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.

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.

Traditionally, anaphor resolution focused on structural cues of the antecedent. Recently, the interaction between discourse factors and information structure affecting antecedent salience has been more thoroughly explored. This volume depicts selected peer-reviewed research papers that tackle issues in anaphor resolution from theoretical, empirical and experimental perspectives. These collected articles present a wide spectrum of cross-linguistic data (Dutch, German, Spanish, Turkish, Yurakaré) and also offer new results from L1 and L2 acquisition studies. Data interpretation span from typological to psycholinguistic viewpoints and are related to recent developments in linguistic theory. One data analysis puts the issue of anaphor resolution in a historical context. The experimental findings are complemented by reviews of the current literature on the role of discourse units. This volume gives a comprehensive overview of the state of discussion how the interaction between information structure and contextual discourse affects salience. That's why it will be welcomed by all linguists and psycholinguists who are theoretically and / or experimentally investigating several aspects of anaphor resolution.

This book covers anaphora resolution for the English language from a linguistic and computational point of view. First, a definition of anaphors that applies to linguistics as well as information technology is given. On this foundation, all types of anaphors and their characteristics for English are outlined. To examine how frequent each type of anaphor is, a corpus of different hypertexts has been established and analysed with regard to anaphors. The most frequent type are non-finite clause anaphors - a type which has never been investigated so far. Therefore, the potential of non-finite clause anaphors are further explored with respect to anaphora resolution. After presenting the fundamentals of computational anaphora resolution and its application in text retrieval, rules for resolving non-finite clause anaphors are established. Therefore, this book shows that a truly interdisciplinary approach can achieve results which would not have been possible otherwise. Open Access: In July 2019, this volume was retroactively turned into an Open Access publication thanks to the support of the Fachinformationsdienst Linguistik. https://www.linguistik.de/

Individual Differences in Anaphora Resolution: Language and cognitive effects explores anaphora resolution from different perspectives, and investigates various aspects of the phenomenon, as contributions include research protocols that combine old and new experimental methodologies as well as theoretical and empirical approaches. A central theme across volume contributions are the multiple linguistic and extralinguistic factors that constrain anaphora resolution, its processing and acquisition by a variety of populations (children and adults, monolinguals, bilinguals and second language learners) as well as the mechanisms underlying anaphora resolution. Anaphora resolution constitutes an ideal environment to test the interaction between domain-general cognitive systems and domain-specific linguistic sub-routines, since variability in referential preferences is not related to binding constraints (an integral part of syntax per se) but is closely tied to processing (functional constraints) modulated by the integration of discourse-filtered information.

This book presents the results of three experimental studies focusing on the ability of people with dyslexia to resolve ambiguous anaphoric sentences where concrete and abstract referents are present. Each study represents a step in the ongoing investigation of this issue, and stems from questions left unanswered by previous research. This work is primarily inspired by the desire to gain a better understanding of the role of syntactic and lexical knowledge in text comprehension, and, more specifically, of the effects of word concreteness and abstractness in anaphora resolution contexts for readers with dyslexia. The book also investigates the resources necessary to process ambiguous anaphoric sentences. The innovative methodology implemented here comprises both experimental techniques (such as eye-tracking) and the use of questionnaires and standardised tests to answer specific research questions. It also puts forward a hypothesis that explains the different deficits manifesting in people with dyslexia, and suggests that, in reading comprehension tasks, the known impairment in people with dyslexia’s working memory may hinder their ability to efficiently and accurately perform tasks involving procedural memory resources. As a consequence, this impairment would emerge as disruptions of people with dyslexia’s semantic and syntactic competence, as well as their functioning in complex tasks which are particularly demanding in terms of working memory resources.

Natural language processing (NLP) is a branch of artificial intelligence that has emerged as a prevalent method of practice for a sizeable amount of companies. NLP enables software to understand human language and process complex data that is generated within businesses. In a competitive market, leading organizations are showing an increased interest in implementing this technology to improve user experience and establish smarter decision-making methods. Research on the application of intelligent analytics is crucial for professionals and companies who wish to gain an edge on the opposition. The Handbook of Research on Natural Language Processing and Smart Service Systems is a collection of innovative research on the integration and development of intelligent software tools and their various applications within professional environments. While highlighting topics including discourse analysis, information retrieval, and advanced dialog systems, this book is ideally designed for developers, practitioners, researchers, managers, engineers, academicians, business professionals, scholars, policymakers, and students seeking current research on the improvement of competitive practices through the use of NLP and smart service systems.