Mostrar el registro sencillo del ítem

Aplicación de técnicas de minería de datos para extraer información de fuentes organizacionales, en la educación de requisitos

dc.contributor.advisorManrique Losada, Bell
dc.contributor.advisorQuintero, Juan Bernardo
dc.contributor.authorMorales Pérez, Juan Sebastián
dc.coverage.spatialLat: 06 15 00 N  degrees minutes  Lat: 6.2500  decimal degreesLong: 075 36 00 W  degrees minutes  Long: -75.6000  decimal degrees
dc.date.accessioned2021-04-20T18:33:39Z
dc.date.available2021-04-20T18:33:39Z
dc.date.created2020-04-27
dc.identifier.otherT 0002 2020
dc.identifier.urihttp://hdl.handle.net/11407/6254
dc.descriptionLa ingeniería de requisitos tiene un papel importante en el éxito de un proyecto de software (Javed, 2010) a través de la educción, especificación, modelado y análisis de las necesidades planteadas por los Stakeholders sobre un producto de software (Unterkalmsteiner et al., 2015). La educación de requisitos dentro de la ingeniería de requisitos abarca el aprendizaje y la comprensión de las necesidades de los usuarios y los Stakeholders del proyecto, en aras de transmitirlas de una manera clara y concisa a los desarrolladores de software (Zowghi & Coulin, 2005) . Sin embargo, es importante resaltar que un usuario se centra en los RF del producto de software, dejando por fuera los RNF que imponen restricciones operativas en diferentes aspectos del comportamiento del sistema, según Mahmoud y Williams (2016).
dc.format.extentp. 1-99
dc.format.mediumElectrónico
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0
dc.titleAplicación de técnicas de minería de datos para extraer información de fuentes organizacionales, en la educación de requisitos
dc.rights.accessrightsinfo:eurepo/semantics/openAccess
dc.publisher.programMaestría en Ingeniería de Software
dc.subject.lembAlgoritmos
dc.subject.lembIngeniería de software
dc.subject.lembLenguajes naturales
dc.subject.lembLingüística computacional
dc.subject.lembMinería de datos
dc.subject.lembProcesamiento de datos
dc.relation.citationstartpage1
dc.relation.citationendpage99
dc.audienceComunidad Universidad de Medellín
dc.publisher.facultyFacultad de Ingenierías
dc.publisher.placeMedellín
dc.relation.referencesAlvarez, J. L., Mata, J., & Riquelme, J. C. (2004). Data mining for the management of software development process. International Journal of Software Engineering and Knowledge Engineering, 14(6), 665–695. Retrieved from http://dx.doi.org/10.1142/S0218194004001841spa
dc.relation.referencesAlzu’Bi, S., Hawashin, B., Eibes, M., & Al-Ayyoub, M. (2018). A Novel Recommender System Based on Apriori Algorithm for Requirements Engineering. 2018 5th International Conference on Social Networks Analysis, Management and Security, SNAMS 2018, 323–327. https://doi.org/10.1109/SNAMS.2018.8554909spa
dc.relation.referencesArora, P. (2014). Application of Data Mining Techniques on Software Engineering Data for Software Quality, 3(6), 6722–6725.spa
dc.relation.referencesAysolmaz, B., Leopold, H., Reijers, H. A., & Demirörs, O. (2017). A semi-automated approach for generating natural language requirements documents based on business process models. Information and Software Technology, 0, 1–16. https://doi.org/10.1016/j.infsof.2017.08.009spa
dc.relation.referencesBaudier, F. (2000). DATA MINING TECHNIQUES AND APPLICATIONS. Sante Publique, 12(SPEC. ISS.), 5–10.spa
dc.relation.referencesBekkerman, R., El-Yaniv, R., Tishby, N., & Winter, Y. (2003). Distributional Word Clusters vs. Words for Text Categorization. Journal of Machine Learning Research, 3(7–8), 1183–1208. Retrieved from http://www.crossref.org/jmlr_DOI.htmlspa
dc.relation.referencesCasamayor, A., Godoy, D., & Campo, M. (2010). Identification of non-functional requirements in textual specifications: A semi-supervised learning approach. Information and Software Technology, 52(4), 436–445. https://doi.org/10.1016/j.infsof.2009.10.010spa
dc.relation.referencesChopra, A., Prashar, A., & Chandresh, S. (2013). Natural Language Processing. International Journal of Technology Enhancements and Emerging Engineering Research, 1(4), 131–134.spa
dc.relation.referencesCleland-Huang, J., Settimi, R., Zou, X., & Solc, P. (2006). The Detection and Classification of Non-Functional Requirements with Application to Early Aspects Bayesian Forecasting View project Architectually Significant Requirements View project The Detection and Classification of Non-Functional Requirements with A. https://doi.org/10.1109/RE.2006.65spa
dc.relation.referencesCleland-Huang, J., Settimi, R., Zou, X., & Sole, P. (2006). The detection and classification of non-functional requirements with application to early aspects. Proceedings of the IEEE International Conference on Requirements Engineering, 36–45. https://doi.org/10.1109/RE.2006.65spa
dc.relation.referencesDas, M. A., Das, M. K., & Puthal, P. B. (2011). Improving Software Development Process through Data Mining Techniques Embedding Alitheia Core Tool, 2(2), 629–632.spa
dc.relation.referencesDeerwester, S., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990). Indexing by Latent Semantic Analysis, 34. https://doi.org/10.1017/CBO9781107415324.004spa
dc.relation.referencesDemmel, J., & Kahan, W. (2005). Accurate Singular Values of Bidiagonal Matrices. SIAM Journal on Scientific and Statistical Computing, 11(5), 873–912. https://doi.org/10.1137/0911052spa
dc.relation.referencesFayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From Data Mining to Knowledge Discovery in Databases. AI Magazine, 17(3), 37. https://doi.org/10.1609/aimag.v17i3.1230spa
dc.relation.referencesGénova, G., Fuentes, J. M., Llorens, J., Hurtado, O., & Moreno, V. (2013). A framework to measure and improve the quality of textual requirements. Requirements Engineering, 18(1), 25–41. https://doi.org/10.1007/s00766-011-0134-zspa
dc.relation.referencesGera, M., & Goel, S. (2015). Data Mining - Techniques, Methods and Algorithms: A Review on Tools and their Validity. International Journal of Computer Applications, 113(18), 22–29. https://doi.org/10.5120/19926-2042spa
dc.relation.referencesGessler, N., & Shrivastava, A. (2015). Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data. (Kelly Talbot, Ed.). Indianapolis: John Wiley & Sons, Inc.spa
dc.relation.referencesGorunescu, F. (2011a). Data Mining: Concepts and Techniques. Elsevier (Vol. 12). https://doi.org/10.1007/978-3-642-19721-5spa
dc.relation.referencesGorunescu, F. (2011b). Introduction to data mining. Data Mining: Concepts, Models and Techniques, (August), 1–43. https://doi.org/10.1007/978-3-642-19721-5spa
dc.relation.referencesHenderson, H. (2003). Encyclopedia of Computer Science and Technology. Reference Reviews incorporating ASLIB Book Guide (Vol. 17). https://doi.org/10.1108/09504120310503999spa
dc.relation.referencesHevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly: Management Information Systems, 28(1).spa
dc.relation.referencesIşman, A. (2012). Technology and technique: An educational perspective. Turkish Online Journal of Educational Technology, 11(2), 207–213. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-84859405558&partnerID=40&md5=36cfa397738db04645f44a8a577c3cf6spa
dc.relation.referencesJaved, B. (2010). Process Support for Requirements Engineering Activities in Global Software Development: A Literature Based Evaluation. Engineering, 6.spa
dc.relation.referencesJiawei, H., Micheline, K., & Jian, P. (2012). Dm Concepts and Techniques Preface and Introduction.spa
dc.relation.referencesJoseph, S. R., Hlomani, H., & Letsholo, K. (2018). Data Mining Algorithms: An Overview. International Journal of Computers & Technology, 15(6), 6806–6813. https://doi.org/10.24297/ijct.v15i6.1615spa
dc.relation.referencesKosterec, M. (2016). Methods of conceptual analysis. Filozofia, 71(3), 220–230.spa
dc.relation.referencesKumar, A., Rath, H. K., Nadaf, S. M., & Simha, A. (2015). Novel Self-learning based Crawling and Data Mining for Automatic Information Extraction. International Conference on Advances in Computing, Communications and Informatics (ICACCI), 7.spa
dc.relation.referencesKurtanovic, Z., & Maalej, W. (2017). Automatically Classifying Functional and Non-functional Requirements Using Supervised Machine Learning. Proceedings - 2017 IEEE 25th International Requirements Engineering Conference, RE 2017, 490–495. https://doi.org/10.1109/RE.2017.82spa
dc.relation.referencesLandhäußer, M., Körner, S. J., & Tichy, W. F. (2014). From requirements to UML models and back: How automatic processing of text can support requirements engineering. Software Quality Journal, 22(1), 121–149. https://doi.org/10.1007/s11219-013-9210-6spa
dc.relation.referencesLiang, W., Qian, W., Wu, Y., Peng, X., & Zhao, W. (2015). Mining Context-Aware User Requirements from Crowd Contributed Mobile Data. Internetware, 132–140. https://doi.org/10.1145/2875913.2875933spa
dc.relation.referencesMahmoud, A., & Williams, G. (2016). Detecting, classifying, and tracing non-functional software requirements. Requirements Engineering, 21(3), 357–381. https://doi.org/10.1007/s00766-016-0252-8spa
dc.relation.referencesMarín, D. (2019). EXTRACCION DE INFORMACIÓN DE DOCUMENTOS DE NEGOCIO ESCRITOS EN LENGUAJE NATURAL EN IDIOMA ESPAÑOL Y SU REPRESENTACIÓN EN UN MODELO CONCEPTUAL, 1, 72.spa
dc.relation.referencesMenendez, V. ., & Castellanos, M. . (2008). Software Process Engineering Metamodel (SPEM). Revista Latinoamericana de Ingenieria de Software, 3(2), 92–100. https://doi.org/10.18294/relais.2015.92-100spa
dc.relation.referencesMinku, L. L., Mendes, E., & Turhan, B. (2016). Data mining for software engineering and humans in the loop. Progress in Artificial Intelligence, 5(4), 307–314. https://doi.org/10.1007/s13748-016-0092-2spa
dc.relation.referencesNaz, H., Motla, Y. H., Asghar, S., Ahmed, M., Shabbir Hassan, M., Mukhtar, M., & Javed, A. (2013). A systematic approach for web engineering practices by integrating data mining technique with requirement change management. 2013 IEEE 4th International Conference on Software Engineering and Service Science, 373–376. https://doi.org/10.1109/ICSESS.2013.6615327spa
dc.relation.referencesNinaus, G., Felfernig, A., Stettinger, M., Reiterer, S., Leitner, G., Weninger, L., & Schanil, W. (2014). INTELLIREQ: Intelligent Techniques for Software Requirements Engineering. European Conference on Artificial Intelligence, 1161–1166. https://doi.org/10.3233/978-1-61499-419-0-1161spa
dc.relation.referencesRaharja, I. M. S., & Siahaan, D. O. (2019). Classification of non-functional requirements using fuzzy similarity KNN Based on ISO / IEC 25010. Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019, 264–269. https://doi.org/10.1109/ICTS.2019.8850944spa
dc.relation.referencesRehman, N. (2017). Data Mining Techniques Methods Algorithms and Tools. International Journal of Computer Science and Mobile Computing, 6(7), 227–231. Retrieved from www.ijcsmc.comspa
dc.relation.referencesSeaver, N. (2019). Knowing Algorithms. DigitalSTS, (February), 412–422. https://doi.org/10.2307/j.ctvc77mp9.30spa
dc.relation.referencesSlankas, J., & Williams, L. (2013). Automated extraction of non-functional requirements in available documentation. 2013 1st International Workshop on Natural Language Analysis in Software Engineering, NaturaLiSE 2013 - Proceedings, 9–16. https://doi.org/10.1109/NAturaLiSE.2013.6611715spa
dc.relation.referencesSlonim, N., & Tishby, N. (2000). Document Clustering using Word Clusters via the Information Bottleneck Method. Neural Computation, 208–215.spa
dc.relation.referencesSommerville, I. (2010). Software Engineering. Software Engineering. https://doi.org/10.1111/j.1365-2362.2005.01463.xspa
dc.relation.referencesSupakkul, S., & Chung, L. (2010). Visualizing non-functional requirements patterns. 2010 5th International Workshop on Requirements Engineering Visualization, REV 2010, 25–34. https://doi.org/10.1109/REV.2010.5625663spa
dc.relation.referencesToussaint, M. B. & Y. (1995). Artificial intelligence tools for software engineering: Processing natural language requirements. Communications, 11, 16.spa
dc.relation.referencesUnterkalmsteiner, M., Gorschek, T., Feldt, R., & Klotins, E. (2015). Assessing requirements engineering and software test alignment - Five case studies. Journal of Systems and Software, 109, 62–77. https://doi.org/10.1016/j.jss.2015.07.018spa
dc.relation.referencesXie, T., Thummalapenta, S., Lo, D., & Liu, C. (2009). Data Mining for Software Engineering. Computer, 42(August), 55–62. https://doi.org/10.1109/MC.2009.256spa
dc.relation.referencesYin, B., & Jin, Z. (2012). Extending the problem frames approach for capturing non-functional requirements. Proceedings - 2012 IEEE/ACIS 11th International Conference on Computer and Information Science, ICIS 2012, 432–437. https://doi.org/10.1109/ICIS.2012.47spa
dc.relation.referencesZhang, W., Yang, Y., Wang, Q., & Shu, F. (2011). An empirical study on classification of non-functional requirements. SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering, 444–449. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-84862953188&partnerID=40&md5=5873bd4a0a3ca9752a1ffee19cd758baspa
dc.relation.referencesZowghi, D., & Coulin, C. (2005). Requirements elicitation: A survey of techniques, approaches, and tools. Engineering and Managing Software Requirements, 19–46. https://doi.org/10.1007/3-540-28244-0_2spa
dc.rights.creativecommonsAttribution-NonCommercial-ShareAlike 4.0 International
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.type.localTesis de Maestría
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.description.degreenameMagíster en Ingeniería de Software
dc.description.degreelevelMaestría
dc.publisher.grantorUniversidad de Medellín


Ficheros en el ítem

Thumbnail
Nombre:
T_MIS_435.pdf
Tamaño:
2.957Mb
Formato:
PDF
Ver/

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

Mostrar el registro sencillo del ítem

Attribution-NonCommercial-ShareAlike 4.0 International
Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-ShareAlike 4.0 International