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Large-scale, highly interconnected networks, which are often
modeled as graphs, pervade both our society and the natural world
around us. Uncertainty, on the other hand, is inherent in the
underlying data due to a variety of reasons, such as noisy
measurements, lack of precise information needs, inference and
prediction models, or explicit manipulation, e.g., for privacy
purposes. Therefore, uncertain, or probabilistic, graphs are
increasingly used to represent noisy linked data in many emerging
application scenarios, and they have recently become a hot topic in
the database and data mining communities. Many classical algorithms
such as reachability and shortest path queries become #P-complete
and, thus, more expensive over uncertain graphs. Moreover, various
complex queries and analytics are also emerging over uncertain
networks, such as pattern matching, information diffusion, and
influence maximization queries. In this book, we discuss the
sources of uncertain graphs and their applications, uncertainty
modeling, as well as the complexities and algorithmic advances on
uncertain graphs processing in the context of both classical and
emerging graph queries and analytics. We emphasize the current
challenges and highlight some future research directions.
Smart Metro Station Systems: Data Science and Engineering
introduces key technologies in data science and engineering for
smart metro station systems. The book consists of three main parts,
focusing on the environment, people and energy. Each chapter
includes practical applications, along with information on metro
traffic flow monitoring and passenger guidance, methods for
behavior analysis and trajectory projection, clustering and anomaly
detection in crowd hotspots, monitoring and prediction for station
humidity, monitoring and spatial prediction for air pollutants,
time series feature extraction and analysis of metro load,
characteristic and correlation analysis of metro load, and
prediction and intelligent ventilation control. This volume offers
a key reference on the emerging area of smart metro stations and
will be useful to those working on smart railways, data science,
engineering, artificial intelligence and aligned fields.
The second edition of Idea Searching examines methods of generating
and identifying ideas, and teaches you to understand what is being
observed and recorded. Using lavish illustrations, concise case
studies and practical examples, it explores how different
experiences, contexts and references are important in identifying
an idea that is appropriate for a particular individual, target
audience or culture. Advocating a step-by-step approach to
generating ideas and brainstorming, it encourages an open mind in
the development of ideas and teaches you to always question
convention. The text is accompanied by a variety of case studies
and examples of work from the world's best contemporary product
designers. It also includes a number of new projects for students,
to encourage further exploration of ideas.
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Health Information Science - 5th International Conference, HIS 2016, Shanghai, China, November 5-7, 2016, Proceedings (Paperback, 1st ed. 2016)
Xiaoxia Yin, James Geller, Ye Li, Rui Zhou, Hua Wang, …
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R2,182
Discovery Miles 21 820
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 5th
International Conference on Health Information Science, HIS 2016,
held in Shanghai, China, in November 2016. The 13 full papers and 9
short papers presented were carefully reviewed and selected from
numerous submissions. The scope of the papers includes
medical/health/biomedicine information resources such as patient
medical records, devices and equipments, software and tools to
capture, store, retrieve, process, analyze, and optimize the use of
information in the health domain; data management, data mining, and
knowledge discovery, all of which play a key role in decision
making, management of public health, examination of standards,
privacy and security issues; computer visualization and artificial
intelligence for computer aided diagnosis; development of new
architectures and applications for health information systems.
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