The topic of this book is the following optimisation problem: given a set of discrete variables and a set of functions, each depending on a subset of the variables, minimise the sum of the functions over all variables. This fundamental research problem has been studied within several different contexts of discrete mathematics, computer science and artificial intelligence under different names: Min-Sum problems, MAP inference in Markov random fields (MRFs) and conditional random fields (CRFs), Gibbs energy minimisation, valued constraint satisfaction problems (VCSPs), and, for two-state...
The topic of this book is the following optimisation problem: given a set of discrete variables and a set of functions, each depending on a subset ...
This book provides an extensive overview of the formal language landscape between context-free grammars (CFG) and PTIME, moving from Tree Adjoining Grammars to Multiple Context-Free Grammars and then to Range Concatenation Grammars.
This book provides an extensive overview of the formal language landscape between context-free grammars (CFG) and PTIME, moving from Tree Adjoining G...
Recent advances in the fields of knowledge representation, reasoning and human-computer interaction have paved the way for a novel approach to treating and handling context. The field of research presented in this book addresses the problem of contextual computing in artificial intelligence based on the state of the art in knowledge representation and human-computer interaction. The author puts forward a knowledge-based approach for employing high-level context in order to solve some persistent and challenging problems in the chosen showcase domain of natural language understanding....
Recent advances in the fields of knowledge representation, reasoning and human-computer interaction have paved the way for a novel approach to trea...
Preferences are useful in many real-life problems, guiding human decision making from early childhood up to complex professional and organizational decisions. In artificial intelligence specifically, preferences is a relatively new topic of relevance to nonmonotonic reasoning, multiagent systems, constraint satisfaction, decision making, social choice theory and decision-theoretic planning The first part of this book deals with preference representation, with specific chapters dedicated to representation languages, nonmonotonic logics of preferences, conditional preference networks, positive...
Preferences are useful in many real-life problems, guiding human decision making from early childhood up to complex professional and organizational de...
This book reviews the basics of rule learning as applied to classical machine learning and modern data mining. It connects attribute-value learning with inductive logic programming, and offers complete coverage of most important elements of rule learning.
This book reviews the basics of rule learning as applied to classical machine learning and modern data mining. It connects attribute-value learning wi...
There is increasing interaction among communities with multiple languages, thus we need services that can effectively support multilingual communication. The Language Grid is an initiative to build an infrastructure that allows end users to create composite language services for intercultural collaboration. The aim is to support communities to create customized multilingual environments by using language services to overcome local language barriers. The stakeholders of the Language Grid are the language resource providers, the language service users, and the language grid operators who...
There is increasing interaction among communities with multiple languages, thus we need services that can effectively support multilingual communic...
This text centers around three main subjects. The first is the concept of modularity and independence in classical logic and nonmonotonic and other nonclassical logic, and the consequences on syntactic and semantical interpolation and language change. In particular, we will show the connection between interpolation for nonmonotonic logic and manipulation of an abstract notion of size. Modularity is essentially the ability to put partial results achieved independently together for a global result. The second aspect of the book is the authors' uniform picture of conditionals, including...
This text centers around three main subjects. The first is the concept of modularity and independence in classical logic and nonmonotonic and other no...
This text offers an extension to the traditional Kripke semantics for non-classical logics by adding the notion of reactivity. Reactive Kripke models change their accessibility relation as we progress in the evaluation process of formulas in the model. This feature makes the reactive Kripke semantics strictly stronger and more applicable than the traditional one. Here we investigate the properties and axiomatisations of this new and most effective semantics, and we offera wide landscape of applications of the idea of reactivity. Applied topics includereactive automata, reactive grammars,...
This text offers an extension to the traditional Kripke semantics for non-classical logics by adding the notion of reactivity. Reactive Kripke mode...
In many real-world problems, rare categories (minority classes) play essential roles despite their extreme scarcity. The discovery, characterization and prediction of rare categories of rare examples may protect us from fraudulent or malicious behavior, aid scientific discovery, and even save lives.
This book focuses on rare category analysis, where the majority classes have smooth distributions, and the minority classes exhibit the compactness property. Furthermore, it focuses on the challenging cases where the support regions of the majority and minority classes overlap. The...
In many real-world problems, rare categories (minority classes) play essential roles despite their extreme scarcity. The discovery, characterizatio...
Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Arising from the EU MUSCLE network, this multidisciplinary book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain.
Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide ins...
