Syntactic and Semantic Relationships in Models of Complex Systems: An Ecological Case

In this paper, the authors extend and generalize the methodology based on the dynamics of systems with the use of differential equations as equations of state, allowing that first order transformed functions not only apply to the primitive or original variables, but also doing so to more complex expressions derived from them, and extending the rules that determine the generation of transformed superior to zero order (variable or primitive). Also, it is demonstrated that for all models of complex reality, there exists a complex model from the syntactic and semantic point of view. The theory is exemplified with a concrete model: MARIOLA model.

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.

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.

PHORA: a system to solve the anaphora in Spanish

In this paper we present a whole Natural Language Processing (NLP) system for Spanish. The core of this system is the parser, which uses the grammatical formalism Lexical-Functional Grammars (LFG). Another important component of this system is the anaphora resolution module. To solve the anaphora, this module contains a method based on linguistic information (lexical, morphological, syntactic and semantic), structural information (anaphoric accessibility space in which the anaphor obtains the antecedent) and statistical information. This method is based on constraints and preferences and solves pronouns and definite descriptions. Moreover, this system fits dialogue and non-dialogue discourse features. The anaphora resolution module uses several resources, such as a lexical database (Spanish WordNet) to provide semantic information and a POS tagger providing the part of speech for each word and its root to make this resolution process easier.

Tackling redundancy in text summarization through different levels of language analysis

One of the main challenges to be addressed in text summarization concerns the detection of redundant information. This paper presents a detailed analysis of three methods for achieving such goal. The proposed methods rely on different levels of language analysis: lexical, syntactic and semantic. Moreover, they are also analyzed for detecting relevance in texts. The results show that semantic-based methods are able to detect up to 90% of redundancy, compared to only the 19% of lexical-based ones. This is also reflected in the quality of the generated summaries, obtaining better summaries when employing syntactic- or semantic-based approaches to remove redundancy.

Una visión comunicacional de la política en Ecuador: Rafael Correa y su bicicleta

Este artículo analiza el video oficial de la campaña del Presidente Correa denominado “spot bicicleta”, elemento promocional usado en las elecciones seccionales del 2013, toma como referencia de análisis las estructuras fonológicas, gráficas, sintácticas y semánticas. La pieza con una duración de 3:30 minutos, recuerda el proceso de “Revolución Ciudadana”, emprendido por el partido Alianza País (35); y resalta la condición de servicio del Presidente, cuyo eje principal es la Patria. El discurso gira entorno a la pobreza, la esperanza y el deseo del Presidente de continuar en el poder. Toda la pieza audiovisual está matizada con elementos posicionados en la mente de los ecuatorianos, usados como una estrategia de persuasión.

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

This paper addresses the problem of the automatic recognition and classification of temporal expressions and events in human language. Efficacy in these tasks is crucial if the broader task of temporal information processing is to be successfully performed. We analyze whether the application of semantic knowledge to these tasks improves the performance of current approaches. We therefore present and evaluate a data-driven approach as part of a system: TIPSem. Our approach uses lexical semantics and semantic roles as additional information to extend classical approaches which are principally based on morphosyntax. The results obtained for English show that semantic knowledge aids in temporal expression and event recognition, achieving an error reduction of 59% and 21%, while in classification the contribution is limited. From the analysis of the results it may be concluded that the application of semantic knowledge leads to more general models and aids in the recognition of temporal entities that are ambiguous at shallower language analysis levels. We also discovered that lexical semantics and semantic roles have complementary advantages, and that it is useful to combine them. Finally, we carried out the same analysis for Spanish. The results obtained show comparable advantages. This supports the hypothesis that applying the proposed semantic knowledge may be useful for different languages.

ViDRILO: The Visual and Depth Robot Indoor Localization with Objects information dataset

In this article we describe a semantic localization dataset for indoor environments named ViDRILO. The dataset provides five sequences of frames acquired with a mobile robot in two similar office buildings under different lighting conditions. Each frame consists of a point cloud representation of the scene and a perspective image. The frames in the dataset are annotated with the semantic category of the scene, but also with the presence or absence of a list of predefined objects appearing in the scene. In addition to the frames and annotations, the dataset is distributed with a set of tools for its use in both place classification and object recognition tasks. The large number of labeled frames in conjunction with the annotation scheme make this dataset different from existing ones. The ViDRILO dataset is released for use as a benchmark for different problems such as multimodal place classification and object recognition, 3D reconstruction or point cloud data compression.

A combined probabilistic framework for learning gestures and actions

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.

El análisis histórico de la mortalidad por causas: problemas y soluciones

El trabajo desarrolla una propuesta metodológica para abordar los principales problemas que plantea el análisis de la mortalidad a partir de las expresiones diagnósticas que se recogen en las partidas de defunción de los registros parroquiales y civiles. La cuestión diacrónica o de recorrido cronológico de las expresiones es abordada desde las técnicas del análisis semántico documental y el estudio de sus tipologías demográfico-sanitarias. La agrupación de las diversas causas de muerte se resuelve con la utilización simultánea de la Segunda Nomenclatura de la Primera Clasificación de Causas de Muerte propuesta por Jacques Bertillon en 1899, y una modificación de la clasificación propuesta por Thomas McKeown en su conocida monografía sobre "El crecimiento moderno de la población".

Decomposition of human behavior using model of competencies: application to robotic control system

For many years, humans and machines have shared the same physical space. To facilitate their interaction with humans, their social integration and for more rational behavior has been sought that the robots demonstrate human-like behavior. For this it is necessary to understand how human behavior is generated, discuss what tasks are performed and how relate to themselves, for subsequent implementation in robots. In this paper, we propose a model of competencies based on human neuroregulator system for analysis and decomposition of behavior into functional modules. Using this model allow separate and locate the tasks to be implemented in a robot that displays human-like behavior. As an example, we show the application of model to the autonomous movement behavior on unfamiliar environments and its implementation in various simulated and real robots with different physical configurations and physical devices of different nature. The main result of this work has been to build a model of competencies that is being used to build robotic systems capable of displaying behaviors similar to humans and consider the specific characteristics of robots.

Canales, sifones y almenaras: el impacto ambiental de las infraestructuras del Canal de Isabel II (Madrid)

El presente artículo tiene como finalidad, valorar el impacto ambiental de las conducciones del Canal de Isabel II en el contexto del paisaje. Partimos de la idea según la cual, las infraestructuras del Canal de Isabel II, y más que formar parte del paisaje por el que se extienden, son el propio paisaje. Nuestra zona de estudio es el noroeste de la Comunidad de Madrid (síntesis de la interacción de los propios agentes naturales, de la ocupación humana y de los usos del suelo), área a la que nos aproximarnos a través de la investigación de la integración paisajística, entendida ésta como una estrategia de intervención en el territorio, que tiene como objetivo principal orientar las transformaciones del paisaje o corregir las ya realizadas, para conseguir su adaptación al propio paisaje. En definitiva, nos encontramos ante la necesidad de ajustar un objeto o actuación territorial a las características fisonómicas de un paisaje dado, o de algunos de sus componentes, así como a su carácter y a sus contenidos semánticos.

When Spanish owns English words

The English language and the Internet, both separately and taken together, are nowadays well-acknowledged as powerful forces which influence and affect the lexico-grammatical characteristics of other languages world-wide. In fact, many authors like Crystal (2004) have pointed out the emergence of the so-called Netspeak, that is, the language used in the Net or World Wide Web; as Crystal himself (2004: 19) puts it, ‘a type of language displaying features that are unique to the Internet […] arising out of its character as a medium which is electronic, global and interactive’. This ‘language’, however, may be differently understood: either as an adaptation of the English language proper to internet requirements and purposes, or as a new and rapidly-changing and developing language as a result of a rapid evolution or adaptation to Internet requirements of almost all world languages, for whom English is a trendsetter. If the second and probably most plausible interpretation is adopted, there are three salient features of ‘Netspeak’: (a) the rapid expansion of all its new linguistic developments thanks to the Internet itself, which may lead to the generalization and widespread acceptance of new words, coinages, or meanings, hundreds of times faster than was the case with the printed media. As said above, (b) the visible influence of English, the most prevalent language on the Internet. Consequently, (c) this new language tends to reduce the ‘distance’ between English and other languages as well as the ignorance of the former by speakers of other languages, since the ‘Netspeak’ version of the latter adopts grammatical, syntactic and lexical features of English. Thus, linguistic differences may even disappear when code-switching and/or borrowing occurs, as whole fragments of English appear in other language contexts. As a consequence of the new situation, an ideal context appears for interlanguage or multilingual word formation to thrive: puns, blends, compounds and word creativity in general find in the web the ideal place to gain rapid acceptance world-wide, as a result of fashion, coincidence, or sheer merit of the new linguistic proposals.

Model of Competencies for Decomposition of Human Behavior: Application to Control System of Robots

Humans and machines have shared the same physical space for many years. To share the same space, we want the robots to behave like human beings. This will facilitate their social integration, their interaction with humans and create an intelligent behavior. To achieve this goal, we need to understand how human behavior is generated, analyze tasks running our nerves and how they relate to them. Then and only then can we implement these mechanisms in robotic beings. In this study, we propose a model of competencies based on human neuroregulator system for analysis and decomposition of behavior into functional modules. Using this model allow separate and locate the tasks to be implemented in a robot that displays human-like behavior. As an example, we show the application of model to the autonomous movement behavior on unfamiliar environments and its implementation in various simulated and real robots with different physical configurations and physical devices of different nature. The main result of this study has been to build a model of competencies that is being used to build robotic systems capable of displaying behaviors similar to humans and consider the specific characteristics of robots.

Aplicación de tecnologías de procesamiento de lenguaje natural y tecnología semántica en Brand Rain y Anpro21

Este artículo presenta la aplicación y resultados obtenidos de la investigación en técnicas de procesamiento de lenguaje natural y tecnología semántica en Brand Rain y Anpro21. Se exponen todos los proyectos relacionados con las temáticas antes mencionadas y se presenta la aplicación y ventajas de la transferencia de la investigación y nuevas tecnologías desarrolladas a la herramienta de monitorización y cálculo de reputación Brand Rain.