The essays in this interdisciplinary book cover a range of implementations and designs, from formal computational models to large-scale NL processing systems.Natural language (NL) refers to human language-complex, irregular, diverse, with all its philosophical problems of meaning and context. Setting a new direction in AI research, this book explores the development of knowledge representation and reasoning (KRR) systems that simulate the role of NL in human information and knowledge processing. Traditionally, KRR systems have incorporated NL as an interface to an expert system or knowledge base that performed tasks separate from NL processing. As this book shows, however, the computational nature of representation and inference in NL makes it the ideal level for all tasks in an intelligent computer system. NL processing combines the qualitative characteristics of human knowledge processing with a computer's quantitative advantages, allowing for in-depth, systematic processing of vast amounts of information. The essays in this interdisciplinary book cover a range of implementations and designs, from formal computational models to large-scale NL processing systems.ContributorsSyed S. Ali, Bonnie J. Dorr, Karen Ehrlich, Robert Givan, Susan M. Haller, Sanda Harabagiu, Chung Hee Hwang, Lucja Iwanska, Kellyn Kruger, Naveen Mata, David A. McAllester, David D. McDonald, Susan W. McRoy, Dan Moldovan, William J. Rapaport, Lenhart Schubert, Stuart C. Shapiro, Clare R. Voss

th It is with great pleasure that I present the selected papers from the 4 Int- national Sanskrit Computational Linguistics Symposium (4i-SCLS) to you. The event is being hosted by the Jawaharlal Nehru University, the premier research UniversityofIndiaduring(December10-12,2010)attheSpecialCenterforS- skrit Studies. The ?rst symposium was organized at INRIA, France, by G' erard Huet in 2007, the second at Brown University, USA, by Peter Scharf in 2008, and the third was organized at the University of Hyderabad by Amba Kulkarni in January2009. The Sanskrit computational linguistics community is relatively young, and the foundation for this kind of formal meeting to exchange ideas between Sanskritists, linguists and computer scientists was given by Prof. Huet and Prof. Amba Kulkarni. My hearty thanks to both of them for bringing about this uni?cation of scholars under one umbrella. The 4i-SCLS saw excellent response from the scholars. We received more than 31 papers, which were examined by our Program Committee members to shortlist 18 papers for publication presented in this volume. The papers can be categorized under the following broad areas: 1. Phonology and speech technology 2. Morphology and shallow parsing 3. Syntax, semantics and parsing 4. Lexical resources, annotation and search 5. Machine translation and ambiguity resolution 6. Computer simulation of Ast ~ adhyay ~ ~ ? . . Some of the notable misses were the speech corpora annotation, image p- cessingtechniques likeOCR,andalsothe paperswrittenin Sanskrit. E?orts will be made to ensure wider participation by scholars in future events.

Rothkegel argues that text production is the result of interaction between text knowledge and object knowledge - the conventional ordering and presentation of knowledge for communicative purposes and the conceptual organisation of world knowledge.

A central problem of natural language generation is that of 'expressibility'. Meteer presents a solution which uses a level of representation called the Text Structure, an intermediate between the representation of world and the language.

This book aims to inform researchers with an interest in natural language generation about advances in the field. It is organised around four topics - system architectures, content planning, discourse planning and realisation in linguistic form - and it presents some of the most important works in this area of research.

Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. "Uncertainty Modeling for Data Mining: A Label Semantics Approach" introduces 'label semantics', a fuzzy-logic-based theory for modeling uncertainty. Several new data mining algorithms based on label semantics are proposed and tested on real-world datasets. A prototype interpretation of label semantics and new prototype-based data mining algorithms are also discussed. This book offers a valuable resource for postgraduates, researchers and other professionals in the fields of data mining, fuzzy computing and uncertainty reasoning.

Zengchang Qin is an associate professor at the School of Automation Science and Electrical Engineering, Beihang University, China; Yongchuan Tang is an associate professor at the College of Computer Science, Zhejiang University, China.

In "Speaking," Willem "Pim" Levelt, Director of the Max-Planck-Institut fur Psycholinguistik, accomplishes the formidable task of covering the entire process of speech production, from constraints on conversational appropriateness to articulation and self-monitoring of speech. Speaking is unique in its balanced coverage of all major aspects of the production of speech, in the completeness of its treatment of the entire speech process, and in its strategy of exemplifying rather than formalizing theoretical issues."

The dream of automatic language translation is now closer thanks to recent advances in the techniques that underpin statistical machine translation. This class-tested textbook from an active researcher in the field, provides a clear and careful introduction to the latest methods and explains how to build machine translation systems for any two languages. It introduces the subject's building blocks from linguistics and probability, then covers the major models for machine translation: word-based, phrase-based, and tree-based, as well as machine translation evaluation, language modeling, discriminative training and advanced methods to integrate linguistic annotation. The book also reports the latest research, presents the major outstanding challenges, and enables novices as well as experienced researchers to make novel contributions to this exciting area. Ideal for students at undergraduate and graduate level, or for anyone interested in the latest developments in machine translation.

This book is a first-stop introduction to corpus-based language research. It takes the reader systematically through the practical problems and benefits including the points to be reviewed before using computers, obtaining corpus material, the main analytical tools and the most important applications of computerised natural language processing. Each chapter offers guidance on programming where appropriate at a level suitable for readers with no prior experience, and provides exercises to help the reader to apply the principles covered. Case studies are used to show how the techniques are used in genuine research situations. * Provides and introduction to computer analysis, techniques, the practical problems involved in using them and their potential benefits * The guidance on programming provides a basic tool kit for use and devleopment by readers with no previous experience. * The exercises at the end of each chapter allow readers to test their understanding and to develop an effective approach to their own research problems. * The case studies demonstrate the use of the techniques described in real research situations.

Fur Leser, die bereits die Grundlagen der Wissensverarbeitung und Computernetzwerke beherrschen, gibt das Buch einen UEberblick uber innovative Verfahren, die die automatisierte Suche, Recherche, Klassifikation und Verwaltung von Texten im Kontext dezentraler Systeme und vor allem im WWW erlauben. Besondere Aufmerksamkeit wird dabei auf eine personalisierte Verarbeitung gerichtet, die auch zeitliche Aspekte, wie z. B. das digitale Vergessen, einbeziehen. An vielen Stellen werden auf interessante und neuartige Art und Weise Analogien aus anderen Wissensgebieten, so z. B. zur Verarbeitung von Informationen und zum Lernen im menschlichen Gehirn sowie der Natur schlechthin genutzt.

This major new textbook provides a clearly-written, concise and accessible introduction to speech and language processing. Assuming knowledge of only the very basics of linguistics and written specifically for students with no technical background, it is the perfect starting point for anyone beginning to study the discipline. Students are introduced to topics such as digital signal processing, speech analysis and synthesis, finite-state machines, automatic speech recognition, parsing and probabilistic grammars, and are shown from a very elementary level how to work with two programming languages, C and Prolog. The accompanying CD-ROM contains all the software described in the book, along with a C compiler, Prolog interpreter and sound file editor, thus providing a self-contained, one-stop resource for the learner. Setting a firm grounding in speech and language processing and an invaluable foundation for further study, Introducing Speech and Language Processing is set to become the leading introduction to the field.

Situation Theory grew out of attempts by Jon Barwise in the late 1970s to provide a semantics for 'naked-infinitive' perceptual reports such as 'Claire saw Jon run'. Barwise's intuition was that Claire didn't just see Jon, an individual, but Jon doing something, a situation. Situations are individuals having properties and standing in relations. A theory of situations would allow us to study and compare various types of situations or situation-like entitles, such as facts, events, and scenes. One of the central themes of situation theory of meaning and reference should be set within a general theory of information, one moreover that is rich enough to do justice to perception, communication, and thought. By now many people have contributed by the need to give a rigorous mathematical account of the principles of information that underwrite the theory.

"Text Analysis with R for Students of Literature" is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological tool kit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that we simply cannot gather using traditional qualitative methods of close reading and human synthesis. "Text Analysis with R for Students of Literature" provides a practical introduction to computational text analysis using the open source programming language R. R is extremely popular throughout the sciences and because of its accessibility, R is now used increasingly in other research areas. Readers begin working with text right away and each chapter works through a new technique or process such that readers gain a broad exposure to core R procedures and a basic understanding of the possibilities of computational text analysis at both the micro and macro scale. Each chapter builds on the previous as readers move from small scale microanalysis of single texts to large scale macroanalysis of text corpora, and each chapter concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book s focus is on making the technical palatable and making the technical useful and immediately gratifying."