Natural Language Processing with Python

Social media is an invaluable source of time-critical information during a crisis. However, emergency response and humanitarian relief organizations that would like to use this information struggle with an avalanche of social media messages that exceeds the human capacity to process. Emergency managers, decision makers, and affected communities can make sense of social media through a combination of machine computation and human compassion - expressed by thousands of digital volunteers who publish, process, and summarize potentially life-saving information. This book brings together computational methods from many disciplines: natural language processing, semantic technologies, data mining, machine learning, network analysis, human-computer interaction, and information visualization, focusing on methods that are commonly used for processing social media messages under time-critical constraints, and offering more than 500 references to in-depth information.

Essentials of Programming in Mathematica® provides an introduction suitable for readers with little or no background in the language as well as for those with some experience using programs such as C, Java, or Perl. The author, an established authority on Mathematica® programming, has written an example-driven text that covers the language from first principles, as well as including material from natural language processing, bioinformatics, graphs and networks, signal analysis, geometry, computer science, and many other applied areas. The book is appropriate for self-study or as a text for a course in programming in computational science. Readers will benefit from the author's tips, which provide insight and suggestions on small and large points. He also provides more than 350 exercises from novice through to advanced level with all of the solutions available online.

This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less well defined or where student-system interactions are less structured, such as during scenario-based simulation and immersive serious games. In order to address how to expand the reach of adaptive training technology to these domains, leading experts in the field present their work in areas such as student modeling, pedagogical strategy, knowledge assessment, natural language processing and virtual human agents. Several approaches to designing adaptive technology are discussed for both traditional educational settings and professional training domains. This book will appeal to anyone concerned with educational and training technology at a profess

The book is intended for lectures on string processes and pattern matching in Master's courses of computer science and software engineering curricula. The details of algorithms are given with correctness proofs and complexity analysis, which make them ready to implement. Algorithms are described in a C-like language. The book is also a reference for students in computational linguistics or computational biology. It presents examples of questions related to the automatic processing of natural language, to the analysis of molecular sequences, and to the management of textual databases.

This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less well defined or where student-system interactions are less structured, such as during scenario-based simulation and immersive serious games. In order to address how to expand the reach of adaptive training technology to these domains, leading experts in the field present their work in areas such as student modeling, pedagogical strategy, knowledge assessment, natural language processing and virtual human agents. Several approaches to designing adaptive technology are discussed for both traditional educational settings and professional training domains. This book will appeal to anyone concerned with educational and training technology at a profess

Yorick Wilks is a central figure in the fields of Natural Language Processing and Artificial Intelligence. This set consists of a volume of selected papers and a volume with contributions from his pee

The book is intended for lectures on string processes and pattern matching in Master's courses of computer science and software engineering curricula. The details of algorithms are given with correctness proofs and complexity analysis, which make them ready to implement. Algorithms are described in a C-like language. The book is also a reference for students in computational linguistics or computational biology. It presents examples of questions related to the automatic processing of natural language, to the analysis of molecular sequences, and to the management of textual databases.

This book unites speech act theory and conversation analysis to advance a theory of conversational competence. It is predicated on the assumption that speech act theory, if it is to be of genuine empirical and theoretical significance, must be embedded within a general theory of conversational competence capable of accounting for how we do things with words in naturally occurring conversation, and it can usefully be seen as a synthesis of traditional speech act theory, conversation analysis, and artificial intelligence research in natural language processing. Michael L. Geis analyses a variety of naturally occurring conversations, presenting them within a framework of computational interest and within discourse representation theory. In particular, he offers an explicit mapping of semantic and pragmatic (i.e. speech-act-theoretic) meaning features and politeness features into so-called conventionalized indirect speech act forms.

A series of important applications of combinatorics on words has emerged with the development of computerized text and string processing. The aim of this volume, the third in a trilogy, is to present a unified treatment of some of the major fields of applications. After an introduction that sets the scene and gathers together the basic facts, there follow chapters in which applications are considered in detail. The areas covered include core algorithms for text processing, natural language processing, speech processing, bioinformatics, and areas of applied mathematics such as combinatorial enumeration and fractal analysis. No special prerequisites are needed, and no familiarity with the application areas or with the material covered by the previous volumes is required. The breadth of application, combined with the inclusion of problems and algorithms and a complete bibliography will make this book ideal for graduate students and professionals in mathematics, computer science, biology a

Information retrieval, IR, the science of extracting information from any potential source, can be viewed in a number of ways: logical, probabilistic and vector space models are some of the most important. In this book, the author, one of the leading researchers in the area, shows how these views can be reforged in the same framework used to formulate the general principles of quantum mechanics. All the usual quantum-mechanical notions have their IR-theoretic analogues, and the standard results can be applied to address problems in IR, such as pseudo-relevance feedback, relevance feedback and ostensive retrieval. The relation with quantum computing is also examined. To keep the book self-contained appendices with background material on physics and mathematics are included. Each chapter ends with bibliographic remarks that point to further reading. This is an important, ground-breaking book, with much new material, for all those working in IR, AI and natural language processing.

This book unites speech act theory and conversation analysis to advance a theory of conversational competence. It is predicated on the assumption that speech act theory, if it is to be of genuine empirical and theoretical significance, must be embedded within a general theory of conversational competence capable of accounting for how we do things with words in naturally occurring conversation, and it can usefully be seen as a synthesis of traditional speech act theory, conversation analysis, and artificial intelligence research in natural language processing. Michael L. Geis analyses a variety of naturally occurring conversations, presenting them within a framework of computational interest and within discourse representation theory. In particular, he offers an explicit mapping of semantic and pragmatic (i.e. speech-act-theoretic) meaning features and politeness features into so-called conventionalized indirect speech act forms.

A hands-on, code-based guide to leveraging Julia in a variety of scientific and data-driven scenarios Key Features: Augment your basic computing skills with an in-depth introduction to JuliaFocus on topic-based approaches to scientific problems and visualisationBuild on prior knowledge of programming languages such as Python, R, or C/C++Purchase of the print or Kindle book includes a free PDF eBook Book Description: Julia is a well-constructed programming language which was designed for fast execution speed by using just-in-time LLVM compilation techniques, thus eliminating the classic problem of performing analysis in one language and translating it for performance in a second.This book is a primer on Julia's approach to a wide variety of topics such as scientific computing, statistics, machine learning, simulation, graphics, and distributed computing.Starting off with a refresher on installing and running Julia on different platforms, you'll quickly get to grips with the core concept

Cognitive Models of Speech Processing presents extensive reviews of current thinking on psycholinguistic and computational topics in speech recognition and natural-language processing, along with a su

Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting se

不會艱深晦澀、不再高深莫測 你一定能看懂的自然語言處理入門書！ INTRODUCTION TO NATURAL LANGUAGE PROCESSING ♘Java與Python雙實作：圖文並茂！演算法、數學公式、程式碼相輔相成。 ♘探索式學習路徑：循序漸進！從問題、演算法再到範例實作，一目瞭然。 編輯推薦 作者匯集多年經驗，從基本概念出發，逐步介紹中文分詞、詞性標註、命名實體識別、資訊抽取、文字聚類、文字分類、句法分析這幾個熱門問題的演算法原理與工程實作。透過講解多種演算法，比較它們的優缺點與適用場景，同時詳細展示實際專案導向的程式碼，協助讀者真正將自然語言處理（NLP）應用到正式環境之中。 儘管作者目前是NLP領域的翹楚，但他曾是非本科生，對自學入門有親身體驗，深諳初學者的學習痛點。希望透過這本與眾不同的入門讀物，為讀者打開另一扇機會之門，幫助你零起點上手NLP，讓你在通勤時也能把書讀完讀懂！ 隨著本書的學習，你將從普通程式設計師晉級為機器學習工程師，最後進化為NLP工程師。 專家好評 HanLP作者何晗寫的這本書值得一讀。這本書系統性地介紹NLP的基礎技術，深入淺出、容易理解，對初學者助益極大。 周明 微軟亞洲研究院副院長，國際計算語言學會會長 本書不僅介紹NLP的任務及演算法，也提供可以實際執行的線上程式碼，非常適合NLP初學者入門並快速部署到正式環境。 王斌 小米人工智慧實驗室主任、NLP首席科學家