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Discourse anaphora is a challenging linguistic phenomenon that has given rise to research in fields as diverse as linguistics, computational linguistics and cognitive science. Because of the diversity of approaches these fields bring to the anaphora problem, the editors of this volume argue that there needs to be a synthesis, or at least a principled attempt to draw the differing strands of anaphora research together. The selected papers in this volume all contribute to the aim of synthesis and were selected to represent the growing importance of corpus-based and computational approaches to anaphora description, and to developing natural language systems for resolving anaphora in natural language.
Discourse anaphora is a challenging linguistic phenomenon that has given rise to research in fields as diverse as linguistics, computational linguistics and cognitive science. Because of the diversity of approaches these fields bring to the anaphora problem, the editors of this volume argue that there needs to be a synthesis, or at least a principled attempt to draw the differing strands of anaphora research together. The selected papers in this volume all contribute to the aim of synthesis and were selected to represent the growing importance of corpus-based and computational approaches to anaphora description, and to developing natural language systems for resolving anaphora in natural language.
Discourse anaphora is a challenging linguistic phenomenon that has given rise to research in fields as diverse as linguistics, computational linguistics and cognitive science. Because of the diversity of approaches these fields bring to the anaphora problem, the editors of this volume argue that there needs to be a synthesis, or at least a principled attempt to draw the differing strands of anaphora research together. The selected papers in this volume all contribute to the aim of synthesis and were selected to represent the growing importance of corpus-based and computational approaches to anaphora description, and to developing natural language systems for resolving anaphora in natural language.
CICLing 2001 is the second annual Conference on Intelligent text processing and Computational Linguistics (hence the name CICLing), see www.CICLing.org. It is intended to provide a balanced view of the cutting edge developments in both theoretical foundations of computational linguistics and practice of natural language text processing with its numerous applications. A feature of the CICLing conferences is their wide scope that covers nearly all areas of computational linguistics and all aspects of natural language processing applications. The conference is a forum for dialogue between the specialists working in these two areas. This year our invited speakers were Graeme Hirst (U. Toronto, Canada), Sylvain Kahane (U. Paris 7, France), and Ruslan Mitkov (U. Wolverhampton, UK). They delivered excellent extended lectures and organized vivid discussions. A total of 72 submissions were received, all but very few of surprisingly high quality. After careful reviewing, the Program Committee selected for presentation 53 of them, 41 as full papers and 12 as short papers, by 98 authors from 19 countries: Spain (19 authors), Japan (15), USA (12), France, Mexico (9 each), Sweden (6), Canada, China, Germany, Italy, Malaysia, Russia, United Arab Emirates (3 each), Argentina (2), Bulgaria, The Netherlands, Ukraine, UK, and Uruguay (1 each).
Ruslan Mitkov's highly successful Oxford Handbook of Computational Linguistics has been substantially revised and expanded in this second edition. Alongside updated accounts of the topics covered in the first edition, it includes 17 new chapters on subjects such as semantic role-labelling, text-to-speech synthesis, translation technology, opinion mining and sentiment analysis, and the application of Natural Language Processing in educational and biomedical contexts, among many others. The volume is divided into four parts that examine, respectively: the linguistic fundamentals of computational linguistics; the methods and resources used, such as statistical modelling, machine learning, and corpus annotation; key language processing tasks including text segmentation, anaphora resolution, and speech recognition; and the major applications of Natural Language Processing, from machine translation to author profiling. The book will be an essential reference for researchers and students in computational linguistics and Natural Language Processing, as well as those working in related industries.
Teaching computers to solve language problems is one of the major challenges of natural language processing. There is a large amount of interesting research devoted to this field. This book fills an existing gap in the literature with an up-to-date survey of the field, including the author’s own contributions. A number of different fields overlap in anaphora resolution – computational linguistics, natural language processing (NLP), grammar, semantics, pragmatics, discourse analysis and artificial intelligence. This book begins by introducing basic notions and terminology, moving onto early research methods and approaches, recent developments and applications, and future directions. It addresses various issues related to the practical implementation of anaphora systems, such as rules employed, algorithms implemented or evaluation techniques used. This is an ideal reference book for students and researchers in this particular area of computational linguistics. Since anaphora resolution is vital for the development of any practical NLP system, the book will be of interest to readers from both academia and industry.
Covering the major approaches to the use of corpus data, this work gathers together influential readings from leading names in the discipline, including Biber, Widdowson, Sinclair, Carter and McCarthy.
This volume provides an up-to-date survey of the field of corpus linguistics, a field whose methodology has revolutionized much of the empirical work done in most fields of linguistic study over the past decade. Corpus linguistics investigates human language by starting out from large collections of texts - spoken, written, or recorded. These language corpora, which are now regularly available in electronic form, are the basis for quantitative and qualitative research on almost any question of linguistic interest. Many techniques that are in use in corpus linguistics today are rooted in the tradition of the late 18th and 19th century, when linguistics began to make use of mathematical and empirical methods. Modern corpus linguistics has used and developed these methods in close connection with computer science and computational linguistics. The handbook sketches the history of corpus linguistics, shows its potential, discusses its problems, and describes various methods of collecting, annotating, and searching corpora as well as processing corpus data. It also reports case studies that illustrate the wide range of linguistic research questions addressed in corpus linguistics. The over 60 articles included in the handbook are divided into five sections: (1) the origins and history of corpus linguistics and surveys of its relationship to central fields of linguistics (2) corpus compilation (3) corpus types (4) preprocessing of corpora (5) the use and exploitation of corpora. The final section gives an overview of the results of corpus studies obtained in phonetics, phonology, morphology, syntax, semantics, sociolinguistics, historical linguistics, stylometry, dialectology, and discourse analysis. It also reports on recent advances made in human and machine translation, contrastive studies, computer-assisted language learning, and automatic summarization. The contributors to the volume are internationally known experts in their respective fields. The handbook is intended for a wide audience ranging from teachers, university students, and scholars to anyone interested in the use of computers in linguistic analyses and applications.
This book lays out a path leading from the linguistic and cognitive basics, to classical rule-based and machine learning algorithms, to today’s state-of-the-art approaches, which use advanced empirically grounded techniques, automatic knowledge acquisition, and refined linguistic modeling to make a real difference in real-world applications. Anaphora and coreference resolution both refer to the process of linking textual phrases (and, consequently, the information attached to them) within as well as across sentence boundaries, and to the same discourse referent. The book offers an overview of recent research advances, focusing on practical, operational approaches and their applications. In part I (Background), it provides a general introduction, which succinctly summarizes the linguistic, cognitive, and computational foundations of anaphora processing and the key classical rule- and machine-learning-based anaphora resolution algorithms. Acknowledging the central importance of shared resources, part II (Resources) covers annotated corpora, formal evaluation, preprocessing technology, and off-the-shelf anaphora resolution systems. Part III (Algorithms) provides a thorough description of state-of-the-art anaphora resolution algorithms, covering enhanced machine learning methods as well as techniques for accomplishing important subtasks such as mention detection and acquisition of relevant knowledge. Part IV (Applications) deals with a selection of important anaphora and coreference resolution applications, discussing particular scenarios in diverse domains and distilling a best-practice model for systematically approaching new application cases. In the concluding part V (Outlook), based on a survey conducted among the contributing authors, the prospects of the research field of anaphora processing are discussed, and promising new areas of interdisciplinary cooperation and emerging application scenarios are identified. Given the book’s design, it can be used both as an accompanying text for advanced lectures in computational linguistics, natural language engineering, and computer science, and as a reference work for research and independent study. It addresses an audience that includes academic researchers, university lecturers, postgraduate students, advanced undergraduate students, industrial researchers, and software engineers.