Programa de Doctorat en Intel·ligència Artificial: Recent submissions
Now showing items 41-60 of 75
Joint parsing of syntactic and semantic dependencies
Syntactic Dependency Parsing and Semantic Role Labeling (SRL) are two main problems in Natural Language Understanding. Both tasks are closely related and can be regarded as parsing on top of a given sequence. In the ...
Regularized approximate policy iteration using kernel for on-line reinforcement learning
By using Reinforcement Learning (RL), an autonomous agent interacting with the environment can learn how to take adequate actions for every situation in order to optimally achieve its own goal. RL provides a general ...
Extending procrustes analysis : building multi-view 2-D models from 3-D human shape samples
This dissertation formalizes the construction of multi-view 2D shape models from 3D data. We propose several extensions of the well-known Procrustes Analysis (PA) algorithm that allow modeling rigid and non-rigid transformations ...
Link prediction in large directed graphs
The first chapter introduces an approach to machine learning (ML) were data is understood as a network of connected entities. This strategy seeks inter-entity information for knowledge discovery, in contrast with traditional ...
Visualization and interpretability in probabilistic dimensionality reduction models
Over the last few decades, data analysis has swiftly evolved from being a task addressed mainly within the remit of multivariate statistics, to an endevour in which data heterogeneity, complexity and even sheer size, driven ...
Introducing norms into practical reasoning agents
As distributed electronic systems grow to include thousands of components, from grid to peer-to-peer nodes, from (Semantic) Web services to web-apps to computation in the cloud, governance of such systems is becoming a ...
Exploiting distributional semantics for content-based and context-aware recommendation
During the last decade, the use of recommender systems has been increasingly growing to the point that, nowadays, the success of many well-known services depends on these technologies. Recommenders Systems help people to ...
Exploration of customer churn routes using machine learning probabilistic models
The ongoing processes of globalization and deregulation are changing the competitive framework in the majority of economic sectors. The appearance of new competitors and technologies entails a sharp increase in competition ...
ProCLAIM: an argument-based model for deliberating over safety critical actions
In this Thesis we present an argument-based model – ProCLAIM – intended to provide a setting for heterogeneous agents to deliberate on whether a proposed action is safe. That is, whether or not a proposed action is expected ...
On the intelligent management of sepsis in the intensive care unit
The management of the Intensive Care Unit (ICU) in a hospital has its own, very specific requirements that involve, amongst others, issues of risk-adjusted mortality and average length of stay; nurse turnover and communication ...
Multi-objective optimization in graphical models
Many real-life optimization problems are combinatorial, i.e. they concern a choice of the best solution from a finite but exponentially large set of alternatives. Besides, the solution quality of many of these problems ...
The Role of preferences in logic programming: nonmonotonic reasoning, user preferences, decision under uncertainty
Intelligent systems that assist users in fulfilling complex tasks need a concise and processable representation of incomplete and uncertain information. In order to be able to choose among different options, these systems ...
Factoid question answering for spoken documents
In this dissertation, we present a factoid question answering system, specifically tailored for Question Answering (QA) on spoken documents. This work explores, for the first time, which techniques can be robustly adapted ...
Unsupervised learning of relation detection patterns
L'extracció d'informació és l'àrea del processament de llenguatge natural l'objectiu de la qual és l'obtenir dades estructurades a partir de la informació rellevant continguda en fragments textuals. L'extracció d'informació ...
A constraint-based hypergraph partitioning approach to coreference resolution
The objectives of this thesis are focused on research in machine learning for coreference resolution. Coreference resolution is a natural language processing task that consists of determining the expressions in a discourse ...
Generative manifold learning for the exploration of partially labeled data
In many real-world application problems, the availability of data labels for supervised learning is rather limited. Incompletely labeled datasets are common in many of the databases generated in some of the currently most ...
Digui: a flexibe dialogue system for guiding the user interaction to guiding the user interaction to acces web services
Current dialogue systems can handle friendly and collaborative communication that supports diverse types of interactions, such as menus in which the user is asked to choose an option, form filling in which the user is ...
Empirical machine translation and its evaluation
Aquesta tesi estudia l'aplicació de les tecnologies del Processament del Llenguatge Natural disponibles actualment al problema de la Traducció Automàtica basada en Mètodes Empírics i la seva Avaluació.<br/><br/>D'una banda, ...
Acquiring information extraction patterns from unannotated corpora
Information Extraction (IE) can be defined as the task of automatically extracting preespecified kind of information from a text document. The extracted information is encoded in the required format and then can be used, ...
Part-of-speech Tagging: A Machine Learning Approach based on Decision Trees
The study and application of general Machine Learning (ML) algorithms to theclassical ambiguity problems in the area of Natural Language Processing (NLP) isa currently very active area of research. This trend is sometimes ...
