Seminar paper from the year 2006 in the subject English Language and Literature Studies - Linguistics, grade: 1, University of Marburg (Fremdsprachliche Philologien), course: Proseminar Semantics, language: English, abstract: "Ambiguity is pervasive at all levels of analysis. It has been, is, and is likely to remain the key problem in natural language processing." (Gadzar 1993:161) This statement by Gerald Gadzar expresses the necessity to cope with the challenge of ambiguity resolution. As the phenomenon of ambiguity is widespread in human language, an interesting question would be: How could a machine be able to handle ambiguity while even humans have difficulties in solving such problems? This paper will first define the phenomenon of ambiguity and explain the different types of it. An interesting aspect will be the effect of garden path sentences.

Academics from a number of disciplines, and several practicing executives, discuss how managers can make effective strategic decisions amidst the uncertainties and ambiguity of major transitions, be they technological, financial, regulatory, or economic. Contributors draw lessons from the experiences of actual companies, and they offer maps and models for guiding effective action. Empirical studies reveal some proven practices for innovation in the face of adversity, and a study in contrasts shows how one company successfully reframed policy in response to a drastic environmental change, and how another succeeded by holding to a constant strategic plan in a changing environment.

Semantic interpretation and the resolution of ambiguity presents an important advance in computer understanding of natural language. While parsing techniques have been greatly improved in recent years, the approach to semantics has generally improved in recent years, the approach to semantics has generally been ad hoc and had little theoretical basis. Graeme Hirst offers a new, theoretically motivated foundation for conceptual analysis by computer, and shows how this framework facilitates the resolution of lexical and syntactic ambiguities. His approach is interdisciplinary, drawing on research in computational linguistics, artificial intelligence, montague semantics, and cognitive psychology.

A thought-provoking guide to help you lean in to the discomfort of the unknown to turn creative opportunities into intentional design, from Stanford University's world-renowned d.school. “Navigating Ambiguity reminds us not to run from uncertainty but rather see it as a defining moment of opportunity.”—Yves Béhar, Founder and CEO, fuseproject A design process presents a series of steps, but in real life, it rarely plays out this neatly. Navigating Ambiguity underscores how the creative process isn’t formulaic. This book shows you how to surrender control by being adaptable, curious, and unbiased as well as resourceful, tenacious, and courageous. Designers and educators Andrea Small and Kelly Schmutte use humor and clear steps to help you embrace uncertainty as you approach a creative project. First, they explain how the brain works and why it defaults to certainty. Then they show you how to let go of the need for control and instead employ a flexible strategy that relies on the balance between acting and adapting, and the give-and-take between opposing approaches to make your way to your goal. Beautiful cut-paper artwork illustrations offer ways to rethink creative work without hitting the usual roadblocks. The result is a more open and satisfying journey from assignment or idea to finished product.

This is an exciting time for Artificial Intelligence, and for Natural Language Processing in particular. Over the last five years or so, a newly revived spirit has gained prominence that promises to revitalize the whole field: the spirit of empiricism. This book introduces a new approach to the important NLP issue of automatic ambiguity resolution, based on statistical models of text. This approach is compared with previous work and proved to yield higher accuracy for natural language analysis. An effective implementation strategy is also described, which is directly useful for natural language analysis. The book is noteworthy for demonstrating a new empirical approach to NLP; it is essential reading for researchers in natural language processing or computational linguistics.

Leverage the power of machine learning and deep learning to extract information from text data About This Book Implement Machine Learning and Deep Learning techniques for efficient natural language processing Get started with NLTK and implement NLP in your applications with ease Understand and interpret human languages with the power of text analysis via Python Who This Book Is For This book is intended for Python developers who wish to start with natural language processing and want to make their applications smarter by implementing NLP in them. What You Will Learn Focus on Python programming paradigms, which are used to develop NLP applications Understand corpus analysis and different types of data attribute. Learn NLP using Python libraries such as NLTK, Polyglot, SpaCy, Standford CoreNLP and so on Learn about Features Extraction and Feature selection as part of Features Engineering. Explore the advantages of vectorization in Deep Learning. Get a better understanding of the architecture of a rule-based system. Optimize and fine-tune Supervised and Unsupervised Machine Learning algorithms for NLP problems. Identify Deep Learning techniques for Natural Language Processing and Natural Language Generation problems. In Detail This book starts off by laying the foundation for Natural Language Processing and why Python is one of the best options to build an NLP-based expert system with advantages such as Community support, availability of frameworks and so on. Later it gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them. During the course of the book, you will explore the semantic as well as syntactic analysis of text. You will understand how to solve various ambiguities in processing human language and will come across various scenarios while performing text analysis. You will learn the very basics of getting the environment ready for natural language processing, move on to the initial setup, and then quickly understand sentences and language parts. You will learn the power of Machine Learning and Deep Learning to extract information from text data. By the end of the book, you will have a clear understanding of natural language processing and will have worked on multiple examples that implement NLP in the real world. Style and approach This book teaches the readers various aspects of natural language Processing using NLTK. It takes the reader from the basic to advance level in a smooth way.

Tolerating Ambiguity for Leadership and Professional Effectiveness focuses on an underaEUR"publicized success factor in work and personal life. As the world of work has become more uncertain and rapidly changing, the ability to tolerate ambiguity as well as thrive from it has gained in importance as a trait and behavior for leaders, managers, and individual contributors. The purpose of the book is to enhance the reader's tolerance for ambiguity as a method of fortifying his or her leadership and professional effectiveness. The book describes relevant research and opinion about many aspects of tolerating ambiguity. Each chapter contains a few ideas for dealing better with ambiguity, and the final chapter presents a comprehensive list of suggestions for becoming more effective at dealing with ambiguity. SelfaEUR"quizzes are presented in ten chapters to help you personalize the major chapter theme under consideration. All key points throughout the book are illustrated with examples, including references to identified individuals and business organizations. The major contribution of the book is its systematic presentation of applied information related to tolerating ambiguity, such as the payoffs from tolerating ambiguity, the attributes and actions of people who tolerate ambiguity, enhancing leadership effectiveness, and the facilitation of creativity and innovation. The book also includes a master plan for applying the information about ambiguity tolerance to serve as a guideline toward action.

This book examines volatility, uncertainty, complexity and ambiguity (VUCA) and addresses the need for broader knowledge and application of new concepts and frameworks to deal with unpredictable and rapid changing situations. The premises of VUCA can shape all aspects of an organization. To cover all areas, the book is divided into six sections. Section 1 acts as an introduction to VUCA and complexity. It reviews ways to manage complexity, while providing examples for tools and approaches that can be applied. The main focus of Section 2 is on leadership, strategy and planning. The chapters in this section create new approaches to handle VUCA environments pertaining to these areas including using the Tetralemma logics, tools from systemic structural constellation (SySt) approach of psychotherapy and organizational development, to provide new ideas for the management of large strategic programs in organizations. Section 3 considers how marketing and sales are affected by VUCA, from social media’s influence to customer value management. Operations and cost management are highlighted in Section 4. This section covers VUCA challenges within global supply chains and decision-oriented controlling. In Section 5 organizational structure and process management are showcased, while Section 6 is dedicated to addressing the effects of VUCA in IT, technology and data management. The VUCA forces present businesses with the need to move from linear modes of thought to problem solving with synthetic and simultaneous thinking. This book should help to provide some starting points and ideas to deal with the next era. It should not be understood as the end of the road, but as the beginning of a journey exploring and developing new concepts for a new way of management.

During the past decade, evidence of dissociation between conscious and nonconscious information processing has emerged from the study of normal subjects and brain damaged patients. The thirty-five original contributions in this book cover the latest work on this important topic. During the past decade, evidence of dissociation between conscious and nonconscious information processing has emerged from the study of normal subjects and brain damaged patients. The thirty-five original contributions in this book cover the latest work on this important topic across such traditional areas of research as vision, face recognition, spatial attention, control processes, semantic memory, episodic memory, and learning. Each section is introduced by an overview chapter that presents and evaluates the available empirical evidence in a given area and is followed by several experimental papers. The book opens with the Association Lecture, by George Mandler, "On Remembering without Really Trying: Hypermnesia, Incubation, and Mind Popping."

Finalist in the Business/Personal Finance category of the 2019 International Book Awards Every day, people around the world make financial decisions. They choose to invest in a stock, sell their holdings in a mutual fund or buy a condominium. These decisions are complex and financially tricky—even for financial professionals. But the literature available on financial research is dated and narrowly focused without any real practical application. Until now there's been a gap in the literature: a book that shows you how to conduct a step by step comprehensive financial investigation that ends in a decision. This book gives you that how. Investing in Financial Research is a guidebook for conducting financial investigations and lays out Cheryl Strauss Einhorn's AREA Method—a research and decision-making system that uniquely controls for bias, focuses on the incentives of others and expands knowledge while improving judgement—and applies it to investigating financial situations. AREA is applicable to all sorts of financial sleuthing, whether for investment analysis or investigative journalism. It allows you to be the expert in your own life. The AREA Method provides you with: *Defined tasks that guide and focus your research on your vision of success; *A structure that isolates your sources, giving you insight into their perspectives, biases and incentives; *Investigative resources, tips and techniques to upgrade your research and analysis beyond document-based sources; *Exercises to foster creativity and originality in your thinking; *A sequence and framework that brings your disparate pieces of research together to build your confidence and conviction about your financial decision.