Input a Word, Analyze the World represents current perspectives on Corpus Linguistics (CL) from a variety of linguistic subdisciplines. Corpus Linguistics has proven itself an excellent methodology for the study of language variation and change, and is well-suited for interdisciplinary collaboration, as shown by the studies in this volume. Its title is inspired by the use of CL to assess language in different registers and with a variety of purposes. This collection contains thirty contributions by scholars in the field from across the globe, dealing with current topics on corpus production and corpus tools; lexical analysis, phraseology and grammar; translation and contrastive linguistics; and language learning. Language specialists will find these papers inspiring, as they present new insights on aspects related to research and teaching.

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic. This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.

This six-volume set of LNCS 14187, 14188, 14189, 14190, 14191 and 14192 constitutes the refereed proceedings of the 17th International Conference on Document Analysis and Recognition, ICDAR 2021, held in San José, CA, USA, in August 2023. The 53 full papers were carefully reviewed and selected from 316 submissions, and are presented with 101 poster presentations. The papers are organized into the following topical sections: Graphics Recognition, Frontiers in Handwriting Recognition, Document Analysis and Recognition.

Analysing language data systematically and looking closely at how people formulate their thoughts can reveal astonishing insights about the human mind. Without presupposing specific subject knowledge, this book gently introduces its readers to theoretical insights as well as practical principles for systematic linguistic analysis from a cognitive perspective. Drawing on Thora Tenbrink's twenty years' experience in both linguistics and cognitive science, this book offers theoretical guidance and practical advice for doing cognitive discourse analysis. It covers areas of analysis as diverse as attention, perspective, granularity, certainty, inference, transformation, communication, and cognitive strategies, using inspiring examples from many different projects. Simple techniques and tools are used to allow readers new to the subject easy ways to apply the methods, without the need for complex technologies, whilst the cross-disciplinary approach can be applied to a diverse range of research purposes and contexts in which language and thought play a role.

This volume includes the full proceedings from the 1999 World Marketing Congress held in Qawra, Malta with the theme Global Perspectives in Marketing for the 21st Century. The focus of the conference and the enclosed papers is on marketing thought and practices from a global perspective. This volume resents papers on various topics including marketing management, marketing strategy, and consumer behavior. Founded in 1971, the Academy of Marketing Science is an international organization dedicated to promoting timely explorations of phenomena related to the science of marketing in theory, research and practice. Among its services to members and the community at large, the Academy offers conferences, congresses and symposia that attract delegates from around the world. Presentations from these events are published in this Proceedings series, which offers a comprehensive archive of volumes reflecting the evolution of the field. Volumes deliver cutting-edge research and insights, complimenting the Academy’s flagship journals, the Journal of the Academy of Marketing Science (JAMS) and AMS Review. Volumes are edited by leading scholars and practitioners across a wide range of subject areas in marketing science.