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Recognizing Textual Entailment
In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing when the meaning of a text snippet is contained in the meaning of a second piece of text. This simple abstraction of an exceedingly complex problem has broad appeal partly because it can be conceived also as a component in other NLP applications, from Machine Translation to Semantic Search to Information Extraction. It also avoids commitment to any specific meaning representation and reasoning framework, broadening its appeal within the research com...
Bitext Alignment
This book provides an overview of various techniques for the alignment of bitexts. It describes general concepts and strategies that can be applied to map corresponding parts in parallel documents on various levels of granularity. Bitexts are valuable linguistic resources for many different research fields and practical applications. The most predominant application is machine translation, in particular, statistical machine translation. However, there are various other threads that can be followed which may be supported by the rich linguistic knowledge implicitly stored in parallel resources. Bitexts have been explored in lexicography, word sense disambiguation, terminology extraction, compu...
Knowledge Graphs
A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence. The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods.
The Balancing Act
Symbolic and statistical approaches to language have historically been at odds--the former viewed as difficult to test and therefore perhaps impossible to define, and the latter as descriptive but possibly inadequate. At the heart of the debate are fundamental questions concerning the nature of language, the role of data in building a model or theory, and the impact of the competence-performance distinction on the field of computational linguistics. Currently, there is an increasing realization in both camps that the two approaches have something to offer in achieving common goals. The eight contributions in this book explore the inevitable "balancing act" that must take place when symbolic ...
Natural Language Processing and Information Systems
This book constitutes the refereed proceedings of the 11th International Conference on Applications of Natural Language to Information Systems, NLDB 2006, held in Klagenfurt, Austria in May/June 2006 as part of UNISCON 2006. The book presents 17 revised full papers and 5 revised short papers, organized in topical sections on concepts extraction and ontology, ontologies and task repository utilization, query processing, information retrieval and dialog processing, and NLP techniques.
Advances in Natural Language Processing
This book constitutes the refereed proceedings of the 5th International Conference on Natural Language Processing, FinTAL 2006, held in Turku, Finland in August 2006. The book presents 72 revised full papers together with 1 invited talk and the extended abstracts of 2 invited keynote addresses. The papers address all current issues in computational linguistics and monolingual and multilingual intelligent language processing - theory, methods and applications.
The Oxford Handbook of Computational Linguistics
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.
Parallel Text Processing
l This book evolved from the ARCADE evaluation exercise that started in 1995. The project's goal is to evaluate alignment systems for parallel texts, i. e. , texts accompanied by their translation. Thirteen teams from various places around the world have participated so far and for the first time, some ten to fifteen years after the first alignment techniques were designed, the community has been able to get a clear picture of the behaviour of alignment systems. Several chapters in this book describe the details of competing systems, and the last chapter is devoted to the description of the evaluation protocol and results. The remaining chapters were especially commissioned from researchers ...
Graph Theory, Computational Intelligence and Thought
Martin Charles Golumbic has been making seminal contributions to algorithmic graph theory and artificial intelligence throughout his career. He is universally admired as a long-standing pillar of the discipline of computer science. He has contributed to the development of fundamental research in artificial intelligence in the area of complexity and spatial-temporal reasoning as well as in the area of compiler optimization. Golumbic's work in graph theory led to the study of new perfect graph families such as tolerance graphs, which generalize the classical graph notions of interval graph and comparability graph. He is credited with introducing the systematic study of algorithmic aspects in i...
Semantics. Volume 3
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