Patrick Saint-Dizier – författare

This book is an introduction to Prolog (£rQgramming in ~ic). It presents the basic foundations of Prolog and basic and fundamental programming methods. This book is written for programmers familiar with other programming languages, as well as for novices in computer science, willing to have an original introduction to programming. The approach adopted in this book is thus based on methodological elements together with some pragmatic aspects. The book is composed of two parts. In the fIrst part the major aspects of programming in Prolog are presented step by step. Each new aspect is illustrated by short examples and exercises. The second part is composed of more developed examples, which are often games, that illustrate major aspects of artifIcial intelligence. More advanced books are given in the bibliography and will allow the reader to deepen his or her know ledge of Prolog. Prolog was first designed in France at OJ.A., Marseille, with a specific syntax. We have adopted here a more common notation, defIned at Edinburgh, which tends to be an implicit norm. At the end of each chapter of the fIrst part, there are exercises that the reader is invited to do and to test on his or her machine. Complete answers are given in Appendix A, at the end of the book.

Lexical semantics has become a major research area within computational linguistics, drawing from psycholinguistics, knowledge representation, computer algorithms and architecture. Research programmes whose goal is the definition of large lexicons are asking what the appropriate representation structure is for different facets of lexical information. Among these facets, semantic information is probably the most complex and the least explored. Computational Lexical Semantics is one of the first volumes to provide models for the creation of various kinds of computerized lexicons for the automatic treatment of natural language, with applications to machine translation, automatic indexing, and database front-ends, knowledge extraction, among other things. It focuses on semantic issues, as seen by linguists, psychologists and computer scientists. Besides describing academic research, it also covers ongoing industrial projects.

Lexical semantics has become a major research area within computational linguistics, drawing from psycholinguistics, knowledge representation, computer algorithms and architecture. Research programmes whose goal is the definition of large lexicons are asking what the appropriate representation structure is for different facets of lexical information. Among these facets, semantic information is probably the most complex and the least explored. Computational Lexical Semantics is one of the first volumes to provide models for the creation of various kinds of computerized lexicons for the automatic treatment of natural language, with applications to machine translation, automatic indexing, and database front-ends, knowledge extraction, among other things. It focuses on semantic issues, as seen by linguists, psychologists and computer scientists. Besides describing academic research, it also covers ongoing industrial projects.

This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology. While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse. Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner.

This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology. While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse. Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner.

A great deal of attention has been devoted in the past ten years in the lingu- tic and computational linguistics communities to the syntax and the semantics of nouns, verbs and also, but to a lesser extent, to adjectives. Related p- nomena such as quanti?cation or tense and aspect have motivated a number of in-depth studies and projects. In contrast, prepositions have received less attention. The reasons are quite clear: prepositions are highly polysemic, p- sibly more so than adjectives, and linguistic realizations are extremely dif?cult to predict, not to mention the dif?culty of identifying cross-linguistic regula- ties. Furthermore, a number of languages do not use prepositions or postpo- tions (or make a limited use of them) and prefer other linguistic forms such as morphological marks, e. g. case marks. Let us mention, however, projects devoted to prepositions expressing space, time and movement in arti?cial intelligence and in natural language processing, and also the development of formalisms and heuristics to handle prepositional phrase attachment ambiguities. Prepositions are also present in subcategorization frames of predicative lexical items, but often in an informal and coarse-grained way. Let us also mention the large number of studies in psycholinguistics and in ethnolinguistics around speci?c preposition senses. Finally, prepositions seem to reach a very deep level in the cognitive-semantic structure of the brain: cognitive grammar developers often use prepositions in their metalanguage, in order to express very primitive notions.

A great deal of attention has been devoted in the past ten years in the lingu- tic and computational linguistics communities to the syntax and the semantics of nouns, verbs and also, but to a lesser extent, to adjectives. Related p- nomena such as quanti?cation or tense and aspect have motivated a number of in-depth studies and projects. In contrast, prepositions have received less attention. The reasons are quite clear: prepositions are highly polysemic, p- sibly more so than adjectives, and linguistic realizations are extremely dif?cult to predict, not to mention the dif?culty of identifying cross-linguistic regula- ties. Furthermore, a number of languages do not use prepositions or postpo- tions (or make a limited use of them) and prefer other linguistic forms such as morphological marks, e. g. case marks. Let us mention, however, projects devoted to prepositions expressing space, time and movement in arti?cial intelligence and in natural language processing, and also the development of formalisms and heuristics to handle prepositional phrase attachment ambiguities. Prepositions are also present in subcategorization frames of predicative lexical items, but often in an informal and coarse-grained way. Let us also mention the large number of studies in psycholinguistics and in ethnolinguistics around speci?c preposition senses. Finally, prepositions seem to reach a very deep level in the cognitive-semantic structure of the brain: cognitive grammar developers often use prepositions in their metalanguage, in order to express very primitive notions.

A great deal of attention has been devoted in the past ten years in the lingu- tic and computational linguistics communities to the syntax and the semantics of nouns, verbs and also, but to a lesser extent, to adjectives. Related p- nomena such as quanti?cation or tense and aspect have motivated a number of in-depth studies and projects. In contrast, prepositions have received less attention. The reasons are quite clear: prepositions are highly polysemic, p- sibly more so than adjectives, and linguistic realizations are extremely dif?cult to predict, not to mention the dif?culty of identifying cross-linguistic regula- ties. Furthermore, a number of languages do not use prepositions or postpo- tions (or make a limited use of them) and prefer other linguistic forms such as morphological marks, e. g. case marks. Let us mention, however, projects devoted to prepositions expressing space, time and movement in arti?cial intelligence and in natural language processing, and also the development of formalisms and heuristics to handle prepositional phrase attachment ambiguities. Prepositions are also present in subcategorization frames of predicative lexical items, but often in an informal and coarse-grained way. Let us also mention the large number of studies in psycholinguistics and in ethnolinguistics around speci?c preposition senses. Finally, prepositions seem to reach a very deep level in the cognitive-semantic structure of the brain: cognitive grammar developers often use prepositions in their metalanguage, in order to express very primitive notions.

This book is an introduction to Prolog (£rQgramming in ~ic). It presents the basic foundations of Prolog and basic and fundamental programming methods. This book is written for programmers familiar with other programming languages, as well as for novices in computer science, willing to have an original introduction to programming. The approach adopted in this book is thus based on methodological elements together with some pragmatic aspects. The book is composed of two parts. In the fIrst part the major aspects of programming in Prolog are presented step by step. Each new aspect is illustrated by short examples and exercises. The second part is composed of more developed examples, which are often games, that illustrate major aspects of artifIcial intelligence. More advanced books are given in the bibliography and will allow the reader to deepen his or her know ledge of Prolog. Prolog was first designed in France at OJ.A., Marseille, with a specific syntax. We have adopted here a more common notation, defIned at Edinburgh, which tends to be an implicit norm. At the end of each chapter of the fIrst part, there are exercises that the reader is invited to do and to test on his or her machine. Complete answers are given in Appendix A, at the end of the book.

This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology. While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse. Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner.