation Computer Systems, 25(6):687–694, jun 2009.
dc.relationAmit Singhal. Modern Information Retrieval: A Brief Overview. Bulletin of the Ieee Computer Society Technical Committee on Data Engineering, 24(4):35–43, 2001.
dc.relationHamid Slimani, Nour-eddine El Faddouli, Samir Bennani, and N Amrous. Models of Digital Educational Resources Indexing and Dynamic User Profile Evolution. International Journal of Emerging Technologies in Learning (iJET), 11(1):26–32, 2016.
dc.relationBoutheina Smine, Rim Faiz, and Jean Pierre Desclés. A semantic annotation model for indexing and retrieving learning objects. Journal of Digital Information Management, 9(4):159–166, 2011.
dc.relationBoutheina Smine, Rim Faiz, and Jean Pierre Desclés. Extracting relevant learning objects using a semantic annotation method. In IEEE International Conference on Education and e-Learning Innovations, pages 1–6, Sousse, Tunisia, jul 2012. IEEE.
dc.relationBoutheina Smine, Rim Faiz, and Jean Pierre Desclés. Relevant learning objects extraction based on semantic annotation. International Journal of Metadata, Semantics and Ontologies, 8(1):13–27, 2013.
dc.relationRion Snow, Brendan O’Connor, Daniel Jurafsky, and Andrew Y Ng. Cheap and fast - but is it good? Evaluation non-expert annotiations for natural language tasks. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 254–263, 2008.
dc.relationSpyridon Stathopoulos and Theodore Kalamboukis. Applying latent semantic analysis to large-scale medical image databases. Computerized Medical Imaging and Graphics, 39:27– 34, 2015.
dc.relationDavid G Stork. An architecture supporting the collection and monitoring of data openly contributed over theWorldWideWeb. In Tenth IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, 2001. WET ICE 2001, number June, pages 380–385, 2001.
dc.relationDavid G Stork, Sand Hill Road, and Menlo Park. Character and Document Research in the Open Mind Initiative. In Fifth International Conference on Document Analysis and Recognition, pages 1–12, 1999.
dc.relationManuel Sucunuta, Guido Riofrio, and Edmundo Tovar. Information Retrieval Model for Open Educational Resources. In IEEE Global Engineering Education Conference (EDUCON), pages 1255–1261, Dubai, 2019. IEEE.
dc.relationValentina Tabares Morales, Néstor Duque Méndez, Paula Rodríguez Marín, Julián Moreno Cadavid, and Demetrio Ovalle Carranza. FROAC: Una Iniciativa Colombiana para la Integración de Repositorios de Objetos de Aprendizaje. Campus Virtuales, 4(1):108–117, 2015.
dc.relationValentina Tabares Morales, Néstor Darío Duque-Méndez, and Julián Moreno. Evaluación experimental de la calidad en la recuperación de objetos de aprendizaje desde repositorios remotos. In Congreso de Ambientes Virtuales Adaptativos CAVA 2011, Bogotá, 2011.
dc.relationValentina Tabares Morales, Néstor Darío Duque-Méndez, Julián Moreno, and Demetrio Ovalle. FROAC - Federación de Objetos de Aprendizaje Colombia. In Novena Conferencia Latinoamericana de Objetos y Tecnologías de Aprendizaje, Manizales, 2014. Universidad Nacional.
dc.relationAlice Tani, Leonardo Candela, and Donatella Castelli. Dealing with metadata quality: The legacy of digital library efforts. Information Processing & Management, 49(6):1194–1205, nov 2013.
dc.relationStefaan Ternier, David Massart, Alessandro Campi, Sam Guinea, Stefano Ceri, and Erik Duval. Interoperability for Searching Learning Object Repositories. The ProLearn Query Language. D-Lib Magazine, 14(1/2), 2008.
dc.relationThe Ohio State University. Choosing & Using Sources: A Guide to Academic Research. The Ohio State University, Columbus, 2016.
dc.relationGabriel H Tolosa and Fernando R A Bordignon. Introducción a la Recuperación de Información: conceptos, modelos y algoritmos. Universidad Nacional de Luján, Buenos Aires, 2008.
dc.relationJuan C. Valle-Lisboa and Eduardo Mizraji. The uncovering of hidden structures by Latent Semantic Analysis. Information Sciences, 177(19):4122–4147, oct 2007.
dc.relationHerbert Van de Sompel, Ryan Chute, and Patrick Hochstenbach. The aDORe federation architecture: digital repositories at scale. International Journal on Digital Libraries, 9(2):83– 100, 2008.
dc.relationCornelis Joost; Van Rijsbergen. Information Retrieval. University of Glasgow, second edition, 1979.
dc.relationJonas Vian, Ronaldo Lima Rocha Campos, Cecilia Estela Giuffra Palomino, and Ricardo Azambuja Silveira. A multiagent model for searching learning objects in heterogeneous set of repositories. In The 2011 11th IEEE International Conference on Advanced Learning Technologies, ICALT 2011, pages 48–52, Athens, GA, USA, 2011. IEEE Xplore.
dc.relationLuis von Ahn and Laura Dabbish. Labeling images with a computer game. In Proceedings of the 2004 conference on Human factors in computing systems - CHI ’04, pages 319–326, 2004.
dc.relationLuis von Ahn, Mihir Kedia, and Manuel Blum. Verbosity: a game for collecting commonsense facts. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 75–78, 2006.
dc.relationLuis von Ahn, Benjamin Maurer, Colin McMillen, David Abraham, and Manuel Blum. reCAPTCHA: human-based character recognition via Web security measures. Science, 321(5895):1465–1468, 2008.
dc.relationEllen M Voorhees. Variations in Relevance Judgements and the Measurement of Retrieval Effectiveness. Proceedings SIGIR’98, 36:315–323, 1998.
dc.relationEllen M Voorhees. The philosophy of information retrieval evaluation. In Evaluation of cross-language information retrieval systems, pages 355–37. Springer Berlin Heidelberg, 2002.
dc.relationEllenMVoorhees and Donna K Harman. TREC: Experiment and Evaluation in Information Retrieval. MIT Press, Cambridge, 2005.
dc.relationG Alan Wang, Jian Jiao, Alan S Abrahams, Weiguo Fan, and Zhongju Zhang. ExpertRank: A topic-aware expert finding algorithm for online knowledge communities. Decision Support Systems, 54:1442–1451, feb 2013.
dc.relationShouhong Wang. Ontology of Learning Objects Repository for Pedagogical Knowledge Sharing. Interdisciplinary Journal of E-Learning and Learning Objects, 4:1–12, 2008.
dc.relationTzone IWang, Kun Hua Tsai, Ming Che Lee, and Ti Kai Chiu. Personalized learning objects recommendation based on the semantic-aware discovery and the learner preference pattern. Educational Technology & Society, 10(3):84–105, 2007.
dc.relationAdam B. Weinberger, Hari Iyer, and Adam E. Green. Conscious Augmentation of Creative State Enhances "Real" Creativity in Open-Ended Analogical Reasoning. PLOS ONE, 11(3):e0150773, mar 2016.
dc.relationNeil Y Yen, Timothy K Shih, Louis R Chao, and Qun Jin. Ranking Metrics and Search Guidance for Learning Object Repository. IEEE Transactions on Learning Technologies, 3(3):250–264, 2010.
dc.relationTuncay Yigit, Ali Hakan Isik, and Murat Ince. Web-based learning object selection software using analytical hierarchy process. IET Software, 8(4):174–183, 2014.
dc.relationBurasakorn Yoosooka and VilasWuwongse. Linked Open Data for Learning Object Discovery: Adaptive e-Learning Systems. In International Conference on Intelligent Networking and Collaborative Systems, pages 60–67. Ieee, nov 2011.
dc.relationSima Zamani, Sai Peck Lee, Ramin Shokripour, and John Anvik. A noun-based approach to feature location using time-aware term-weighting. Information and Software Technology, 56(8):991–1011, aug 2014.
dc.relationMarkus Zanker and Markus Jessenitschnig. Case-studies on exploiting explicit customer requirements in recommender systems. User Modeling and User-Adapted Interaction, 19(1- 2 SPEC. ISS.):133–166, 2009.
dc.relationYuqun Zeng, Xusheng Liu, Yanshan Wang, Feichen Shen, Sijia Liu, Majid Rastegar- Mojarad, LiweiWang, and Hongfang Liu. Recommending Education Materials for Diabetic Questions Using Information Retrieval Approaches. Journal of Medical Internet Research, 19(10):e342, 2017.
dc.relationLeyla Zhuhadar and Olfa Nasraoui. Personalized cluster-based semantically enriched web search for e-learning. In The 2nd international workshop on Ontologies and nformation systems for the semantic web - ONISW ’08, pages 105–112, Napa Valley, USA, 2008. ACM.
dc.relationLeyla Zhuhadar and Olfa Nasraoui. Semantic information retrieval for personalized elearning. In IEEE International Conference on Tools with Artificial Intelligence, ICTAI, volume 1, pages 364–368, 2008.
dc.relationLeyla Zhuhadar and Olfa Nasraoui. A hybrid recommender system guided by semantic user profiles for search in the e-learning domain. Journal of Emerging Technologies in Web Intelligence, 2(4):272–281, 2010.
dc.relationLeyla Zhuhadar, Olfa Nasraoui, RobertWyatt, and Elizabeth Romero. Automated discovery, categorization and retrieval of personalized semantically enriched E-learning resources. In IEEE International Conference on Semantic Computing, pages 414–419, Berkeley, USA, 2009.
dc.relationClaus Zinn, Thorsten Trippel, Steve Kaminski, and Emanuel Dima. Crosswalking from CMDI to Dublin Core and MARC 21. In The International Conference on Language Resources and Evaluation, pages 2489–2495, Portorož, Slovenia, 2016.
dc.rightsReconocimiento 4.0 Internacional
dc.rightshttp://creativecommons.org/licenses/by/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleSistema híbrido para la búsqueda de objetos de aprendizaje textuales en repositorios, basado en metadatos y contenido
dc.typeTrabajo de grado - Doctorado


Este ítem pertenece a la siguiente institución