Evaluation of pronoun resolution algorithm for Spanish dialogues

In this paper, we present an algorithm for anaphora resolution in Spanish dialogues and an evaluation of the algorithm for pronominal anaphora. The proposed algorithm uses both linguistic information and the structure of the dialogue to find the antecedent of the anaphors. The system has been evaluated on ten dialogues.

Evaluating EmotiBlog robustness for sentiment analysis tasks

EmotiBlog is a corpus labelled with the homonymous annotation schema designed for detecting subjectivity in the new textual genres. Preliminary research demonstrated its relevance as a Machine Learning resource to detect opinionated data. In this paper we compare EmotiBlog with the JRC corpus in order to check the EmotiBlog robustness of annotation. For this research we concentrate on its coarse-grained labels. We carry out a deep ML experimentation also with the inclusion of lexical resources. The results obtained show a similarity with the ones obtained with the JRC demonstrating the EmotiBlog validity as a resource for the SA task.

Paralelismo sintáctico-semántico para el tratamiento de elementos extrapuestos en textos no restringidos

En este artículo presentamos un método basado en la teoría del paralelismo para la identificación y resolución de elementos extrapuestos en textos no restringidos. Esta teoría de paralelismo está basada en (Palomar 96) y se amplía con el desarrollo de técnicas de análisis parcial –en las que se estudia las partes relevantes del texto- que facilitan la resolución de los fenómenos lingüísticos. Nos basaremos en los programas Datalog extendidos (Dahl 94) (Dahl 95) como herramienta para la definición e implementación de gramáticas. Éstas no están basadas en reglas gramaticales sino en la detección de información relevante, relajando el proceso y ampliando el conjunto potencial de textos analizables.

EmotiBlog: towards a finer-grained sentiment analysis and its application to opinion mining

Comunicación presentada en las IV Jornadas TIMM, Torres (Jaén), 7-8 abril 2011.

Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.

Towards a unified framework for opinion retrieval, mining and summarization

The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained show the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.

Event ordering through temporal expression resolution

In this paper a multilingual method for event ordering based on temporal expression resolution is presented. This method has been implemented through the TERSEO system which consists of three main units: temporal expression recognizing, resolution of the coreference introduced by these expressions, and event ordering. By means of this system, chronological information related to events can be extracted from documental databases. This information is automatically added to the documental database in order to allow its use by question answering systems in those cases referring to temporality. The system has been evaluated obtaining results of 91 % precision and 71 % recall. For this, a blind evaluation process has been developed guaranteing a reliable annotation process that was measured through the kappa factor.

Architecture of a multi-modal dialogue system oriented to multilingual question-answering

In this paper, a proposal of a multi-modal dialogue system oriented to multilingual question-answering is presented. This system includes the following ways of access: voice, text, avatar, gestures and signs language. The proposal is oriented to the question-answering task as a user interaction mechanism. The proposal here presented is in the first stages of its development phase and the architecture is presented for the first time on the base of the experiences in question-answering and dialogues previously developed. The main objective of this research work is the development of a solid platform that will permit the modular integration of the proposed architecture.

The University of Alicante at CL-SR Track

In this paper, the new features that IR-n system applies on the topic processing for CL-SR are described. This set of features are based on applying logic forms to topics with the aim of incrementing the weight of topic terms according to a set of syntactic rules.

Applying logic forms and statistical methods to CL-SR performance

This paper describes a CL-SR system that employs two different techniques: the first one is based on NLP rules that consist on applying logic forms to the topic processing while the second one basically consists on applying the IR-n statistical search engine to the spoken document collection. The application of logic forms to the topics allows to increase the weight of topic terms according to a set of syntactic rules. Thus, the weights of the topic terms are used by IR-n system in the information retrieval process.

AliQAn, Spanish QA system at multilingual QA@CLEF-2008

Comunicación presentada en Cross-Language Evaluation Forum (CLEF 2008), Aarhus, Denmark, September 17-19, 2008.

TEXT-MESS: Intelligent, Interactive and Multilingual Text Mining based on Human Language Technologies, TIN2006-15265-C06

The goal of the project is to analyze, experiment, and develop intelligent, interactive and multilingual Text Mining technologies, as a key element of the next generation of search engines, systems with the capacity to find "the need behind the query". This new generation will provide specialized services and interfaces according to the search domain and type of information needed. Moreover, it will integrate textual search (websites) and multimedia search (images, audio, video), it will be able to find and organize information, rather than generating ranked lists of websites.

Using IR-n for information retrieval of Genomics Track

Nowadays there is a big amount of biomedical literature which uses complex nouns and acronyms of biological entities thus complicating the task of retrieval specific information. The Genomics Track works for this goal and this paper describes the approach we used to take part of this track of TREC 2007. As this is the first time we participate in this track, we configurated a new system consisting of the following diferenciated parts: preprocessing, passage generation, document retrieval and passage (with the answer) extraction. We want to call special attention to the textual retrieval system used, which was developed by the University of Alicante. Adapting the resources for the propouse, our system has obtained precision results over the mean and median average of the 66 official runs for the Document, Aspect and Passage2 MAP; and in the case of Passage MAP we get nearly the median and mean value. We want to emphasize we have obtained these results without incorporating specific information about the domain of the track. For the future, we would like to further develop our system in this direction.

La gestión de la innovación en la administración local: algunos resultados empíricos

La introducción de innovaciones ha sido una herramienta básica que los gobiernos de distintos países y administraciones han usado para mejorar los servicios públicos. Las presiones financieras, los controles burocráticos y las demandas de mejores servicios por parte de los ciudadanos hacen a la vez difícil y, por otra parte, necesaria a la innovación, como la única vía de responder eficientemente a las demandas ciudadanas. En el presente trabajo analizamos el nivel de implantación de innovaciones en los ayuntamientos españoles así como qué tipo de innovaciones son más comúnmente utilizadas. Además contrastamos la relación entre el comportamiento innovador y el tamaño organizativo. Por otra parte, puesto que las innovaciones deben darse no cómo un fenómeno aislado, sino como parte de la estrategia corporativa, contrastaremos el comportamiento innovador de los ayuntamientos analizados con sus tipologías o perfiles estratégicos.

IARG-AnCora: anotación de los corpus AnCora con argumentos implícitos

IARG-AnCora tiene como objetivo la anotación con papeles temáticos de los argumentos implícitos de las nominalizaciones deverbales en el corpus AnCora. Estos corpus servirán de base para los sistemas de etiquetado automático de roles semánticos basados en técnicas de aprendizaje automático. Los analizadores semánticos son componentes básicos en las aplicaciones actuales de las tecnologías del lenguaje, en las que se quiere potenciar una comprensión más profunda del texto para realizar inferencias de más alto nivel y obtener así mejoras cualitativas en los resultados.