Automatic Detection Of Verbal Deception
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Automatic Detection Of Verbal Deception
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Author : Eileen Fitzpatrick
language : en
Publisher: Springer
Release Date : 2015-09-01
Automatic Detection Of Verbal Deception written by Eileen Fitzpatrick and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-01 with Computers categories.
The attempt to spot deception through its correlates in human behavior has a long history. Until recently, these efforts have concentrated on identifying individual "cues" that might occur with deception. However, with the advent of computational means to analyze language and other human behavior, we now have the ability to determine whether there are consistent clusters of differences in behavior that might be associated with a false statement as opposed to a true one. While its focus is on verbal behavior, this book describes a range of behaviors—physiological, gestural as well as verbal—that have been proposed as indicators of deception. An overview of the primary psychological and cognitive theories that have been offered as explanations of deceptive behaviors gives context for the description of specific behaviors. The book also addresses the differences between data collected in a laboratory and "real-world" data with respect to the emotional and cognitive state of the liar. It discusses sources of real-world data and problematic issues in its collection and identifies the primary areas in which applied studies based on real-world data are critical, including police, security, border crossing, customs, and asylum interviews; congressional hearings; financial reporting; legal depositions; human resource evaluation; predatory communications that include Internet scams, identity theft, and fraud; and false product reviews. Having established the background, this book concentrates on computational analyses of deceptive verbal behavior that have enabled the field of deception studies to move from individual cues to overall differences in behavior. The computational work is organized around the features used for classification from -gram through syntax to predicate-argument and rhetorical structure. The book concludes with a set of open questions that the computational work has generated.
Automatic Detection Of Verbal Deception
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Author : Eileen Fitzpatrick
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Automatic Detection Of Verbal Deception written by Eileen Fitzpatrick and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
The attempt to spot deception through its correlates in human behavior has a long history. Until recently, these efforts have concentrated on identifying individual "cues" that might occur with deception. However, with the advent of computational means to analyze language and other human behavior, we now have the ability to determine whether there are consistent clusters of differences in behavior that might be associated with a false statement as opposed to a true one. While its focus is on verbal behavior, this book describes a range of behaviors—physiological, gestural as well as verbal—that have been proposed as indicators of deception. An overview of the primary psychological and cognitive theories that have been offered as explanations of deceptive behaviors gives context for the description of specific behaviors. The book also addresses the differences between data collected in a laboratory and "real-world" data with respect to the emotional and cognitive state of the liar. It discusses sources of real-world data and problematic issues in its collection and identifies the primary areas in which applied studies based on real-world data are critical, including police, security, border crossing, customs, and asylum interviews; congressional hearings; financial reporting; legal depositions; human resource evaluation; predatory communications that include Internet scams, identity theft, and fraud; and false product reviews. Having established the background, this book concentrates on computational analyses of deceptive verbal behavior that have enabled the field of deception studies to move from individual cues to overall differences in behavior. The computational work is organized around the features used for classification from -gram through syntax to predicate-argument and rhetorical structure. The book concludes with a set of open questions that the computational work has generated.
The Palgrave Handbook Of Deceptive Communication
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Author : Tony Docan-Morgan
language : en
Publisher: Springer
Release Date : 2019-04-29
The Palgrave Handbook Of Deceptive Communication written by Tony Docan-Morgan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-29 with Psychology categories.
Deception and truth-telling weave through the fabric of nearly all human interactions and every communication context. The Palgrave Handbook of Deceptive Communication unravels the topic of lying and deception in human communication, offering an interdisciplinary and comprehensive examination of the field, presenting original research, and offering direction for future investigation and application. Highly prominent and emerging deception scholars from around the world investigate the myriad forms of deceptive behavior, cross-cultural perspectives on deceit, moral dimensions of deceptive communication, theoretical approaches to the study of deception, and strategies for detecting and deterring deceit. Truth-telling, lies, and the many grey areas in-between are explored in the contexts of identity formation, interpersonal relationships, groups and organizations, social and mass media, marketing, advertising, law enforcement interrogations, court, politics, and propaganda. Thishandbook is designed for advanced undergraduate and graduate students, academics, researchers, practitioners, and anyone interested in the pervasive nature of truth, deception, and ethics in the modern world.
A Practical Guide To Sentiment Analysis
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Author : Erik Cambria
language : en
Publisher: Springer
Release Date : 2017-04-07
A Practical Guide To Sentiment Analysis written by Erik Cambria and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-07 with Medical categories.
Sentiment analysis research has been started long back and recently it is one of the demanding research topics. Research activities on Sentiment Analysis in natural language texts and other media are gaining ground with full swing. But, till date, no concise set of factors has been yet defined that really affects how writers’ sentiment i.e., broadly human sentiment is expressed, perceived, recognized, processed, and interpreted in natural languages. The existing reported solutions or the available systems are still far from perfect or fail to meet the satisfaction level of the end users. The reasons may be that there are dozens of conceptual rules that govern sentiment and even there are possibly unlimited clues that can convey these concepts from realization to practical implementation. Therefore, the main aim of this book is to provide a feasible research platform to our ambitious researchers towards developing the practical solutions that will be indeed beneficial for our society, business and future researches as well.
Neural Network Methods For Natural Language Processing
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Author : Yoav Goldberg
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Neural Network Methods For Natural Language Processing written by Yoav Goldberg and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
Linked Lexical Knowledge Bases
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Author : Iryna Gurevych
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Linked Lexical Knowledge Bases written by Iryna Gurevych and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
This book conveys the fundamentals of Linked Lexical Knowledge Bases (LLKB) and sheds light on their different aspects from various perspectives, focusing on their construction and use in natural language processing (NLP). It characterizes a wide range of both expert-based and collaboratively constructed lexical knowledge bases. Only basic familiarity with NLP is required and this book has been written for both students and researchers in NLP and related fields who are interested in knowledge-based approaches to language analysis and their applications. Lexical Knowledge Bases (LKBs) are indispensable in many areas of natural language processing, as they encode human knowledge of language in machine readable form, and as such, they are required as a reference when machines attempt to interpret natural language in accordance with human perception. In recent years, numerous research efforts have led to the insight that to make the best use of available knowledge, the orchestrated exploitation of different LKBs is necessary. This allows us to not only extend the range of covered words and senses, but also gives us the opportunity to obtain a richer knowledge representation when a particular meaning of a word is covered in more than one resource. Examples where such an orchestrated usage of LKBs proved beneficial include word sense disambiguation, semantic role labeling, semantic parsing, and text classification. This book presents different kinds of automatic, manual, and collaborative linkings between LKBs. A special chapter is devoted to the linking algorithms employing text-based, graph-based, and joint modeling methods. Following this, it presents a set of higher-level NLP tasks and algorithms, effectively utilizing the knowledge in LLKBs. Among them, you will find advanced methods, e.g., distant supervision, or continuous vector space models of knowledge bases (KB), that have become widely used at the time of this book's writing. Finally, multilingual applications of LLKB's, such as cross-lingual semantic relatedness and computer-aided translation are discussed, as well as tools and interfaces for exploring LLKBs, followed by conclusions and future research directions.
Bayesian Analysis In Natural Language Processing
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Author : Shay Cohen
language : en
Publisher: Springer Nature
Release Date : 2022-11-10
Bayesian Analysis In Natural Language Processing written by Shay Cohen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-10 with Computers categories.
Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate for various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples. We cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we cover some of the fundamental modeling techniques in NLP, such as grammar modeling and their use with Bayesian analysis.
Domain Sensitive Temporal Tagging
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Author : Jannik Strötgen
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Domain Sensitive Temporal Tagging written by Jannik Strötgen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
This book covers the topic of temporal tagging, the detection of temporal expressions and the normalization of their semantics to some standard format. It places a special focus on the challenges and opportunities of domain-sensitive temporal tagging. After providing background knowledge on the concept of time, the book continues with a comprehensive survey of current research on temporal tagging. The authors provide an overview of existing techniques and tools, and highlight key issues that need to be addressed. This book is a valuable resource for researchers and application developers who need to become familiar with the topic and want to know the recent trends, current tools and techniques, as well as different application domains in which temporal information is of utmost importance. Due to the prevalence of temporal expressions in diverse types of documents and the importance of temporal information in any information space, temporal tagging is an important task in natural language processing (NLP), and applications of several domains can benefit from the output of temporal taggers to provide more meaningful and useful results. In recent years, temporal tagging has been an active field in NLP and computational linguistics. Several approaches to temporal tagging have been proposed, annotation standards have been developed, gold standard data sets have been created, and research competitions have been organized. Furthermore, some temporal taggers have also been made publicly available so that temporal tagging output is not just exploited in research, but is finding its way into real world applications. In addition, this book particularly focuses on domain-specific temporal tagging of documents. This is a crucial aspect as different types of documents (e.g., news articles, narratives, and colloquial texts) result in diverse challenges for temporal taggers and should be processed in a domain-sensitive manner.
Metaphor
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Author : Tony Veale
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Metaphor written by Tony Veale and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
The literary imagination may take flight on the wings of metaphor, but hard-headed scientists are just as likely as doe-eyed poets to reach for a metaphor when the descriptive need arises. Metaphor is a pervasive aspect of every genre of text and every register of speech, and is as useful for describing the inner workings of a "black hole" (itself a metaphor) as it is the affairs of the human heart. The ubiquity of metaphor in natural language thus poses a significant challenge for Natural Language Processing (NLP) systems and their builders, who cannot afford to wait until the problems of literal language have been solved before turning their attention to figurative phenomena. This book offers a comprehensive approach to the computational treatment of metaphor and its figurative brethren—including simile, analogy, and conceptual blending—that does not shy away from their important cognitive and philosophical dimensions. Veale, Shutova, and Beigman Klebanov approach metaphor from multiple computational perspectives, providing coverage of both symbolic and statistical approaches to interpretation and paraphrase generation, while also considering key contributions from philosophy on what constitutes the "meaning" of a metaphor. This book also surveys available metaphor corpora and discusses protocols for metaphor annotation. Any reader with an interest in metaphor, from beginning researchers to seasoned scholars, will find this book to be an invaluable guide to what is a fascinating linguistic phenomenon.
Computer Vision And Image Processing
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Author : Neeta Nain
language : en
Publisher: Springer Nature
Release Date : 2020-03-28
Computer Vision And Image Processing written by Neeta Nain and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-28 with Computers categories.
This two-volume set (CCIS 1147, CCIS 1148) constitutes the refereed proceedings of the 4th International Conference on Computer Vision and Image Processing. held in Jaipur, India, in September 2019. The 73 full papers and 10 short papers were carefully reviewed and selected from 202 submissions. The papers are organized by the topical headings in two parts. Part I: Biometrics; Computer Forensic; Computer Vision; Dimension Reduction; Healthcare Information Systems; Image Processing; Image segmentation; Information Retrieval; Instance based learning; Machine Learning.Part II: Neural Network; Object Detection; Object Recognition; Online Handwriting Recognition; Optical Character Recognition; Security and Privacy; Unsupervised Clustering.