Download or read book Practical Natural Language Processing written by Sowmya Vajjala and published by O'Reilly Media. This book was released on 2020-06-17 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective

Download or read book Mining Text Data written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2012-02-03 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

Download or read book Learning to Classify Text Using Support Vector Machines written by Thorsten Joachims and published by Springer Science & Business Media. This book was released on 2002-04-30 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes with a learning theory that can guide real-world applications. Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a statistical learning model of text classification. In addition, it includes an overview of the field of text classification, making it self-contained even for newcomers to the field. This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning.

Download or read book Text Mining written by Ashok N. Srivastava and published by CRC Press. This book was released on 2009-06-15 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the FieldGiving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify te

Download or read book Text Classification Method Review written by A. Mahinovs and published by . This book was released on 2005 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Innovative Data Communication Technologies and Application written by Jennifer S. Raj and published by Springer Nature. This book was released on 2021-02-02 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research in the fields of computational intelligence, ubiquitous computing models, communication intelligence, communication security, machine learning, informatics, mobile computing, cloud computing and big data analytics. The best selected papers, presented at the International Conference on Innovative Data Communication Technologies and Application (ICIDCA 2020), are included in the book. The book focuses on the theory, design, analysis, implementation and applications of distributed systems and networks.

Download or read book Text Mining written by Gabe Ignatow and published by SAGE Publications. This book was released on 2016-04-20 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online communities generate massive volumes of natural language data and the social sciences continue to learn how to best make use of this new information and the technology available for analyzing it. Text Mining brings together a broad range of contemporary qualitative and quantitative methods to provide strategic and practical guidance on analyzing large text collections. This accessible book, written by a sociologist and a computer scientist, surveys the fast-changing landscape of data sources, programming languages, software packages, and methods of analysis available today. Suitable for novice and experienced researchers alike, the book will help readers use text mining techniques more efficiently and productively.

Download or read book Proceedings of the Second International Conference on Soft Computing for Problem Solving SocProS 2012 December 28 30 2012 written by B. V. Babu and published by Springer. This book was released on 2014-07-08 with total page 1529 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present book is based on the research papers presented in the International Conference on Soft Computing for Problem Solving (SocProS 2012), held at JK Lakshmipat University, Jaipur, India. This book provides the latest developments in the area of soft computing and covers a variety of topics, including mathematical modeling, image processing, optimization, swarm intelligence, evolutionary algorithms, fuzzy logic, neural networks, forecasting, data mining, etc. The objective of the book is to familiarize the reader with the latest scientific developments that are taking place in various fields and the latest sophisticated problem solving tools that are being developed to deal with the complex and intricate problems that are otherwise difficult to solve by the usual and traditional methods. The book is directed to the researchers and scientists engaged in various fields of Science and Technology.

Download or read book Advances in Information Retrieval written by David E. Losada and published by Springer. This book was released on 2005-04-01 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to Santiago de Compostela! We are pleased to host the 27th Annual EuropeanConferenceonInformationRetrievalResearch(ECIR2005)onits?rst visit to Spain. These proceedings contain the refereed full papers and poster abstracts p- sented at ECIR 2005. This conference was initially established by the Infor- tion Retrieval Specialist Group of the British Computer Society (BCS-IRSG) under the name “Annual Colloquium on Information Retrieval Research. ” The colloquium was held in the United Kingdom each year until 1998, when the event was organized in Grenoble, France. Since then the conference venue has alternated between the United Kingdom and Continental Europe, re?ecting the growing European orientation of ECIR. For the same reason, in 2001 the event was renamed “European Conference on Information Retrieval Research. ” In - cent years, ECIR has continued to grow and has become the major European forum for the discussion of research in the ?eld of information retrieval. ECIR 2005 was held at the Technical School of Engineering of the University of Santiago de Compostela, Spain. In terms of submissions, ECIR 2005 was a record-breaking success, since 124 full papers were submitted in response to the call for papers. This was a sharp increase from the 101 submissions received for ECIR 2003, which was the most successful ECIR in terms of submissions. ECIR 2005 established also a call for posters, and 41 posters where submitted. Paper and poster submissions were received from across Europe and further a?eld, including North America, South America, Asia and Australia, which is a clear indicationofthegrowingpopularityandreputationoftheconference.

Download or read book Natural Language Processing for Social Media written by Atefeh Farzindar and published by Morgan & Claypool Publishers. This book was released on 2017-12-15 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, healthcare, business intelligence, industry, marketing, and security and defence. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, virtual reality, and social networking. In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.

Download or read book Deep Learning with R written by François Chollet and published by Simon and Schuster. This book was released on 2018-01-22 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. Continue your journey into the world of deep learning with Deep Learning with R in Motion, a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/deep-​learning-with-r-in-motion). Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. Deep-learning systems now enable previously impossible smart applications, revolutionizing image recognition and natural-language processing, and identifying complex patterns in data. The Keras deep-learning library provides data scientists and developers working in R a state-of-the-art toolset for tackling deep-learning tasks. About the Book Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. Initially written for Python as Deep Learning with Python by Keras creator and Google AI researcher François Chollet and adapted for R by RStudio founder J. J. Allaire, this book builds your understanding of deep learning through intuitive explanations and practical examples. You'll practice your new skills with R-based applications in computer vision, natural-language processing, and generative models. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image classification and generation Deep learning for text and sequences About the Reader You'll need intermediate R programming skills. No previous experience with machine learning or deep learning is assumed. About the Authors François Chollet is a deep-learning researcher at Google and the author of the Keras library. J.J. Allaire is the founder of RStudio and the author of the R interfaces to TensorFlow and Keras. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions

Download or read book Linguistic Inquiry and Word Count written by James W. Pennebaker and published by Lawrence Erlbaum Assoc Incorporated. This book was released on 1999-04-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Language, whether spoken or written, is an important window into people's emotional and cognitive worlds. Text analysis of these narratives, focusing on specific words or classes of words, has been used in numerous research studies including studies of emotional, cognitive, structural, and process components of individuals' verbal and written language. It was in this research context that the LIWC program was developed. The program analyzes text files on a word-by-word basis, calculating percentage words that match each of several language dimensions. Its output is a text file that can be opened in any of a variety of applications, including word processors and spreadsheet programs. The program has 68 pre-set dimensions (output variables) including linguistic dimensions, word categories tapping psychological constructs, and personal concern categories, and can accommodate user-defined dimensions as well. Easy to install and use, this software offers researchers in social, personality, clinical, and applied psychology a valuable tool for quantifying the rich but often slippery data provided in the form of personal narratives. The software comes complete on one 31/2 diskette and runs on any Windows-based computer.

Download or read book Deep Learning for Natural Language Processing written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2017-11-21 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning methods are achieving state-of-the-art results on challenging machine learning problems such as describing photos and translating text from one language to another. In this new laser-focused Ebook, finally cut through the math, research papers and patchwork descriptions about natural language processing. Using clear explanations, standard Python libraries and step-by-step tutorial lessons you will discover what natural language processing is, the promise of deep learning in the field, how to clean and prepare text data for modeling, and how to develop deep learning models for your own natural language processing projects.

Download or read book Survey of Text Mining written by Michael W. Berry and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.

Download or read book Feature Extraction written by Isabelle Guyon and published by Springer. This book was released on 2008-11-16 with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction. Until now there has been insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons.

Download or read book Rebooting AI written by Gary Marcus and published by Vintage. This book was released on 2019-09-10 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.

Download or read book Advanced Classification Techniques for Healthcare Analysis written by Chakraborty, Chinmay and published by IGI Global. This book was released on 2019-02-22 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical and information communication technology professionals are working to develop robust classification techniques, especially in healthcare data/image analysis, to ensure quick diagnoses and treatments to patients. Without fast and immediate access to healthcare databases and information, medical professionals’ success rates and treatment options become limited and fall to disastrous levels. Advanced Classification Techniques for Healthcare Analysis provides emerging insight into classification techniques in delivering quality, accurate, and affordable healthcare, while also discussing the impact health data has on medical treatments. Featuring coverage on a broad range of topics such as early diagnosis, brain-computer interface, metaheuristic algorithms, clustering techniques, learning schemes, and mobile telemedicine, this book is ideal for medical professionals, healthcare administrators, engineers, researchers, academicians, and technology developers seeking current research on furthering information and communication technology that improves patient care.