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Even the magically inclined know werewolves don’t exist. So why is her new rescue dog suddenly taking human form? When Meredith Townsend finds a dog locked in a basement at a madman's compound, her magic immediately senses a lie. She knows it isn't simply a dog, but she never expects a werewolf—since everyone knows they don't exist. But not only does this rescue "dog" take human form, he happens to be none other than Jensen King, the man she had a torridly hot affair with—before he disappeared without a trace. Now he needs Meredith's help to find his sister—and the other Shifters stolen from his enclave—before they're sold to the highest bidder at an underground magical auction. If Meredith and Jensen fail, war looms on the horizon between Aspect and Shifter societies. If they succeed, do two people from such a different background have a chance at making love work?
Webster offers a comprehensive summarizing work of major teachings of the Bible in a very user-friendly format. This quick and easy guide to Bible teachings is ideal for discipling new believers, for use in small groups, and many more applications. (Christian)
This book offers detailed surveys and systematic discussion of models, algorithms and applications for link mining, focusing on theory and technique, and related applications: text mining, social network analysis, collaborative filtering and bioinformatics.
This book presents the latest research on computational approaches to learning. It includes high-quality peer-reviewed papers from the “Intelligent and Interactive Computing Conference (IIC 2018)” organized by the Universiti Teknikal Malaysia, Melaka. It uses empirical studies, theoretical analysis, and comparisons with psychological phenomena to show how learning methods can be employed to solve important application problems. The book also describes ongoing research in various research labs, universities and institutions, which may lead to the development of marketable products.
The three-volume set constitutes the proceedings of the 17th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2022, which was held during November 24th-26th, 2022. The conference took place in Dalian, China.The 95 full and 62 short papers presented in these proceedings were carefully reviewed and selected from 265 submissions. The contributions in cyber-physical systems including intelligent transportation systems and smart healthcare systems; security and privacy; topology control and coverage; energy-efficient algorithms, systems and protocol design
Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individuals. The title offers theoretical foundations to support emerging data-driven cyber-physical applications and touches on key issues such as privacy. The authors present solutions based on recent research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion. Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability Presents novel theoretical foundations for assured social sensing and modeling humans as sensors Includes case studies and application examples based on real data sets Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book
This book constitutes the refereed proceedings of the twelfth International Conference, on Discovery Science, DS 2009, held in Porto, Portugal, in October 2009. The 35 revised full papers presented were carefully selected from 92 papers. The scope of the conference includes the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their applications.
On the Web, a massive amount of user-generated content is available through various channels (e.g., texts, tweets, Web tables, databases, multimedia-sharing platforms, etc.). Conflicting information, rumors, erroneous and fake content can be easily spread across multiple sources, making it hard to distinguish between what is true and what is not. This book gives an overview of fundamental issues and recent contributions for ascertaining the veracity of data in the era of Big Data. The text is organized into six chapters, focusing on structured data extracted from texts. Chapter 1 introduces the problem of ascertaining the veracity of data in a multi-source and evolving context. Issues related to information extraction are presented in Chapter 2. Current truth discovery computation algorithms are presented in details in Chapter 3. It is followed by practical techniques for evaluating data source reputation and authoritativeness in Chapter 4. The theoretical foundations and various approaches for modeling diffusion phenomenon of misinformation spreading in networked systems are studied in Chapter 5. Finally, truth discovery computation from extracted data in a dynamic context of misinformation propagation raises interesting challenges that are explored in Chapter 6. This text is intended for a seminar course at the graduate level. It is also to serve as a useful resource for researchers and practitioners who are interested in the study of fact-checking, truth discovery, or rumor spreading.
This book constitutes the proceedings of the 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, held in Gold Coast, Australia, in December 2016. The 70 papers presented in this volume were carefully reviewed and selected from 105 submissions. The selected papers covered a wide variety of important topics in the area of data mining, including parallel and distributed data mining algorithms, mining on data streams, graph mining, spatial data mining, multimedia data mining, Web mining, the Internet of Things, health informatics, and biomedical data mining.