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Reversible grammar allows computational models to be built that are equally well suited for the analysis and generation of natural language utterances. This task can be viewed from very different perspectives by theoretical and computational linguists, and computer scientists. The papers in this volume present a broad range of approaches to reversible, bi-directional, and non-directional grammar systems that have emerged in recent years. This is also the first collection entirely devoted to the problems of reversibility in natural language processing. Most papers collected in this volume are derived from presentations at a workshop held at the University of California at Berkeley in the summer of 1991 organised under the auspices of the Association for Computational Linguistics. This book will be a valuable reference to researchers in linguistics and computer science with interests in computational linguistics, natural language processing, and machine translation, as well as in practical aspects of computability.
This book aims to inform researchers with an interest in natural language generation about advances in the field. It is organised around four topics – system architectures, content planning, discourse planning and realisation in linguistic form - and it presents some of the most important works in this area of research.
Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of both Natural Language Understanding (NLU) and Natural Language Generation (NLG). This is because the aims of these fields are to build systems that understand what people mean when they speak or write, and that can produce linguistic strings that successfully express to people the intended content. In order for NLP to scale beyond partial, task-specific solutions, researchers in these fields must be informed by what is known about how humans use language to express and understand communicative intents. The purpose of this book is to present a selection of useful information about semantics and pragmatics, as understood in linguistics, in a way that's accessible to and useful for NLP practitioners with minimal (or even no) prior training in linguistics.
Languages, in all their forms, are the more efficient and natural means for people to communicate. Enormous quantities of information are produced, distributed and consumed using languages. Human language technology's main purpose is to allow the use of automatic systems and tools to assist humans in producing and accessing information, to improve communication between humans, and to assist humans in communicating with machines. This book, sponsored by the Directorate General XIII of the European Union and the Information Science and Engineering Directorate of the National Science Foundation, USA, offers the first comprehensive overview of the human language technology field.
Consider the problem of a robot (algorithm, learning mechanism) moving along the real line attempting to locate a particular point ? . To assist the me- anism, we assume that it can communicate with an Environment (“Oracle”) which guides it with information regarding the direction in which it should go. If the Environment is deterministic the problem is the “Deterministic Point - cation Problem” which has been studied rather thoroughly [1]. In its pioneering version [1] the problem was presented in the setting that the Environment could charge the robot a cost which was proportional to the distance it was from the point sought for. The question of having multiple communicating robots locate a point on the line has also been studied [1, 2]. In the stochastic version of this problem, we consider the scenario when the learning mechanism attempts to locate a point in an interval with stochastic (i. e. , possibly erroneous) instead of deterministic responses from the environment. Thus when it should really be moving to the “right” it may be advised to move to the “left” and vice versa. Apart from the problem being of importance in its own right, the stoch- tic pointlocationproblemalsohas potentialapplications insolvingoptimization problems. Inmanyoptimizationsolutions–forexampleinimageprocessing,p- tern recognition and neural computing [5, 9, 11, 12, 14, 16, 19], the algorithm worksits wayfromits currentsolutionto the optimalsolutionbasedoninfor- tion that it currentlyhas. A crucialquestionis oneof determining the parameter whichtheoptimizationalgorithmshoulduse.
This two-volume set of LNAI 12340 and LNAI 12341 constitutes the refereed proceedings of the 9th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2020, held in Zhengzhou, China, in October 2020. The 70 full papers, 30 poster papers and 14 workshop papers presented were carefully reviewed and selected from 320 submissions. They are organized in the following areas: Conversational Bot/QA; Fundamentals of NLP; Knowledge Base, Graphs and Semantic Web; Machine Learning for NLP; Machine Translation and Multilinguality; NLP Applications; Social Media and Network; Text Mining; and Trending Topics.
A comprehensive overview of the state-of-the-art in natural language generation for interactive systems, with links to resources for further research.
This volume presents the proceedings of the Sixth International Workshop on Automated Natural Language Generation held in Castel Ivano, Trento, Italy, April 5-7, 1992. Besides an invited lecture by Nadia Magnenat-Thalmann, a well-known researcher in computer animation, on creating and visualizing speech and emotion, the volume includes the 17 thouroughly reviewed papers accepted for presentation, selected out of the submissions to the Workshop, as well as 11 statements contributed to panels on multilinguality and generation or extending language generation to multiple media. The accepted papers by leading researchers from Japan, North America and Europe fall in sections on generator system architecture, issues in realisation, issues in discourse structure, and beyond traditional generation.
CICLing 2003 (www.CICLing.org) was the 4th annual Conference on Intelligent Text Processing and Computational Linguistics. It was intended to provide a balanced view of the cutting-edge developments in both the theoretical foundations of computational linguistics and the practice of natural language text processing with its numerous applications. A feature of 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 we were honored by the presence of our keynote speakers Eric Brill (Microsoft Research, USA), Aravind Joshi (U. Pennsylvania, USA), Adam Kilgarriff (Brighton U., UK), and Ted Pedersen (U. Minnesota, USA), who delivered excellent extended lectures and organized vivid discussions. Of 92 submissions received, after careful reviewing 67 were selected for presentation; 43 as full papers and 24 as short papers, by 150 authors from 23 countries: Spain (23 authors), China (20), USA (16), Mexico (13), Japan (12), UK (11), Czech Republic (8), Korea and Sweden (7 each), Canada and Ireland (5 each), Hungary (4), Brazil (3), Belgium, Germany, Italy, Romania, Russia and Tunisia (2 each), Cuba, Denmark, Finland and France (1 each).