Recuperación de información: reflexiones epistémicas de una ciencia en su estado embrionario Artículos históricos Lic. Alberto Camaraza Monserrate La recuperación de información surgió como campo del conocimiento independiente en 1950. El contexto social y filosófico en que se enmarca tiene una singular influencia en la naciente ciencia y determina la orientación de sus presupuestos teóricos y prácticos. La relación bipolar sociedad-ciencia en este caso, provee un sentido y una guía que permite analizar y responder a incógnitas epistémicas inherentes al período de génesis de la recuperación de la información, así como a su posterior desarrollo. Palabras clave: Recuperación de la información, historia, epistemología. The information retrieval appeared in 1950 as a field of independent knowledge. Key words: Information retrieval, history, epistemology. Copyright: © ECIMED. Cita (Vancouver): Camaraza Monserrate A . ¿Cuáles son las raíces que provocan este nuevo estadio informacional? Fig. 1. Los Estados Unidos En busca de una definición
Quick Intro to RDF Quick Intro to RDF This is a really brief introduction to Resource Description Framework (RDF). You might also be interested in... For a more detailed look at RDF, see RDF in Depth on this site, which this page was based on.Two video introductions to the Semantic Web and RDF and RDFa by Manu Sporny are very good.Ian Davis's RDF Tutorial slides are also very good.There is also a Russian translation of this page. RDF is a method for expressing knowledge in a decentralized world and is the foundation of the Semantic Web, in which computer applications make use of distributed, structured information spread throughout the Web. The Big Picture RDF is a general method to decompose any type of knowledge into small pieces, with some rules about the semantics, or meaning, of those pieces. @prefix : < . The meaning is obvious. If you know XML, here's a brief comparison. But you don't have to use XML. Consider this second document of RDF: So why use RDF? RDF Defined Conclusion
bendiken/rdf - GitHub Graph database Database that uses mathematical graphs to store and search data Graph databases differ from graph compute engines. Graph databases are technologies that are translations of the relational online transaction processing (OLTP) databases. One study concluded that an RDBMS was "comparable" in performance to existing graph analysis engines at executing graph queries.[7] History[edit] Graph structures could be represented in network model databases from the late 1960s. Labeled graphs could be represented in graph databases from the mid-1980s, such as the Logical Data Model.[10][11] Commercial object databases (ODBMSs) emerged in the early 1990s. Several improvements to graph databases appeared in the early 1990s, accelerating in the late 1990s with endeavors to index web pages. In the mid-to-late 2000s, commercial graph databases with ACID guarantees such as Neo4j and Oracle Spatial and Graph became available. Background[edit] Graph databases portray the data as it is viewed conceptually.