Detecting Texts
Detecting Texts

Author: Patricia Merivale

Publisher: University of Pennsylvania Press

Published: 2011-06-07

Total Pages: 316

ISBN-13: 0812205456

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Although readers of detective fiction ordinarily expect to learn the mystery's solution at the end, there is another kind of detective story—the history of which encompasses writers as diverse as Poe, Borges, Robbe-Grillet, Auster, and Stephen King—that ends with a question rather than an answer. The detective not only fails to solve the crime, but also confronts insoluble mysteries of interpretation and identity. As the contributors to Detecting Texts contend, such stories belong to a distinct genre, the "metaphysical detective story," in which the detective hero's inability to interpret the mystery inevitably casts doubt on the reader's similar attempt to make sense of the text and the world. Detecting Texts includes an introduction by the editors that defines the metaphysical detective story and traces its history from Poe's classic tales to today's postmodernist experiments. In addition to the editors, contributors include Stephen Bernstein, Joel Black, John T. Irwin, Jeffrey T. Nealon, and others.

Video Text Detection
Video Text Detection

Author: Tong Lu

Publisher: Springer

Published: 2014-07-23

Total Pages: 272

ISBN-13: 1447165152

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This book presents a systematic introduction to the latest developments in video text detection. Opening with a discussion of the underlying theory and a brief history of video text detection, the text proceeds to cover pre-processing and post-processing techniques, character segmentation and recognition, identification of non-English scripts, techniques for multi-modal analysis and performance evaluation. The detection of text from both natural video scenes and artificially inserted captions is examined. Various applications of the technology are also reviewed, from license plate recognition and road navigation assistance, to sports analysis and video advertising systems. Features: explains the fundamental theory in a succinct manner, supplemented with references for further reading; highlights practical techniques to help the reader understand and develop their own video text detection systems and applications; serves as an easy-to-navigate reference, presenting the material in self-contained chapters.

Text and Social Media Analytics for Fake News and Hate Speech Detection
Text and Social Media Analytics for Fake News and Hate Speech Detection

Author: Hemant Kumar Soni

Publisher: CRC Press

Published: 2024-08-21

Total Pages: 325

ISBN-13: 104010049X

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Identifying and stopping the dissemination of fabricated news, hate speech, or deceptive information camouflaged as legitimate news poses a significant technological hurdle. This book presents emergent methodologies and technological approaches of natural language processing through machine learning for counteracting the spread of fake news and hate speech on social media platforms. • Covers various approaches, algorithms, and methodologies for fake news and hate speech detection. • Explains the automatic detection and prevention of fake news and hate speech through paralinguistic clues on social media using artificial intelligence. • Discusses the application of machine learning models to learn linguistic characteristics of hate speech over social media platforms. • Emphasizes the role of multilingual and multimodal processing to detect fake news. • Includes research on different optimization techniques, case studies on the identification, prevention, and social impact of fake news, and GitHub repository links to aid understanding. The text is for professionals and scholars of various disciplines interested in fake news and hate speech detection.

Text Segmentation and Recognition for Enhanced Image Spam Detection
Text Segmentation and Recognition for Enhanced Image Spam Detection

Author: Mallikka Rajalingam

Publisher: Springer Nature

Published: 2020-08-10

Total Pages: 120

ISBN-13: 3030530477

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This book discusses email spam detection and its challenges such as text classification and categorization. The book proposes an efficient spam detection technique that is a combination of Character Segmentation and Recognition and Classification (CSRC). The author describes how this can detect whether an email (text and image based) is a spam mail or not. The book presents four solutions: first, to extract the text character from the image by segmentation process which includes a combination of Discrete Wavelet Transform (DWT) and skew detection. Second, text characters are via text recognition and visual feature extraction approach which relies on contour analysis with improved Local Binary Pattern (LBP). Third, extracted text features are classified using improvised K-Nearest Neighbor search (KNN) and Support Vector Machine (SVM). Fourth, the performance of the proposed method is validated by the measure of metric named as sensitivity, specificity, precision, recall, F-measure, accuracy, error rate and correct rate. Presents solutions to email spam detection and discusses its challenges such as text classification and categorization; Analyzes the proposed techniques’ performance using precision, F-measure, recall and accuracy; Evaluates the limitations of the proposed research thereby recommending future research.

Disinformation in Open Online Media
Disinformation in Open Online Media

Author: Davide Ceolin

Publisher: Springer Nature

Published: 2023-12-15

Total Pages: 204

ISBN-13: 3031478967

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This book constitutes the refereed proceedings of the 5th Multidisciplinary International Symposium on Disinformation in Open Online Media, MISDOOM 2023, which was held in Amsterdam, The Netherlands, during November 21–22, 2023. The 13 full papers presented in this book were carefully reviewed and selected from 19 submissions. The papers focus on misinformation, disinformation, hate speech, disinformation campaigns, social network analysis, large language models, generative AI, and multi-modal embeddings.

An Introduction to Signal Detection and Estimation
An Introduction to Signal Detection and Estimation

Author: H. Vincent Poor

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 558

ISBN-13: 1475738633

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The purpose of this book is to introduce the reader to the basic theory of signal detection and estimation. It is assumed that the reader has a working knowledge of applied probabil ity and random processes such as that taught in a typical first-semester graduate engineering course on these subjects. This material is covered, for example, in the book by Wong (1983) in this series. More advanced concepts in these areas are introduced where needed, primarily in Chapters VI and VII, where continuous-time problems are treated. This book is adapted from a one-semester, second-tier graduate course taught at the University of Illinois. However, this material can also be used for a shorter or first-tier course by restricting coverage to Chapters I through V, which for the most part can be read with a background of only the basics of applied probability, including random vectors and conditional expectations. Sufficient background for the latter option is given for exam pIe in the book by Thomas (1986), also in this series.

Document Image Processing
Document Image Processing

Author: Ergina Kavallieratou

Publisher: MDPI

Published: 2018-10-03

Total Pages: 217

ISBN-13: 3038971057

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This book is a printed edition of the Special Issue "Document Image Processing" that was published in J. Imaging

Natural Language Processing with Python
Natural Language Processing with Python

Author: Steven Bird

Publisher: "O'Reilly Media, Inc."

Published: 2009-06-12

Total Pages: 506

ISBN-13: 0596555717

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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.