Retrieval of bilingual Spanish-English information by means of a standard automatic translation system

This paper describes our participation in bilingual retrieval (queries in Spanish on documents in English), by means of an information retrieval system based on the vector model. The queries, formulated in Spanish, were translated into English by means of a commercial automatic translation system; the terms extracted from the resulting translations were filtered in order to get rid of empty words and then they were normalised by stemming. Results are poorer than those obtained through monolingual retrieval with the original queries in English slightly above 15%

Web Page Retrieval by Combining Evidence

The participation of the REINA Research Group in WebCLEF 2005 focused in the monolingual mixed task. Queries or topics are of two types: named and home pages. For both, we first perform a search by thematic contents; for the same query, we do a search in several elements of information from every page (title, some meta tags, anchor text) and then we combine the results. For queries about home pages, we try to detect using a method based in some keywords and their patterns of use. After, a re-rank of the results of the thematic contents retrieval is performed, based on Page-Rank and Centrality coeficients

La cibermetría en la recuperación de información en el Web

The exponential growth of web and distributed data characteristics, high volatility, unstructured data, redundant and highly heterogeneous, have introduced new problems in information retrieval processes. Therefore it is necessary to open new avenue of research that allow us to obtain good levels of accuracy. The papers are based on exploiting the hypertext features of the site is reaching great fame. The cybermetrics is providing many options for working with links and is offering some interesting options at this time, and much of the techniques used in the same may be useful in the processes of information retrieval on the web

Líneas de investigación en web mining, extracción automática de conocimiento y redes sociales

REINA's research lines in Social Network Analysis. Application to Topic Detection & Tracking

REINA at RepLab2013 Topic Detection Task: Community Detection

Social networks have become a large repository of comments which can extract multiple information. Twitter is one of the most widespread social networks and larger and is therefore an important source for detecting states of opinion, events and happenings before even the mainstream media. Topic detection is important to discover areas of interest that arise in the tweets. We have used classical systems for a similarity matrix and we have used community detection techniques. The results have been good and allows us to study new possibilities

Scientific culture: Public perception of Science and Technology in Spanish Wikipedia

The paper shows the relationship between Science and Technology Wikipedia articles (Spanish edition), using Social Network Analysis Techniques

Science and Technology in Social Networks: Twitter

Using the Internet as a primary source of scientific information search it is enhanced with the use of social networks. This requires a study and standardization of the content obtained in this way. Through the study of scientific information on twitter profiles could identify the main issues and quantity and quality of shared scientific information

Experiencias en la utilización de metodologías no presenciales de aprendizaje en la impartición de la asignatura Informática aplicada a la traducción

The experience in the use of e-learning to teach an official university course was shown in the text. The degree of utilization of e-learning tools was pointed out, and also the effort of students and teachers to achieve the skills of them was analyzed. It allows us to evaluate if the formative activity of the students using such systems needs big efforts of adjustment. It is an element of important valuation that can be applied in the learning of the Translation and Interpretation studies adapted to the EEES system

FORGE: An eLearning Framework for Remote Laboratory Experimentation on FIRE Testbed Infrastructure

The Forging Online Education through FIRE (FORGE) initiative provides educators and learners in higher education with access to world-class FIRE testbed infrastructure. FORGE supports experimentally driven research in an eLearning environment by complementing traditional classroom and online courses with interactive remote laboratory experiments. The project has achieved its objectives by defining and implementing a framework called FORGEBox. This framework offers the methodology, environment, tools and resources to support the creation of HTML-based online educational material capable accessing virtualized and physical FIRE testbed infrastruc- ture easily. FORGEBox also captures valuable quantitative and qualitative learning analytic information using questionnaires and Learning Analytics that can help optimise and support student learning. To date, FORGE has produced courses covering a wide range of networking and communication domains. These are freely available from FORGEBox.eu and have resulted in over 24,000 experiments undertaken by more than 1,800 students across 10 countries worldwide. This work has shown that the use of remote high- performance testbed facilities for hands-on remote experimentation can have a valuable impact on the learning experience for both educators and learners. Additionally, certain challenges in developing FIRE-based courseware have been identified, which has led to a set of recommendations in order to support the use of FIRE facilities for teaching and learning purposes

Organización Automática del Conocimiento: la geografía en la Wikipedia

The Information Technologies drive an unprecedented growth of information, which raises the problem of the organization of it. As it is digital information, it is possible to approach her organization through automated procedures. On the other hand, Network Analysis Techniques are a powerful tool that allows us to model different phenomena and then apply automatic techniques. In this paper we describe the application of these Network Analysis Techniques to model and process an important number of documents, such as the one constituted by Wikipedia articles. The subsequent application of community detection algorithms allows grouping the articles based on their hyperlinks and their thematic affinity. This work focuses, after having applied these techniques, on the geographical relationship of the articles, on their network communities and the connections between them.Las tecnologías de la información propician un crecimiento sin precedentes de la información, lo cual plantea el problema de la organización de ésta. Al tratarse de información digital es posible abordar su organización mediante procedimientos automatizados. De otro lado, las Técnicas de Análisis de Redes son un poderoso instrumento que permite modelar diferentes fenómenos y aplicar después técnicas automáticas. En este trabajo se describe la aplicación de estas Técnicas de Análisis de Redes para modelar y procesar una masa importante de documentos, como la constituida por los artículos de la Wikipedia. La aplicación posterior de algoritmos de detección de comunidades permite agrupar los artículos en función de sus hiperenlaces y su afinidad temática. Este trabajo se centra, después de haber aplicado estas técnicas, en la relación geográfica de los artículos, en sus comunidades de red y las conexiones entre ellas