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

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."

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.

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.

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.

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. "

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.

Polysemy is a term used in semantic and lexical analysis to describe a word with multiple meanings. The problem is to establish whether its the same word with related meanings or different words that happen to look or sound the same. In 'Plainly planes plane plains plainly' how many distinct lexical items are there? Such words present few difficulties in everyday language, but pose near-intractable problems for linguists and lexicographers. The contributors, including Anna Wierzbicka, Charles Fillmore, and James Pustejovsky, consider the implications of these problems for grammatical theory and how they may be addressed in computational linguistics.

Contemporary data analytics involves extracting insights from data and translating them into action. With its turn towards empirical methods and convergent data sources, cognitive linguistics is a fertile context for data analytics. There are key differences between data analytics and statistical analysis as typically conceived. Though the former requires the latter, it emphasizes the role of domain-specific knowledge. Statistical analysis also tends to be associated with preconceived hypotheses and controlled data. Data analytics, on the other hand, can help explore unstructured datasets and inspire emergent questions. This volume addresses two key aspects in data analytics for cognitive linguistic work. Firstly, it elaborates the bottom-up guiding role of data analytics in the research trajectory, and how it helps to formulate and refine questions. Secondly, it shows how data analytics can suggest concrete courses of research-based action, which is crucial for cognitive linguistics to be truly applied. The papers in this volume impart various data analytic methods and report empirical studies across different areas of research and application. They aim to benefit new and experienced researchers alike.

This volume will be of particular interest to readers interested in expanding the applications of corpus linguistics techniques through new tools and approaches. The text includes selected papers from the Fifth North American Symposium, hosted by the Linguistics Department at Montclair State University in Montclair New Jersey in May 2004. The symposium papers represented several areas of corpus studies including language development, syntactic analysis, pragmatics and discourse, language change, register variation, corpus creation and annotation, and practical applications of corpus work, primarily in language teaching, but also in medical training and machine translation. A common thread through most of the papers was the use of corpora to study domains longer than the word. Not surprisingly, fully half of the papers deal with the computational tools and linguistic strategies needed to search for and analyze these longer spans of language while most of the remaining papers examine particular syntactic and rhetorical properties of one or more corpora.

Peer reviewed articles from the Natural Language Processing and Cognitive Science (NLPCS) 2014 meeting in October 2014 workshop. The meeting fosters interactions among researchers and practitioners in NLP by taking a Cognitive Science perspective. Articles cover topics such as artificial intelligence, computational linguistics, psycholinguistics, cognitive psychology and language learning.

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 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.

Computer keystroke logging is an exciting development in writing research methodology that allows a documents evolution to be logged and then replayed as if the document were being written for the first time. Computer keystroke logged data allows analysis of the revisions and pauses made by authors during the writing of texts.
Computer Keystroke Logging and Writing: Methods and Applications is the first book to successfully collect a group of leading computer keystroke logging researchers into a single volume and provide an invaluable introduction and overview of this dynamic area of research.
This volume provides the reader unfamiliar with writing research an introduction to the field and it provides the reader unfamiliar with the technique a sound background in keystroke logging technology and an understanding of its potential in writing research. In the core of the methods section, leading researchers demonstrate how keystroke logging can be used to analyze the writing process phenomena of the pause, the writing unit and the revision unit. These phenomena are illustrated with data from current keystroke logging research projects. The final section of the book explores a range of application possibilities for computer keystroke logging. These include how keystroke logging can be used to study how translators approach their work, how keystroke logging, alone or coupled with other techniques, can be used to examine theoretical proposals and models, and how keystroke logging can be used in pedagogical settings.
*Work from the world's leading researchers in one volume
*Provides and excellent introduction and overview of key-stroke logging
*Includes a discussion ofapplications for this exciting new field

It is with great pleasure that we are presenting to the community the second edition of this extraordinary handbook. It has been over 15 years since the publication of the first edition and there have been great changes in the landscape of philosophical logic since then. The first edition has proved invaluable to generations of students and researchers in formal philosophy and language, as well as to consumers of logic in many applied areas. The main logic article in the Encyclopaedia Britannica 1999 has described the first edition as 'the best starting point for exploring any of the topics in logic'. We are confident that the second edition will prove to be just as good The first edition was the second handbook published for the logic commu nity. It followed the North Holland one volume Handbook of Mathematical Logic, published in 1977, edited by the late Jon Barwise. The four volume Handbook of Philosophical Logic, published 1983-1989 came at a fortunate temporal junction at the evolution of logic. This was the time when logic was gaining ground in computer science and artificial intelligence circles. These areas were under increasing commercial pressure to provide devices which help and/or replace the human in his daily activity. This pressure required the use of logic in the modelling of human activity and organisa tion on the one hand and to provide the theoretical basis for the computer program constructs on the other."

This book provides an in-depth view of the current issues, problems and approaches in the computation of meaning as expressed in language. Aimed at linguists, computer scientists, and logicians with an interest in the computation of meaning, this book focuses on two main topics in recent research in computational semantics. The first topic is the definition and use of underspecified semantic representations, i.e. formal structures that represent part of the meaning of a linguistic object while leaving other parts unspecified. The second topic discussed is semantic annotation. Annotated corpora have become an indispensable resource both for linguists and for developers of language and speech technology, especially when used in combination with machine learning methods. The annotation in corpora has only marginally addressed semantic information, however, since semantic annotation methodologies are still in their infancy. This book discusses the development and application of such methodologies.

Research writing and teaching is a great challenge for novice scholars, especially L2 writers. This book presents a compelling and much-needed automated writing evaluation (AWE) reinforcement to L2 research writing pedagogy.

Using data from a newspaper corpus, this book offers the first empirical study into the development of style in early mass media. The book analyses how news discourse was shaped over time by external factors, such as the historical context, news production, technological innovation and current affairs, and as such both conformed to and deviated from generic conventions. In this analysis, media style appears as a dynamic concept which is highly sensitive to innovative approaches towards making news not only informative but also entertaining to read.This cutting edge survey will be of interest to academics researching corpus linguistics, media discourse and stylistics.The editorial board includes: Frantisek Cermak (Prague), Susan Conrad (Portland), Geoffrey Leech (Lancaster), Elena Tognini-Bonelli (Lecce and TWC), Ruth Wodak (Lancaster and Vienna), and, Feng Zhiwei (Beijing)."The Corpus and Discourse" series consists of two strands. The first, "Research in Corpus and Discourse", features innovative contributions to various aspects of corpus linguistics and a wide range of applications, from language technology via the teaching of a second language to a history of mentalities. The second strand, "Studies in Corpus and Discourse", is comprised of key texts bridging the gap between social studies and linguistics. Although equally academically rigorous, this strand will be aimed at a wider audience of academics and postgraduate students working in both disciplines.

Natural Language is not only the most important means of communication between human beings, it is also used over historical periods for the pres- vation of cultural achievements and their transmission from one generation to the other. During the last few decades, the ?ood of digitalized information has been growing tremendously. This tendency will continue with the globali- tion of information societies and with the growing importance of national and international computer networks. This is one reason why the theoretical und- standing and the automated treatment of communication processes based on natural language have such a decisive social and economic impact. In this c- text, the semantic representation of knowledge originally formulated in natural language plays a central part, because it connects all components of natural language processing systems, be they the automatic understanding of natural language (analysis), the rational reasoning over knowledge bases, or the g- eration of natural language expressions from formal representations. This book presents a method for the semantic representation of natural l- guage expressions (texts, sentences, phrases, etc. ) which can be used as a u- versal knowledge representation paradigm in the human sciences, like lingu- tics, cognitive psychology, or philosophy of language, as well as in com- tational linguistics and in arti?cial intelligence. It is also an attempt to close the gap between these disciplines, which to a large extent are still working separately.

Vagueness is central to the flexibility and robustness of natural language descriptions. Vague concepts are robust to the imprecision of our perceptions, while still allowing us to convey useful, and sometimes vital, information. The study of vagueness in Artificial Intelligence (AI) is therefore motivated by the desire to incorporate this robustness and flexibility into intelligent computer systems. Such a goal, however, requires a formal model of vague concepts that will allow us to quantify and manipulate the uncertainty resulting from their use as a means of passing information between autonomous agents.

This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. The new calculus has many applications, especially in automated reasoning, learning, data analysis and information fusion. This book gives a rigorous introduction to label semantics theory, illustrated with many examples, and suggests clear operational interpretations of the proposed measures. It also provides a detailed description of how the theory can be applied in data analysis and information fusion based on a range of benchmark problems.

'Natural Language Processing in the Real World' is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real-world where there may not be an existing rich dataset. This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented. This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects. .