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The Rape of the Lock and the Dunciad (Deseret Alphabet Edition)
Alexander Pope (1688-1744) was an English poet, best-known for his translation of Homer and other works in heroic couplets. He is the most-quoted English writer after William Shakespeare. The Rape of the Lock is a satiric poem and mock-epic, based on a scandal caused when a nobleman, Robert Petre, cut off a lock of Arabella Fermor's hair without her permission. By recounting the incident in the elevated style of Homer's epics, Pope trivializes it in the hopes of ending the schism between the two families. The Dunciad, another mock-epic, pillories many of the then-prominent but now-forgotten literary figures of the day by describing their devotion to the goddess Dulness. This book is in the Deseret Alphabet, a phonetic alphabet for writing English developed in the mid-19th century at the University of Deseret (now the University of Utah).
Sentic Computing
In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data.
Data Analysis in the Cloud
Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud. Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis. - Introduces data analysis techniques and cloud computing concepts - Describes cloud-based models and systems for Big Data analytics - Provides examples of the state-of-the-art in cloud data analysis - Explains how to develop large-scale data mining applications on clouds - Outlines the main research trends in the area of scalable Big Data analysis
Encyclopedia of Big Data Technologies
The Encyclopedia of Big Data Technologies provides researchers, educators, students and industry professionals with a comprehensive authority over the most relevant Big Data Technology concepts. With over 300 articles written by worldwide subject matter experts from both industry and academia, the encyclopedia covers topics such as big data storage systems, NoSQL database, cloud computing, distributed systems, data processing, data management, machine learning and social technologies, data science. Each peer-reviewed, highly structured entry provides the reader with basic terminology, subject overviews, key research results, application examples, future directions, cross references and a bibliography. The entries are expository and tutorial, making this reference a practical resource for students, academics, or professionals. In addition, the distinguished, international editorial board of the encyclopedia consists of well-respected scholars, each developing topics based upon their expertise.
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