Fénix: a flexible information exchange data model for natural language processing

In this paper we describe Fénix, a data model for exchanging information between Natural Language Processing applications. The format proposed is intended to be flexible enough to cover both current and future data structures employed in the field of Computational Linguistics. The Fénix architecture is divided into four separate layers: conceptual, logical, persistence and physical. This division provides a simple interface to abstract the users from low-level implementation details, such as programming languages and data storage employed, allowing them to focus in the concepts and processes to be modelled. The Fénix architecture is accompanied by a set of programming libraries to facilitate the access and manipulation of the structures created in this framework. We will also show how this architecture has been already successfully applied in different research projects.

From constituents to syntax-oriented dependencies

This paper describes the automatic process of building a dependency annotated corpus based on Ancora constituent structures. The Ancora corpus already has a dependency structure information layer, but the new annotated data applies a purely syntactic orientation and offers in this way a new resource to the linguistic research community. The paper details the process of reannotating the corpus, the linguistic criteria used and the obtained results.

Automatic prediction of emotions from text in Spanish for expressive speech synthesis in the chat domain

This paper describes a module for the prediction of emotions in text chats in Spanish, oriented to its use in specific-domain text-to-speech systems. A general overview of the system is given, and the results of some evaluations carried out with two corpora of real chat messages are described. These results seem to indicate that this system offers a performance similar to other systems described in the literature, for a more complex task than other systems (identification of emotions and emotional intensity in the chat domain).

Más allá de la búsqueda

Trasparencias de la asignatura BIIW sobre Sistemas de Recuperación de Información.

Catálogo de MySQL

Trasparencias y material para la clase sobre Catálogo de MySQL.

Ejercicios Catálogo MySQL

Ejercicios sobre el catálogo de MySQL

Motores MySQL

Descripción de los distintos tipos de motores MySQL.

COMPENDIUM: a text summarisation tool for generating summaries of multiple purposes, domains, and genres

In this paper, we present a Text Summarisation tool, compendium, capable of generating the most common types of summaries. Regarding the input, single- and multi-document summaries can be produced; as the output, the summaries can be extractive or abstractive-oriented; and finally, concerning their purpose, the summaries can be generic, query-focused, or sentiment-based. The proposed architecture for compendium is divided in various stages, making a distinction between core and additional stages. The former constitute the backbone of the tool and are common for the generation of any type of summary, whereas the latter are used for enhancing the capabilities of the tool. The main contributions of compendium with respect to the state-of-the-art summarisation systems are that (i) it specifically deals with the problem of redundancy, by means of textual entailment; (ii) it combines statistical and cognitive-based techniques for determining relevant content; and (iii) it proposes an abstractive-oriented approach for facing the challenge of abstractive summarisation. The evaluation performed in different domains and textual genres, comprising traditional texts, as well as texts extracted from the Web 2.0, shows that compendium is very competitive and appropriate to be used as a tool for generating summaries.

The role of statistical and semantic features in single-document extractive summarization

This paper reports on the further results of the ongoing research analyzing the impact of a range of commonly used statistical and semantic features in the context of extractive text summarization. The features experimented with include word frequency, inverse sentence and term frequencies, stopwords filtering, word senses, resolved anaphora and textual entailment. The obtained results demonstrate the relative importance of each feature and the limitations of the tools available. It has been shown that the inverse sentence frequency combined with the term frequency yields almost the same results as the latter combined with stopwords filtering that in its turn proved to be a highly competitive baseline. To improve the suboptimal results of anaphora resolution, the system was extended with the second anaphora resolution module. The present paper also describes the first attempts of the internal document data representation.

Población de la Base de Datos

Presentación de la sesión de prácticas sobre Población de Base de Datos automática.

Gestión de índices

¿Qué es un índice? ¿Cómo se estructura? ¿Cómo se almacena la información en una tabla? Esta presentación describe cada uno de estos aspectos y nos da consejos de cómo optimizar las tablas, índices y consultas.

UniMOOC: trabajo colaborativo e innovación educativa

Desde que en 2007-2008 se pusiera en práctica por vez primera la metodología MOOC (Cursos Abierto Online y Masivo), el proceso de innovación educativa se ha acelerado gracias a iniciativas tan potentes como Udacity, Coursera o MITx. Su impacto potencial en el mundo universitario y de la enseñanza en general han llevado a replantear el futuro de la educación a gran escala. El éxito de los MOOCs ha sido exponencial, desde los 50 matriculados en el curso de David Wiley sobre Educación Abierta (año 2007) hasta los más de 2.5 millones de inscritos en Coursera en 2012. Hasta este punto, se ha vivido un proceso de reafirmación y apuesta por el modelo tanto por parte de la sociedad como de las instituciones educativas de mayor prestigio en el mundo. A pesar de encontrarnos aun en un marco metodológico claramente experimental, ya nadie puede negar el éxito cosechado por los MOOCs y el previsible futuro que parece aguardarles. En este documento se presenta el caso UniMOOC como el primer MOOC para emprendedores en español, un proyecto que comienza a definirse en la primavera de 2012, y que cuenta con una proyección orientada a alcanzar los 60.000 alumnos en su primera edición.

Materials docents de Fonaments d'Informàtica en Enginyeria de l'Edificació

Materials docents de Fonaments d'Informàtica en Enginyeria de l'Edificació

Towards the Design of a Textile Chemical Ontology

The main goal of this paper is to present the initial version of a Textile Chemical Ontology, to be used by textile professionals with the purpose of conceptualising and representing the banned and harmful chemical substances that are forbidden in this domain. After analysing different methodologies and determining that “Methontology” is the most appropriate for the purposes, this methodology is explored and applied to the domain. In this manner, an initial set of concepts are defined, together with their hierarchy and the relationships between them. This paper shows the benefits of using the ontology through a real use case in the context of Information Retrieval. The potentiality of the proposed ontology in this preliminary evaluation encourages extending the ontology with a higher number of concepts and relationships, and validating it within other Natural Language Processing applications.

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.