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Author : R. Harald Baayen Publisher : Springer Science & Business Media Page : 335 pages File Size : 42,5 Mb Release : 2012-12-06 Category : Language Arts & Disciplines ISBN : 9789401008440
Word Frequency Distributions by R. Harald Baayen Pdf
This book is a comprehensive introduction to the statistical analysis of word frequency distributions, intended for computational linguists, corpus linguists, psycholinguists, and researchers in the field of quantitative stylistics. It aims to make these techniques more accessible for non-specialists, both theoretically, by means of a careful introduction to the underlying probabilistic and statistical concepts, and practically, by providing a program library implementing the main models for word frequency distributions.
Word Frequency Distributions by R. Harald Baayen Pdf
This book is a comprehensive introduction to the statistical analysis of word frequency distributions, intended for computational linguists, corpus linguists, psycholinguists, and researchers in the field of quantitative stylistics. It aims to make these techniques more accessible for non-specialists, both theoretically, by means of a careful introduction to the underlying probabilistic and statistical concepts, and practically, by providing a program library implementing the main models for word frequency distributions.
Word Frequency Distributions by R. Harald Baayen Pdf
This book is a comprehensive introduction to the statistical analysis of word frequency distributions, intended for computational linguists, corpus linguists, psycholinguists, and researchers in the field of quantitative stylistics. It aims to make these techniques more accessible for non-specialists, both theoretically, by means of a careful introduction to the underlying probabilistic and statistical concepts, and practically, by providing a program library implementing the main models for word frequency distributions.
The present book finds and collects absolutely new aspects of word frequency. First, eminent characteristics (such as the h-point, first used in scientometrics, the k-, m-, and n-points) are introduced - it can be shown that the geometry of word frequency is fundamentally based on them. Furthermore, various indicators of text properties are proposed for the first time, such as thematic concentration, autosemantic text compactness, autosemantic density, etc. In detail, the autosemantic structure of a given text is evaluated by means of a graph representation and its properties (according to a problem from network research). Special emphasis is given to the part-of-speech differentiation, which plays a significant role in stylistics. On the basis of a general theory, which has been developed especially for linguistic research, problems of the frequency structure of texts with respect to word occurrence are investigated and discussed in detail. Methodologically, specific reference is made to synergetic linguistics, including some exemplary analyses, showing that there are points of contact with this field. A separate chapter is dedicated to within-sentence word position; this issue considers grammar as well as language genesis; another chapter is dedicated to the type-token ratio, discussing all established methods and their relevance for word frequency analysis. All methods presented in the book are statistically tested; to this end, some new tests have been developed. All procedures and calculations are conducted for 20 languages, ranging from Polynesia, Indonesia, India, and Europe to a North American Indian language. The broad distribution of the data and texts from all genres allows generalizations with respect to language typology.
The frequency with which particular words are used in a text can tell us something meaningful both about that text and also about its author because their choice of words is seldom random. Focusing on the most frequent lexical items of a number of generated word frequency lists can help us to determine whether all the texts are written by the same author. Alternatively, they might wish to determine whether the most frequent words of a given text (captured by its word frequency list) are suggestive of potentially meaningful patterns that could have been overlooked had the text been read manually. This edited collection brings together cutting-edge research written by leading experts in the field on the construction of word-lists for the analysis of both frequency and keyword usage. Taken together, these papers provide a comprehensive and up-to-date survey of the most exciting research being conducted in this subject.
Natural Language Processing with Python by Steven Bird,Ewan Klein,Edward Loper Pdf
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
The Psycho-Biology Of Language by George Kingsley Zipf Pdf
This is Volume XXI in a series of twenty-one on the Cognitive Psychology. Orignally published in 1936, this is a study on the introduction to Dynamic Philology.
Statistics in Corpus Linguistics by Vaclav Brezina Pdf
A comprehensive and accessible introduction to statistics in corpus linguistics, covering multiple techniques of quantitative language analysis and data visualisation.
Author : Vito Pirrelli,Ingo Plag,Wolfgang U. Dressler Publisher : Walter de Gruyter GmbH & Co KG Page : 621 pages File Size : 45,7 Mb Release : 2020-04-20 Category : Language Arts & Disciplines ISBN : 9783110432442
Word Knowledge and Word Usage by Vito Pirrelli,Ingo Plag,Wolfgang U. Dressler Pdf
Word storage and processing define a multi-factorial domain of scientific inquiry whose thorough investigation goes well beyond the boundaries of traditional disciplinary taxonomies, to require synergic integration of a wide range of methods, techniques and empirical and experimental findings. The present book intends to approach a few central issues concerning the organization, structure and functioning of the Mental Lexicon, by asking domain experts to look at common, central topics from complementary standpoints, and discuss the advantages of developing converging perspectives. The book will explore the connections between computational and algorithmic models of the mental lexicon, word frequency distributions and information theoretical measures of word families, statistical correlations across psycho-linguistic and cognitive evidence, principles of machine learning and integrative brain models of word storage and processing. Main goal of the book will be to map out the landscape of future research in this area, to foster the development of interdisciplinary curricula and help single-domain specialists understand and address issues and questions as they are raised in other disciplines.
Text Mining with R by Julia Silge,David Robinson Pdf
Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.
Information Theory and Language by Łukasz Dębowski ,Christian Bentz Pdf
“Information Theory and Language” is a collection of 12 articles that appeared recently in Entropy as part of a Special Issue of the same title. These contributions represent state-of-the-art interdisciplinary research at the interface of information theory and language studies. They concern in particular: • Applications of information theoretic concepts such as Shannon and Rényi entropies, mutual information, and rate–distortion curves to the research of natural languages; • Mathematical work in information theory inspired by natural language phenomena, such as deriving moments of subword complexity or proving continuity of mutual information; • Empirical and theoretical investigation of quantitative laws of natural language such as Zipf’s law, Herdan’s law, and Menzerath–Altmann’s law; • Empirical and theoretical investigations of statistical language models, including recently developed neural language models, their entropies, and other parameters; • Standardizing language resources for statistical investigation of natural language; • Other topics concerning semantics, syntax, and critical phenomena. Whereas the traditional divide between probabilistic and formal approaches to human language, cultivated in the disjoint scholarships of natural sciences and humanities, has been blurred in recent years, this book can contribute to pointing out potential areas of future research cross-fertilization.
Blueprints for Text Analytics Using Python by Jens Albrecht,Sidharth Ramachandran,Christian Winkler Pdf
Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order. This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly. Extract data from APIs and web pages Prepare textual data for statistical analysis and machine learning Use machine learning for classification, topic modeling, and summarization Explain AI models and classification results Explore and visualize semantic similarities with word embeddings Identify customer sentiment in product reviews Create a knowledge graph based on named entities and their relations
Probabilistic Linguistics by Rens Bod,Jennifer Hay,Stefanie Jannedy Pdf
For the past forty years, linguistics has been dominated by the idea that language is categorical and linguistic competence discrete. It has become increasingly clear, however, that many levels of representation, from phonemes to sentence structure, show probabilistic properties, as does the language faculty. Probabilistic linguistics conceptualizes categories as distributions and views knowledge of language not as a minimal set of categorical constraints but as a set of gradient rules that may be characterized by a statistical distribution. Whereas categorical approaches focus on the endpoints of distributions of linguistic phenomena, probabilistic approaches focus on the gradient middle ground. Probabilistic linguistics integrates all the progress made by linguistics thus far with a probabilistic perspective. This book presents a comprehensive introduction to probabilistic approaches to linguistic inquiry. It covers the application of probabilistic techniques to phonology, morphology, semantics, syntax, language acquisition, psycholinguistics, historical linguistics, and sociolinguistics. It also includes a tutorial on elementary probability theory and probabilistic grammars.
