This contributed volume explores the achievements gained and the remaining puzzling questions by applying dynamical systems theory to the linguistic inquiry. In particular, the book is divided into three parts, each one addressing one of the following topics: 1) Facing complexity in the right way: mathematics and complexity 2) Complexity and theory of language 3) From empirical observation to formal models: investigation of specific linguistic phenomena, like enunciation, deixis, or the meaning of the metaphorical phrases The application of complexity theory to describe cognitive phenomena is a recent and very promising trend in cognitive science. At the time when dynamical approaches triggered a paradigm shift in cognitive science some decade ago, the major topic of research were the challenges imposed by classical computational approaches dealing with the explanation of cognitive phenomena like consciousness, decision making and language. The target audience primarily comprises researchers and experts in the field but the book may also be beneficial for graduate and post-graduate students who want to enter the field.

This book offers an introduction to modern natural language processing using machine learning, focusing on how neural networks create a machine interpretable representation of the meaning of natural language. Language is crucially linked to ideas - as Webster's 1923 "English Composition and Literature" puts it: "A sentence is a group of words expressing a complete thought". Thus the representation of sentences and the words that make them up is vital in advancing artificial intelligence and other "smart" systems currently being developed. Providing an overview of the research in the area, from Bengio et al.'s seminal work on a "Neural Probabilistic Language Model" in 2003, to the latest techniques, this book enables readers to gain an understanding of how the techniques are related and what is best for their purposes. As well as a introduction to neural networks in general and recurrent neural networks in particular, this book details the methods used for representing words, senses of words, and larger structures such as sentences or documents. The book highlights practical implementations and discusses many aspects that are often overlooked or misunderstood. The book includes thorough instruction on challenging areas such as hierarchical softmax and negative sampling, to ensure the reader fully and easily understands the details of how the algorithms function. Combining practical aspects with a more traditional review of the literature, it is directly applicable to a broad readership. It is an invaluable introduction for early graduate students working in natural language processing; a trustworthy guide for industry developers wishing to make use of recent innovations; and a sturdy bridge for researchers already familiar with linguistics or machine learning wishing to understand the other.

Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches defines the role of ANLP within NLP, and alongside other disciplines such as linguistics, computer science, and cognitive science. The description also includes the categorization of current ANLP research, and examples of current research in ANLP. This book is a useful reference for teachers, students, and materials developers in fields spanning linguistics, computer science, and cognitive science.

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. Specifically, the problems addressed concern the handling of noise due to speech recognition errors, semantic ambiguities, and the notorious problem of underspecification. Consequently the book examines the individual contributions of contextual composing for different types of context. Therefore, contextual information stemming from the domain at hand, prior discourse, and the specific user and real world situation are considered and integrated in a formal model that is applied and evaluated employing different multimodal mobile dialog systems. This book is intended to meet the needs of readers from at least three fields - AI and computer science; computational linguistics; and natural language processing - as well as some computationally oriented linguists, making it a valuable resource for scientists, researchers, lecturers, language processing practitioners and professionals as well as postgraduates and some undergraduates in the aforementioned fields. "The book addresses a problem of great and increasing technical and practical importance - the role of context in natural language processing (NLP). It considers the role of context in three important tasks: Automatic Speech Recognition, Semantic Interpretation, and Pragmatic Interpretation. Overall, the book represents a novel and insightful investigation into the potential of contextual information processing in NLP." Jerome A Feldman, Professor of Electrical Engineering and Computer Science, UC Berkeley, USA http://dm.tzi.de/research/contextual-computing/

Collaboratively Constructed Language Resources (CCLRs) such as Wikipedia, Wiktionary, Linked Open Data, and various resources developed using crowdsourcing techniques such as Games with a Purpose and Mechanical Turk have substantially contributed to the research in natural language processing (NLP). Various NLP tasks utilize such resources to substitute for or supplement conventional lexical semantic resources and linguistically annotated corpora. These resources also provide an extensive body of texts from which valuable knowledge is mined. There are an increasing number of community efforts to link and maintain multiple linguistic resources.
This book aims offers comprehensive coverage of CCLR-related topics, including their construction, utilization in NLP tasks, and interlinkage and management.Various Bachelor/Master/Ph.D. programs in natural language processing, computational linguistics, and knowledge discovery can use this book both as the main text and as a supplementary reading.The bookalso provides a valuable reference guide for researchers and professionalsforthe above topics."

A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.

This book brings together scientists, researchers, practitioners, and students from academia and industry to present recent and ongoing research activities concerning the latest advances, techniques, and applications of natural language processing systems, and to promote the exchange of new ideas and lessons learned. Taken together, the chapters of this book provide a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of intelligent natural language processing. The book presents the state-of-the-art in research on natural language processing, computational linguistics, applied Arabic linguistics and related areas. New trends in natural language processing systems are rapidly emerging - and finding application in various domains including education, travel and tourism, and healthcare, among others. Many issues encountered during the development of these applications can be resolved by incorporating language technology solutions. The topics covered by the book include: Character and Speech Recognition; Morphological, Syntactic, and Semantic Processing; Information Extraction; Information Retrieval and Question Answering; Text Classification and Text Mining; Text Summarization; Sentiment Analysis; Machine Translation Building and Evaluating Linguistic Resources; and Intelligent Language Tutoring Systems.

Proactive Spoken Dialogue Interaction in Multi-Party Environments describes spoken dialogue systems that act as independent dialogue partners in the conversation with and between users. The resulting novel characteristics such as proactiveness and multi-party capabilities pose new challenges on the dialogue management component of such a system and require the use and administration of an extensive dialogue history. In order to assist the proactive spoken dialogue systems development, a comprehensive data collection seems mandatory and may be performed in a Wizard-of-Oz environment. Such an environment builds also the appropriate basis for an extensive usability and acceptance evaluation.

Proactive Spoken Dialogue Interaction in Multi-Party Environments is a useful reference for students and researchers in speech processing.

The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics and pragmatics are based on methods from signal processing and the causal Bayesian models pioneered by especially Pearl. In signal processing, the Bayesian method finds the most probable interpretation by finding the one that maximizes the product of the prior probability and the likelihood of the interpretation. It thus stresses the importance of a production model for interpretation as in Grice's contributions to pragmatics or in interpretation by abduction.

There are not many people who can be said to have influenced and impressed researchers in so many disparate areas and language-geographic fields as Lauri Carlson, as is evidenced in the present Festschrift. His insight and acute linguistic sensitivity and linguistic rationality have spawned findings and research work in many areas, from non-standard etymology to hardcore formal linguistics, not forgetting computational areas such as parsing, terminological databases, and, last but not least, machine translation. In addition to his renowned and widely acknowledged insights in tense and aspect and its relationship with nominal quantification, and his ground-breaking work in dialog using game-theoretic machinery, Lauri has in the last fifteen years as Professor of Language Theory and Translation Technology contributed immensely to areas such as translation, terminology and general applications of computational linguistics. The three editors of the present volume have successfully performed doctoral studies under Lauri 's supervision, and wish with this volume to pay tribute to his supervision and to his influence in matters associated with research and scientific, linguistic and philosophical inquiry, as well as to his humanity and friendship.

The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.

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 coordinate the former.

This book includes 18 chapters in six parts that summarize various research results and associated development activities on the Language Grid. The chapters in Part I describe the framework of the Language Grid, i.e., service-oriented collective intelligence, used to bridge providers, users and operators. Two kinds of software are introduced, the service grid server software and the Language Grid Toolbox, and code for both is available via open source licenses. Part II describes technologies for service workflows that compose atomic language services. Part III reports on research work and activities relating to sharing and using language services. Part IV describes various applications of language services as applicable to intercultural collaboration. Part V contains reports on applying the Language Grid for translation activities, including localization of industrial documents and Wikipedia articles. Finally, Part VI illustrates how the Language Grid can be connected to other service grids, such as DFKI's Heart of Gold and smart classroom services in Tsinghua University in Beijing.

The book will be valuable for researchers in artificial intelligence, natural language processing, services computing and human--computer interaction, particularly those who are interested in bridging technologies and user communities.

"

This book is written for both linguists and computer scientists working in the field of artificial intelligence as well as to anyone interested in intelligent text processing.

Lexical function is a concept that formalizes semantic and syntactic relations between lexical units. Collocational relation is a type of institutionalized lexical relations which holds between the base and its partner in a collocation. Knowledge of collocation is important for natural language processing because collocation comprises the restrictions on how words can be used together. The book shows how collocations can be annotated with lexical functions in a computer readable dictionary - allowing their precise semantic analysis in texts and their effective use in natural language applications including parsers, high quality machine translation, periphrasis system and computer-aided learning of lexica. The books shows how to extract collocations from corpora and annotate them with lexical functions automatically. To train algorithms, the authors created a dictionary of lexical functions containing more than 900 Spanish disambiguated and annotated examples which is a part of this book. The obtained results show that machine learning is feasible to achieve the task of automatic detection of lexical functions.

The theory of formal languages is widely accepted as the backbone of t- oretical computer science. It mainly originated from mathematics (com- natorics, algebra, mathematical logic) and generative linguistics. Later, new specializations emerged from areas ofeither computer science(concurrent and distributed systems, computer graphics, arti?cial life), biology (plant devel- ment, molecular genetics), linguistics (parsing, text searching), or mathem- ics (cryptography). All human problem solving capabilities can be considered, in a certain sense, as a manipulation of symbols and structures composed by symbols, which is actually the stem of formal language theory. Language - in its two basic forms, natural and arti?cial - is a particular case of a symbol system. This wide range of motivations and inspirations explains the diverse - plicability of formal language theory ? and all these together explain the very large number of monographs and collective volumes dealing with formal language theory. In 2004 Springer-Verlag published the volume Formal Languages and - plications, edited by C. Martin-Vide, V. Mitrana and G. P?un in the series Studies in Fuzziness and Soft Computing 148, which was aimed at serving as an overall course-aid and self-study material especially for PhD students in formal language theory and applications. Actually, the volume emerged in such a context: it contains the core information from many of the lectures - livered to the students of the International PhD School in Formal Languages and Applications organized since 2002 by the Research Group on Mathem- ical Linguistics from Rovira i Virgili University, Tarragona, Spain."

The volume "Genres on the Web" has been designed for a wide audience, from the expert to the novice. It is a required book for scholars, researchers and students who want to become acquainted with the latest theoretical, empirical and computational advances in the expanding field of web genre research. The study of web genre is an overarching and interdisciplinary novel area of research that spans from corpus linguistics, computational linguistics, NLP, and text-technology, to web mining, webometrics, social network analysis and information studies. This book gives readers a thorough grounding in the latest research on web genres and emerging document types.

The book covers a wide range of web-genre focused subjects, such as:
The identification of the sources of web genres
Automatic web genre identification
The presentation of structure-oriented models
Empirical case studies

One of the driving forces behind genre research is the idea of a genre-sensitive information system, which incorporates genre cues complementing the current keyword-based search and retrieval applications."

The design of formal calculi in which fundamental concepts underlying interactive systems can be described and studied has been a central theme of theoretical computer science in recent decades, while membrane computing, a rule-based formalism inspired by biological cells, is a more recent field that belongs to the general area of natural computing. This is the first book to establish a link between these two research directions while treating mobility as the central topic. In the first chapter the authors offer a formal description of mobility in process calculi, noting the entities that move: links ( -calculus), ambients (ambient calculi) and branes (brane calculi). In the second chapter they study mobility in the framework of natural computing. The authors define several systems of mobile membranes in which the movement inside a spatial structure is provided by rules inspired by endocytosis and exocytosis. They study their computational power in comparison with the classical notion of Turing computability and their efficiency in algorithmically solving hard problems in polynomial time. The final chapter deals with encodings, establishing links between process calculi and membrane computing so that researchers can share techniques between these fields. The book is suitable for computer scientists working in concurrency and in biologically inspired formalisms, and also for mathematically inclined scientists interested in formalizing moving agents and biological phenomena. The text is supported with examples and exercises, so it can also be used for courses on these topics.

Research in Natural Language Processing (NLP) has rapidly advanced in recent years, resulting in exciting algorithms for sophisticated processing of text and speech in various languages. Much of this work focuses on English; in this book we address another group of interesting and challenging languages for NLP research: the Semitic languages. The Semitic group of languages includes Arabic (206 million native speakers), Amharic (27 million), Hebrew (7 million), Tigrinya (6.7 million), Syriac (1 million) and Maltese (419 thousand). Semitic languages exhibit unique morphological processes, challenging syntactic constructions and various other phenomena that are less prevalent in other natural languages. These challenges call for unique solutions, many of which are described in this book.

The 13 chapters presented in this book bring together leading scientists from several universities and research institutes worldwide. While this book devotes some attention to cutting-edge algorithms and techniques, its primary purpose is a thorough explication of best practices in the field. Furthermore, every chapter describes how the techniques discussed apply to Semitic languages. The book covers both statistical approaches to NLP, which are dominant across various applications nowadays and the more traditional, rule-based approaches, that were proven useful for several other application domains. We hope that this book will provide a "one-stop-shop'' for all the requisite background and practical advice when building NLP applications for Semitic languages.

Parsing can be defined as the decomposition of complex structures into their constituent parts, and parsing technology as the methods, the tools and the software to parse automatically. Parsing is a central area of research in the automatic processing of human language. Parsers are being used in many application areas, for example question answering, extraction of information from text, speech recognition and understanding, and machine translation. New developments in parsing technology are thus widely applicable.
This book contains contributions from many of today's leading researchers in the area of natural language parsing technology. The contributors describe their most recent work and a diverse range of techniques and results. This collection provides an excellent picture of the current state of affairs in this area. This volume is the third in a line of such collections, and its breadth of coverage should make it suitable both as an overview of the current state of the field for graduate students, and as a reference for established researchers.
This volume is of specific interest to researchers, advanced undergraduate students, graduate students, and teachers in the following areas: 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 software and systems, including applications such as machine translation, information extraction, spoken dialogue, multimodal human-computer interaction, text mining, and semantic web technology.

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.

The Social Web (including services such as MySpace, Flickr, last.fm, and WordPress) has captured the attention of millions of users as well as billions of dollars in investment and acquisition. Social websites, evolving around the connections between people and their objects of interest, are encountering boundaries in the areas of information integration, dissemination, reuse, portability, searchability, automation and demanding tasks like querying. The Semantic Web is an ideal platform for interlinking and performing operations on diverse person- and object-related data available from the Social Web, and has produced a variety of approaches to overcome the boundaries being experienced in Social Web application areas.

After a short overview of both the Social Web and the Semantic Web, Breslin et al. describe some popular social media and social networking applications, list their strengths and limitations, and describe some applications of Semantic Web technology to address their current shortcomings by enhancing them with semantics. Across these social websites, they demonstrate a twofold approach for interconnecting the islands that are social websites with semantic technologies, and for powering semantic applications with rich community-created content. They conclude with observations on how the application of Semantic Web technologies to the Social Web is leading towards the "Social Semantic Web" (sometimes also called "Web 3.0"), forming a network of interlinked and semantically-rich content and knowledge.

The book is intended for computer science professionals, researchers, and graduates interested in understanding the technologies and research issues involved in applying Semantic Web technologies to social software. Practitioners and developers interested in applications such as blogs, social networks or wikis will also learn about methods for increasing the levels of automation in these forms of Web communication.

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.

Spoken Dialogue Systems Technology and Design covers key topics in the field of spoken language dialogue interaction from a variety of leading researchers. It brings together several perspectives in the areas of corpus annotation and analysis, dialogue system construction, as well as theoretical perspectives on communicative intention, context-based generation, and modelling of discourse structure. These topics are all part of the general research and development within the area of discourse and dialogue with an emphasis on dialogue systems; corpora and corpus tools and semantic and pragmatic modelling of discourse and dialogue.

This volume is a selection of papers presented at a workshop entitled Predicative Forms in Natural Language and in Lexical Knowledge Bases organized in Toulouse in August 1996. A predicate is a named relation that exists among one or more arguments. In natural language, predicates are realized as verbs, prepositions, nouns and adjectives, to cite the most frequent ones. Research on the identification, organization, and semantic representa tion of predicates in artificial intelligence and in language processing is a very active research field. The emergence of new paradigms in theoretical language processing, the definition of new problems and the important evol ution of applications have, in fact, stimulated much interest and debate on the role and nature of predicates in naturallangage. From a broad theoret ical perspective, the notion of predicate is central to research on the syntax semantics interface, the generative lexicon, the definition of ontology-based semantic representations, and the formation of verb semantic classes. From a computational perspective, the notion of predicate plays a cent ral role in a number of applications including the design of lexical knowledge bases, the development of automatic indexing systems for the extraction of structured semantic representations, and the creation of interlingual forms in machine translation."