Research-based knowledge to corporate businesses: the Danish experience
DOI:
https://doi.org/10.22201/dgb.0187750xp.2014.2.63Palabras clave:
sme, Denmark, research-based, strategy, healthcareResumen
One of the goals in the Danish Government’s strategy for growth in Denmark is to promote the awareness, access and use of research-based knowledge to citizens and institutions, both private and public. In gaining better use of research-based knowledge, Denmark’s chances of being able to play a prominent role as a knowledge society, both nationally and internationally, will substantially increase. To transform the strategy into practice Denmark’s Electronic Research Library, deff, has been created. In this article business consultant of deff, Anders Mejlbjerg, describes how deff is working to expand the awareness of research-based knowledge to various public institutions and to small and medium-sized private enterprises, known as SMEs.
Descargas
Citas
Abbott, Dean. Introduction to Text Mining [en línea]: Virtual Data Intensive Summer School, July 10, 2013. <http://www.vscse.org/summerschool/2013/Abbott. pdf> [Consulta: 17 junio 2014].
Beath, Cynthia, Becerra-Fernández, Irma, Ross, Jean, Short, James. El valor de la explosión de la in- formación [en línea]. iq Intelligence quarterly:diario de análisis avanzado, 2013, p. 8-11.
Belsky, Gary. Why Text Mining May Be The Next Big Thing [en línea]. Technology & Media, 20 de Marzo de 2012. <http://business.time.com/2012/03/20/ why-text-mining-may-be-the-next-big-thing/>
Digital Universe [en línea]. EMC2. <http://www.emc. com/leadership/programs/digital-universe.htm> [Consulta: 22 octubre 2013].
Extraction des informations et des connaissances [en línea]. <http://touriaelouahabi.wordpress.com/text-mining/ principes-et-concepts-text-mining/> [Consulta: 17 junio 2014].
Fung, Benjamin C.M., Wang, Ke, Ester, Martin. B. Hierarchical Document Clustering Using Frequent Itemsets [en línea]. <http://epubs.siam.org/doi/ pdf/10.1137/1.9781611972733.6> [Consulta: 14 julio 2010].
Fuzzy cluster analysis. Frank Höppner y otros. New York: J. Wiley, c1999. 289 p.
Gupta, Vishal, Lehal, Gurpreet S. A Survey of Text Mining Techniques and Applications. Journal of emerging technologies in Web intelligence, August 2009, vol. 1, no. 1, p. 60-76.
Haykin, Simon. Neuronal Networks: A Comprehensive Foundation. New York: Macmillan, 1994.
Journal Selection for medline Indexing at NLM [en línea]. U.S. National Library of Medicine. <http://www.nlm.nih. gov/pubs/factsheets/j_sel_faq.html#a15> [Consulta: 22 octubre 2013].
Krallinger, Martin. Current trends in biomedical text mi- ning: chemicals, drugs and mutations [video]. Madrid, España: S. N. Centre, 2013. Jornadas Mavir, (19 de noviembre de 2013).
Marín, Maria José, Rico, Eva, Juli, Pascual. Data mining en relación a la documentación periodística [en línea]. <http://personales.upv.es/ccarrasc/doc/2003-2004/ DMPeriodistico/TREBALLSRP.htm> [Consulta: 2011].
The National Centre for Text Mining [en línea]. [Consulta: 20 marzo 2014].
Neural Networks Design. Martin T. Hagan, Howard B. Demuth, Mark H. Beale, Orlando de Jesús. e.u.a: PWS Publishing, 1996.
Noorden, Richard Van. Elsevier opens its papers to text-mining. Nature, 3 febrero 2014, vol. 506, no. 7486.
Rauber, Andreas, Merkl, Dieter. Text Mining in the somlib Digital Library System: The Representation of Topics and Genres. Applied Intelligence, 2003, vol. 18, p. 271-293.
Salton, Gerard. Automatic text processing: The transformation, analysis, and retrieval of information by computer. Reading, Massachusetts: Addison Wesley, c1989. 530 p.
Sánchez, D., Martín-Bautista, M. Un enfoque deductivo para la minería de texto [en línea]. [06 febrero 2014].
Sentiment analysis [en línea]. Wikipedia, The Free Encyclopedia. <http://en.wikipedia.org/w/index.php?title=Sentiment_ analysis&oldid=625073725> [Consulta: 18 septiembre, 2014].
Smalhaiser, Neil, Swanson, D. Assessing a gap in the bio- medical literature: magnesium deficiency and neurologic disease. Neuroscience research communications, 1994, vol. 15, p. 1-9.
Sukanya, M., Biruntha, S. Techniques on Text Mining. En: ieee International Conference on Advanced Communi- cation Control and Computing Technologies (ICACCCT), 23- 25 Aug., 2012. Ramanathapuram: IEEE, 2012.
Survey of Text Mining ii: Clustering, Classification and Retrieval. Michael W. Berry, Malu Castellanos, editors. Lon- don: Springer, 2008. 240 p.
Swanson, Don R. Complementary structures in disjoint science literatures. En: Proceeding SIGIR ’91, Proceedings of the 14th Annual International ACM/SIGIR Conference on Re- search and development in information retrieval. New York: ACM, c1991, p. 280-289.
Tapping the Power of Text Mining. Weiguo Fan, Linda Wallace, Stephanie Rich, Zhongju Zhang. Communication of the ACM, September 2006, vol. 49, no. 9, p. 76-82.
Text mining: A new frontier for lossless compression. Ian H. Witten, Zane Bray, Malika Mahoui, Bill Teahan. En: Data Compression Conference, 1999. Proceedings. dcc ‘99. Snowbird: IEEE, 1999, p. 198-207.
Text mining in a digital library. Ian H. Witten, Katherine J. Don, Michael Dewsnip, Valentin Tablan. International Journal on Digital Libraries, 2003, vol. 4, no. 1, p. 56-59.
Value and benefits of text mining [en línea]. Jisc.
Yanliang Qi, Zhang, Yang, Song, Min. Text Mining for Bioinformatics: State of the Art Review. En: Conference on Computer Science and Information Technology, 2009, ICCSIT 2009, 2nd ieee International Conference on Computer Science and Information
Technology, 8-11 Aug., 2009. Beijing: IEEE, 2009.
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Descargar el formato de Cesión de derechos en formato PDF:
Formato de Cesión de derechos
Imprímalo y una vez que lo haya firmado envíenoslo vía fax o por correo a:
Revista Biblioteca Universitaria:
Dirección General de Bibliotecas y Servicios Digitales de Información de la UNAM
Departamento de Publicaciones
Edificio de la Biblioteca Central, 11o Piso,
Circuito Interior, Ciudad Universitaria, 04510 México, D.F.
Tel 5622-1616,
Fax: 5622-1601,
