This book celebrates the work of Yorick Wilks in the form of a selection of his papers which are intended to reflect the range and depth of his work. The volume accompanies a Festschrift which celebrates his contribution to the fields of Computational Linguistics and Artificial Intelligence. The selected papers reflect Yorick 's contribution to both practical and theoretical aspects of automatic language processing.

Academic vocabulary is in fashion, as witnessed by the increasing number of books published on the topic. In the first part of this book , Magali Paquot scrutinizes the concept of 'academic vocabulary' and proposes a corpus-driven procedure based on the criteria of keyness, range and evenness of distribution to select academic words that could be part of a common-core academic vocabulary syllabus. In the second part, the author offers a thorough analysis of academic vocabulary in the International Corpus of Learner English (ICLE) and describes the factors that account for learners' difficulties in academic writing. She then focuses on the role of corpora, and more particularly, learner corpora, in EAP material design. It is the first monograph in which Granger's (1996) Contrastive Interlanguage Analysis is used to compare 10 ICLE learner sub-corpora, in order to distinguish between linguistic features that are shared by learners from a wide range of mother tongue backgrounds and unique features that may be transfer-related.

This book unites a range of approaches to the collection and digitization of diverse language corpora. Its specific focus is on best practices identified in the exploitation of these resources in landmark impact initiatives across different parts of the globe. The development of increasingly accessible digital corpora has coincided with improvements in the standards governing the collection, encoding and archiving of 'Big Data'. Less attention has been paid to the importance of developing standards for enriching and preserving other types of corpus data, such as that which captures the nuances of regional dialects, for example. This book takes these best practices another step forward by addressing innovative methods for enhancing and exploiting specialized corpora so that they become accessible to wider audiences beyond the academy.

The structure and properties of any natural language expression depend on its component sub-expressions - "resources" - and relations among them that are sensitive to basic structural properties of order, grouping, and multiplicity. Resource-sensitivity thus provides a perspective on linguistic structure that is well-defined and universally-applicable. The papers in this collection - by J. van Benthem, P. Jacobson, G. JAger, G-J. Kruijff, G. Morrill, R. Muskens, R. Oehrle, and A. Szabolcsi - examine linguistic resources and resource-sensitivity from a variety of perspectives, including:

- Modal aspects of categorial type inference;
- Multi-dimensional type structures and grammatical architecture;
- Resource-sensitive aspects of binding and anaphora;
- Resource-sensitive inference and discourse context.

In particular, the book contains a number of papers treating anaphorically-dependent expressions as functions, whose application to an appropriate argument yields a type and an interpretation directly integratable with the surrounding grammatical structure. To situate this work in a larger setting, the book contains two appendices:

- an introductory guide to resource-sensivity;
- notes on the historical background of resource-sensitive approaches to binding and anaphora.

The community responsible for developing lexicons for Natural Language Processing (NLP) and Machine Readable Dictionaries (MRDs) started their ISO standardization activities in 2003. These activities resulted in the ISO standard - Lexical Markup Framework (LMF).After selecting and defining a common terminology, the LMF team had to identify the common notions shared by all lexicons in order to specify a common skeleton (called the core model) and understand the various requirements coming from different groups of users.The goals of LMF are to provide a common model for the creation and use of lexical resources, to manage the exchange of data between and among these resources, and to enable the merging of a large number of individual electronic resources to form extensive global electronic resources.The various types of individual instantiations of LMF can include monolingual, bilingual or multilingual lexical resources. The same specifications can be used for small and large lexicons, both simple and complex, as well as for both written and spoken lexical representations. The descriptions range from morphology, syntax and computational semantics to computer-assisted translation. The languages covered are not restricted to European languages, but apply to all natural languages.The LMF specification is now a success and numerous lexicon managers currently use LMF in different languages and contexts.This book starts with the historical context of LMF, before providing an overview of the LMF model and the Data Category Registry, which provides a flexible means for applying constants like /grammatical gender/ in a variety of different settings. It then presents concrete applications and experiments on real data, which are important for developers who want to learn about the use of LMF.

Contents

1. LMF - Historical Context and Perspectives, Nicoletta Calzolari, Monica Monachini and Claudia Soria.2. Model Description, Gil Francopoulo and Monte George.3. LMF and the Data Category Registry: Principles and Application, Menzo Windhouwer and Sue Ellen Wright.4. Wordnet-LMF: A Standard Representation for Multilingual Wordnets, Piek Vossen, Claudia Soria and Monica Monachini.5. Prolmf: A Multilingual Dictionary of Proper Names and their Relations, Denis Maurel, Beatrice Bouchou-Markhoff.6. LMF for Arabic, Aida Khemakhem, Bilel Gargouri, Kais Haddar and Abdelmajid Ben Hamadou.7. LMF for a Selection of African Languages, Chantal Enguehard and Mathieu Mangeot.8. LMF and its Implementation in Some Asian Languages, Takenobu Tokunaga, Sophia Y.M. Lee, Virach Sornlertlamvanich, Kiyoaki Shirai, Shu-Kai Hsieh and Chu-Ren Huang.9. DUELME: Dutch Electronic Lexicon of Multiword Expressions, Jan Odijk.10. UBY-LMF - Exploring the Boundaries of Language-Independent Lexicon Models, Judith Eckle-Kohler, Iryna Gurevych, Silvana Hartmann, Michael Matuschek and Christian M. Meyer.11. Conversion of Lexicon-Grammar Tables to LMF: Application to French, eric Laporte, Elsa Tolone and Matthieu Constant.12. Collaborative Tools: From Wiktionary to LMF, for Synchronic and Diachronic Language Data, Thierry Declerck, Pirsoka Lendvai and Karlheinz Morth.13. LMF Experiments on Format Conversions for Resource Merging: Converters and Problems, Marta Villegas, Muntsa Padro and Nuria Bel.14. LMF as a Foundation for Servicized Lexical Resources, Yoshihiko Hayashi, Monica Monachini, Bora Savas, Claudia Soria and Nicoletta Calzolari.15. Creating a Serialization of LMF: The Experience of the RELISH Project, Menzo Windhouwer, Justin Petro, Irina Nevskaya, Sebastian Drude, Helen Aristar-Dry and Jost Gippert.16. Global Atlas: Proper Nouns, From Wikipedia to LMF, Gil Francopoulo, Frederic Marcoul, David Causse and Gregory Piparo.17. LMF in U.S. Government Language Resource Management, Monte George.

About the Authors

Gil Francopoulo works for Tagmatica (www.tagmatica.com), a company specializing in software development in the field of linguistics and documentation in the semantic web, in Paris, France, as well as for Spotter (www.spotter.com), a company specializing in media and social media analytics.

The book offers a detailed guide to temporal ordering, exploring open problems in the field and providing solutions and extensive analysis. It addresses the challenge of automatically ordering events and times in text. Aided by TimeML, it also describes and presents concepts relating to time in easy-to-compute terms. Working out the order that events and times happen has proven difficult for computers, since the language used to discuss time can be vague and complex. Mapping out these concepts for a computational system, which does not have its own inherent idea of time, is, unsurprisingly, tough. Solving this problem enables powerful systems that can plan, reason about events, and construct stories of their own accord, as well as understand the complex narratives that humans express and comprehend so naturally. This book presents a theory and data-driven analysis of temporal ordering, leading to the identification of exactly what is difficult about the task. It then proposes and evaluates machine-learning solutions for the major difficulties. It is a valuable resource for those working in machine learning for natural language processing as well as anyone studying time in language, or involved in annotating the structure of time in documents.

This book builds on decades of research and provides contemporary theoretical foundations for practical applications to intelligent technologies and advances in artificial intelligence (AI). Reflecting the growing realization that computational models of human reasoning and interactions can be improved by integrating heterogeneous information resources and AI techniques, its ultimate goal is to promote integrated computational approaches to intelligent computerized systems. The book covers a range of interrelated topics, in particular, computational reasoning, language, syntax, semantics, memory, and context information. The respective chapters use and develop logically oriented methods and techniques, and the topics selected are from those areas of logic that contribute to AI and provide its mathematical foundations. The intended readership includes researchers working in the areas of traditional logical foundations, and on new approaches to intelligent computational systems.

The book features recent attempts to construct corpora for specific purposes - e.g. multifactorial Dutch (parallel), Geasy Easy Language Corpus (intralingual), HK LegCo interpreting corpus - and showcases sophisticated and innovative corpus analysis methods. It proposes new approaches to address classical themes - i.e. translation pedagogy, translation norms and equivalence, principles of translation - and brings interdisciplinary perspectives - e.g. contrastive linguistics, cognition and metaphor studies - to cast new light. It is a timely reference for the researchers as well as postgraduate students who are interested in the applications of corpus technology to solving translation and interpreting problems.

Over the past two decades, statistical and other quantitative concepts, models and methods have been increasingly gaining importance and interest in all areas of linguistics and text analysis, as well as in a number of neighboring disciplines and areas of application. The term "quantitative linguistics" comprises all scientific and technical approaches which use such terms and methods in the analysis of or work with language(s), texts and other related subjects. The 71 articles in this handbook, written by internationally-recognized experts, offer a broad, up-to-date overview of the scientific-theoretical principles, the history, the diversity of the subject areas studied, the methods and models used, the results obtained thus far and their applications. The articles are divided up into thirteen chapters: the first chapter includes contributions on the basic principles and the history of the field, nine additional chapters are dedicated to individual descriptions of the levels of linguistic research (from phonology to pragmatics) as well as typological, diachronic and geolinguistic questions. The next two chapters include a description of important models, hypotheses and principles; selected areas of application; and references to neighboring disciplines. The last portion of the handbook is an informative contribution, with information about publication forums, bibliographies, major projects, Internet links, etc. This handbook is useful not only for researchers, teachers and students of all branches of linguistics and the philologies, but also for scientists in neighboring fields, whose theoretical and empirical research touches on linguistic questions (for instance, psychology and sociology), or for those who want to make use of the proven methods or results from quantitative linguistics in their own research. Key features: International authors Unique and fundamental systematics of the field Multidisciplinary and application-oriented

Everyday life would be easier if we could simply talk with machines instead of having to program them. Before such talking robots can be built, however, there must be a theory of how communicating with natural language works. This requires not only a grammatical analysis of the language signs, but also a model of the cognitive agent, with interfaces for recognition and action, an internal database, and an algorithm for reading content in and out. In Database Semantics, these ingredients are used for reconstructing natural language communication as a mechanism for transferring content from the database of the speaker to the database of the hearer.

Part I of this book presents a high-level description of an artificial agent which humans can freely communicate with in their accustomed language. Part II analyzes the major constructions of natural language, i.e., intra- and extrapropositional functor - argument structure, coordination, and coreference, in the speaker and the hearer mode. Part III defines declarative specifications for fragments of English, which are used for an implementation in Java.

The book provides researchers, graduate students and software engineers with a functional framework for the theoretical analysis of natural language communication and for all practical applications of natural language processing.

In both the linguistic and the language engineering community, the creation and use of annotated text collections (or annotated corpora) is currently a hot topic. Annotated texts are of interest for research as well as for the development of natural language pro cessing (NLP) applications. Unfortunately, the annotation of text material, especially more interesting linguistic annotation, is as yet a difficult task and can entail a substan tial amount of human involvement. Allover the world, work is being done to replace as much as possible of this human effort by computer processing. At the frontier of what can already be done (mostly) automatically we find syntactic wordclass tagging, the annotation of the individual words in a text with an indication of their morpho syntactic classification. This book describes the state of the art in syntactic wordclass tagging. As an attempt to give an overall view of the field, this book is of interest to (at least) two, possibly very different, types of reader. The first type consists of those people who are using, or are planning to use, tagged material and taggers. They will want to know what the possibilities and impossibilities of tagging are, but are not necessarily interested in the internal working of automatic taggers. This, on the other hand, is the main interest of our second type of reader, the builders of automatic taggers and other natural language processing software."

A study on minimalist syntax develops an empirical argument for a crash-proof computational system. A crash-proof system is obtained if syntactic dependencies are strictly local (i.e. there is no long-distance Agree). Apparent long-distance dependencies turn out to be the outcome of a recursive chain on local complex dependencies. This framework allows for novel analyses of quirky subjects in Icelandic and Spanish, indefinite SE in Spanish and different types of expletive constructions in English, French, German, Spanish, Italian and Icelandic.

The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from the text. Proposed approach combines the semantic and common-sense knowledge for the better understanding of the text. In addition, the book aims to extract prominent features from the unstructured text by eliminating the noisy, irrelevant and redundant features. Readers will also discover a proposed method for efficient dimensionality reduction to alleviate the data sparseness problem being faced by machine learning model. Authors pay attention to the four main findings of the book : -Performance of the sentiment analysis can be improved by reducing the redundancy among the features. Experimental results show that minimum Redundancy Maximum Relevance (mRMR) feature selection technique improves the performance of the sentiment analysis by eliminating the redundant features. - Boolean Multinomial Naive Bayes (BMNB) machine learning algorithm with mRMR feature selection technique performs better than Support Vector Machine (SVM) classifier for sentiment analysis. - The problem of data sparseness is alleviated by semantic clustering of features, which in turn improves the performance of the sentiment analysis. - Semantic relations among the words in the text have useful cues for sentiment analysis. Common-sense knowledge in form of ConceptNet ontology acquires knowledge, which provides a better understanding of the text that improves the performance of the sentiment analysis.

TRENDS IN LINGUISTICS is a series of books that open new perspectives in our understanding of language. The series publishes state-of-the-art work on core areas of linguistics across theoretical frameworks, as well as studies that provide new insights by approaching language from an interdisciplinary perspective. TRENDS IN LINGUISTICS considers itself a forum for cutting-edge research based on solid empirical data on language in its various manifestations, including sign languages. It regards linguistic variation in its synchronic and diachronic dimensions as well as in its social contexts as important sources of insight for a better understanding of the design of linguistic systems and the ecology and evolution of language. TRENDS IN LINGUISTICS publishes monographs and outstanding dissertations as well as edited volumes, which provide the opportunity to address controversial topics from different empirical and theoretical viewpoints. High quality standards are ensured through anonymous reviewing.

This book describes the main objective of EuroWordNet, which is the building of a multilingual database with lexical semantic networks or wordnets for several European languages. Each wordnet in the database represents a language-specific structure due to the unique lexicalization of concepts in languages. The concepts are inter-linked via a separate Inter-Lingual-Index, where equivalent concepts across languages should share the same index item. The flexible multilingual design of the database makes it possible to compare the lexicalizations and semantic structures, revealing answers to fundamental linguistic and philosophical questions which could never be answered before. How consistent are lexical semantic networks across languages, what are the language-specific differences of these networks, is there a language-universal ontology, how much information can be shared across languages? First attempts to answer these questions are given in the form of a set of shared or common Base Concepts that has been derived from the separate wordnets and their classification by a language-neutral top-ontology. These Base Concepts play a fundamental role in several wordnets. Nevertheless, the database may also serve many practical needs with respect to (cross-language) information retrieval, machine translation tools, language generation tools and language learning tools, which are discussed in the final chapter. The book offers an excellent introduction to the EuroWordNet project for scholars in the field and raises many issues that set the directions for further research in semantics and knowledge engineering.

This volume maps the watershed areas between two 'holy grails' of computer science: the identification and interpretation of "affect "- including sentiment and mood. The expression of sentiment and mood involves the use of metaphors, especially in emotive situations. Affect computing is rooted in hermeneutics, philosophy, political science and sociology, and is now a key area of research in computer science. The 24/7 news sites and blogs facilitate the expression and shaping of opinion locally and globally. Sentiment analysis, based on text and data mining, is being used in the looking at news and blogs for purposes as diverse as: brand management, film reviews, financial market analysis and prediction, homeland security. There are systems that learn how sentiments are articulated.

This work draws on, and informs, research in fields as varied as artificial intelligence, especially reasoning and machine learning, corpus-based information extraction, linguistics, and psychology. "

The "Yearbook of Corpus Linguistics and Pragmatics" "2013" discusses current methodological debates on the synergy of Corpus Linguistics and Pragmatics research. The volume presents insightful pragmatic analyses of corpora in new technological domains and devotes some chapters to the pragmatic description of spoken corpora from various theoretical traditions.

The "Yearbook of Corpus Linguistics and Pragmatics" series will give readers insight into how pragmatics can be used to explain real corpus data, and, in addition, how corpora can explain pragmatic intuitions, and from there, develop and refine theory. Corpus Linguistics can offer a meticulous methodology based on mathematics and statistics, while Pragmatics is characterized by its efforts to interpret intended meaning in real language. This yearbook offers a platform to scholars who combine both research methodologies to present rigorous and interdisciplinary findings about language in real use.

This book is about machine translation (MT) and the classic problems associated with this language technology. It examines the causes of these problems and, for linguistic, rule-based systems, attributes the cause to language's ambiguity and complexity and their interplay in logic-driven processes. For non-linguistic, data-driven systems, the book attributes translation shortcomings to the very lack of linguistics. It then proposes a demonstrable way to relieve these drawbacks in the shape of a working translation model (Logos Model) that has taken its inspiration from key assumptions about psycholinguistic and neurolinguistic function. The book suggests that this brain-based mechanism is effective precisely because it bridges both linguistically driven and data-driven methodologies. It shows how simulation of this cerebral mechanism has freed this one MT model from the all-important, classic problem of complexity when coping with the ambiguities of language. Logos Model accomplishes this by a data-driven process that does not sacrifice linguistic knowledge, but that, like the brain, integrates linguistics within a data-driven process. As a consequence, the book suggests that the brain-like mechanism embedded in this model has the potential to contribute to further advances in machine translation in all its technological instantiations.

Quantitative linguistic research reveals fascinating patterns in contemporary and historical linguistic data. The book offers insights from a broad range of languages, including Japanese, Slovene and Catalan. The reader is convinced that statistic empirical analysis - and increasingly also machine learning and big data - should be an essential part of any serious linguistic enquiry.

This book deals with two fundamental issues in the semiotics of the image. The first is the relationship between image and observer: how does one look at an image? To answer this question, this book sets out to transpose the theory of enunciation formulated in linguistics over to the visual field. It also aims to clarify the gains made in contemporary visual semiotics relative to the semiology of Roland Barthes and Emile Benveniste. The second issue addressed is the relation between the forces, forms and materiality of the images. How do different physical mediums (pictorial, photographic and digital) influence visual forms? How does materiality affect the generativity of forms? On the forces within the images, the book addresses the philosophical thought of Gilles Deleuze and Rene Thom as well as the experiment of Aby Warburg's Atlas Mnemosyne. The theories discussed in the book are tested on a variety of corpora for analysis, including both paintings and photographs, taken from traditional as well as contemporary sources in a variety of social sectors (arts and sciences). Finally, semiotic methodology is contrasted with the computational analysis of large collections of images (Big Data), such as the "Media Visualization" analyses proposed by Lev Manovich and Cultural Analytics in the field of Computer Science to evaluate the impact of automatic analysis of visual forms on Digital Art History and more generally on the image sciences.

The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities. This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statistical models of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information science. It may also be of interest for the upcoming area of systems biology with which the chapters collected here share the view on systems from the point of view of network analysis.

This volume presents articles that focus on the application of formal models in the study of language in a variety of innovative ways, and is dedicated to Jacques Moeschler, professor at University of Geneva, to mark the occasion of his 60th birthday. The contributions, by seasoned and budding linguists of all different linguistic backgrounds, reflect Jacques Moeschler's diverse and visionary research over the years. The book contains three parts. The first part shows how different formal models can be applied to the analysis of such diverse problems as the syntax, semantics and pragmatics of tense, aspect and deictic expressions, syntax and pragmatics of quantifiers and semantics and pragmatics of connectives and negation. The second part presents the application of formal models to the treatment of cognitive issues related to the use of language, and in particular, demonstrating cognitive accounts of different types of human interactions, the context in utterance interpretation (salience, inferential comprehension processes), figurative uses of language (irony pretence), the role of syntax in Theory of Mind in autism and the analysis of the aesthetics of nature. Finally, the third part addresses computational and corpus-based approaches to natural language for investigating language variation, language universals and discourse related issues. This volume will be of great interest to syntacticians, pragmaticians, computer scientists, semanticians and psycholinguists.

Computer parsing technology, which breaks down complex linguistic structures into their constituent parts, is a key research area in the automatic processing of human language. This volume is a collection of contributions from leading researchers in the field of natural language processing technology, each of whom detail their recent work which includes new techniques as well as results. The book presents an overview of the state of the art in current research into parsing technologies, focusing on three important themes: dependency parsing, domain adaptation, and deep parsing. The technology, which has a variety of practical uses, is especially concerned with the methods, tools and software that can be used to parse automatically. Applications include extracting information from free text or speech, question answering, speech recognition and comprehension, recommender systems, machine translation, and automatic summarization. New developments in the area of parsing technology are thus widely applicable, and researchers and professionals from a number of fields will find the material here required reading. As well as the other four volumes on parsing technology in this series this book has a breadth of coverage that makes it suitable both as an overview of the field for graduate students, and as a reference for established researchers in computational linguistics, artificial intelligence, computer science, language engineering, information science, and cognitive science. It will also be of interest to designers, developers, and advanced users of natural language processing systems, including applications such as spoken dialogue, text mining, multimodal human-computer interaction, and semantic web technology.

The present volume of the Yearbook of Corpus Linguistics and Pragmatics series, presents cutting-edge corpus pragmatics research on language use in new social and educational environments. The Yearbook of Corpus Linguistics and Pragmatics offers a platform to scholars who carry out rigorous and interdisciplinary research on language in real use. Corpus Linguistics and Pragmatics have traditionally represented two paths of scientific research, parallel but often mutually exclusive and excluding. Corpus Linguistics can offer a precise methodology based on mathematics and statistics while Pragmatics strives to interpret intended meaning in real language. This series will give readers insight into how pragmatics can be used to explain real corpus data, and how corpora can illustrate pragmatic intuitions.

This book presents the concept of the double hierarchy linguistic term set and its extensions, which can deal with dynamic and complex decision-making problems. With the rapid development of science and technology and the acceleration of information updating, the complexity of decision-making problems has become increasingly obvious. This book provides a comprehensive and systematic introduction to the latest research in the field, including measurement methods, consistency methods, group consensus and large-scale group consensus decision-making methods, as well as their practical applications. Intended for engineers, technicians, and researchers in the fields of computer linguistics, operations research, information science, management science and engineering, it also serves as a textbook for postgraduate and senior undergraduate university students.