An inference mechanism for question answering

This work describes an inference mechanism applied to AliQAn Question Answering System for Spanish in open domain. AliQAn is based fundamentally on the use of syntactic patterns to identify the possible answers. An inference mechanism is applied to the questions set of economic type. In this way, our system improves the accuracy of this question type from 33% to 57%.Facultad de Informátic

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.This paper has been partially supported by the MESOLAP (TIN2010-14860) and GEODAS-BI (TIN2012-37493-C03-03) projects from the Spanish Ministry of Education and Competitivity. Alejandro Maté is funded by the Generalitat Valenciana under an ACIF grant (ACIF/2010/298)

Un mecanismo de inferencia aplicado a la búsqueda de respuesta

Este trabajo describe un mecanismo de inferencia aplicado al Sistema de Búsqueda de Respuestas AliQAn para el idioma español y en dominio abierto. AliQAn está basado fundamentalmente en el uso de patrones sintácticos para identificar las posibles respuestas. Un mecanismo de inferencia es aplicado al conjunto de preguntas de tipo económico. De esta manera, nuestro sistema mejora la precisión de este tipo de preguntas de un 33% a un 57 %.This work describe an inference mechanism apply to AliQAn Question Answering System for Spanish in open domain. AliQAn is based in use of syntactic pattern to identify the answers. Our approach apply an inference mechanism to questions set of economic type. Thus, our system enhance the accuracy of this question type of 33% to 57 %.Red de Universidades con Carreras en Informática (RedUNCI

Sistemas multiagentes en ambientes dinámicos

La meta fundamental de este proyecto es el desarrollo de conocimiento especializado en el área de Inteligencia Artificial Distribuida, estudiando técnicas de representación del conocimiento y razonamiento, junto con métodos de planificación y tecnologías del lenguaje natural aplicadas al desarrollo de sistemas multiagentes. En la línea Planificación, la temática de investigación es el desarrollo de una arquitectura para agentes que soporte tanto control reactivo como deliberativo, de forma tal que el agente pueda actuar de manera competente y efectiva en un ambiente real. Uno de los objetivos de esta investigación es el intento de dotar a un agente inteligente de ambas capacidades. Esto brindará la posibilidad de elegir cuál sería la mejor forma de actuar frente a un problema determinado. Por otro lado, las otras líneas se basan en técnicas de procesamiento del lenguaje natural (PLN). La información textual disponible en la web podría ser categorizada en expresiones de hecho y de opinión. Las expresiones de hechos están relacionadas a entidades, eventos y sus propiedades. Por otro lado, las de opinión son usualmente expresiones subjetivas que describen algún sentimiento sobre las personas, valoraciones o sentimientos hacia las entidades, eventos y sus propiedades. Siguiendo con esto, cada línea de investigación, dentro del PLN, está orientada a tratar con una de estas categorías. Es así que la línea de Opinion Mining se centra en las expresiones de opinión. Mientras que la línea de investigación sobre la inteligencia empresarial (Business Intelligence), en esta primera etapa, está orientada a trabajar solamente con expresiones de hechos.Eje: Agentes y sistemas inteligentesRed de Universidades con Carreras en Informática (RedUNCI

An overview of the linguistic resources used in cross-language question answering systems in CLEF Conference

The development of the Semantic Web requires great economic and human effort. Consequently, it is very useful to create mechanisms and tools that facilitate its expansion. From the standpoint of information retrieval (hereafter IR), access to the contents of the Semantic Web can be favored by the use of natural language, as it is much simpler and faster for the user to engage in his habitual form of expression. The growing popularity of Internet and the wide availability of web informative resources for general audiences are a fairly recent phenomenon, although man´s need to hurdle the language barrier and communicate with others is as old as the history of mankind. The World Wide Web, also known as WWW, together with the growing globalization of companies and organizations, and the increase of the non-English speaking audience, entails the demand for tools allowing users to secure information from a wide range of resources. Yet the underlying linguistic restrictions are often overlooked by researchers and designers. Against this background, a key characteristic to be evaluated in terms of the efficiency of IR systems is its capacity to allow users find a corpus of documents in different languages, and to facilitate the relevant information despite limited linguistic competence regarding the target language

An Overview of the Linguistic Resources used in Cross-Language Question Answering Systems in CLEF Conference

The development of the Semantic Web requires great economic and human effort. Consequently, it is very useful to create mechanisms and tools that facilitate its expansion. From the standpoint of information retrieval (hereafter IR), access to the contents of the Semantic Web can be favored by the use of natural language, as it is much simpler and faster for the user to engage in his habitual form of expression. The growing popularity of Internet and the wide availability of web informative resources for general audiences are a fairly recent phenomenon, although man´s need to hurdle the language barrier and communicate with others is as old as the history of mankind. The World Wide Web, also known as WWW, together with the growing globalization of companies and organizations, and the increase of the non-English speaking audience, entails the demand for tools allowing users to secure information from a wide range of resources. Yet the underlying linguistic restrictions are often overlooked by researchers and designers. Against this background, a key characteristic to be evaluated in terms of the efficiency of IR systems is its capacity to allow users find a corpus of documents in different languages, and to facilitate the relevant information despite limited linguistic competence regarding the target language