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Machine Learning Techniques For Space Weather

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Machine Learning Techniques for Space Weather

Machine Learning Techniques for Space Weather Book
Author : Enrico Camporeale,Simon Wing,Jay Johnson
Publisher : Elsevier
Release : 2018-05-31
ISBN : 0128117893
Language : En, Es, Fr & De

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Book Description :

Machine Learning Techniques for Space Weather provides a thorough and accessible presentation of machine learning techniques that can be employed by space weather professionals. Additionally, it presents an overview of real-world applications in space science to the machine learning community, offering a bridge between the fields. As this volume demonstrates, real advances in space weather can be gained using nontraditional approaches that take into account nonlinear and complex dynamics, including information theory, nonlinear auto-regression models, neural networks and clustering algorithms. Offering practical techniques for translating the huge amount of information hidden in data into useful knowledge that allows for better prediction, this book is a unique and important resource for space physicists, space weather professionals and computer scientists in related fields. Collects many representative non-traditional approaches to space weather into a single volume Covers, in an accessible way, the mathematical background that is not often explained in detail for space scientists Includes free software in the form of simple MATLAB® scripts that allow for replication of results in the book, also familiarizing readers with algorithms

Engineering System Design for Automated Space Weather Forecast

Engineering System Design for Automated Space Weather Forecast Book
Author : Mohammad Hani Alomari
Publisher : Unknown
Release : 2009
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Coronal Mass Ejections (CMEs) and solar flares are energetic events taking place at the Sun that can affect the space weather or the near-Earth environment by the release of vast quantities of electromagnetic radiation and charged particles. Solar active regions are the areas where most flares and CMEs originate. Studying the associations among sunspot groups, flares, filaments, and CMEs is helpful in understanding the possible cause and effect relationships between these events and features. Forecasting space weather in a timely manner is important for protecting technological systems and human life on earth and in space. The research presented in this thesis introduces novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this work consists of three stages: (1) designing computer tools to find the associations among sunspot groups, flares, filaments, and CMEs (2) applying machine learning algorithms to the associations' datasets and (3) studying the evolution patterns of sunspot groups using time-series methods. Machine learning algorithms are used to provide computerised learning rules and models that enable the system to provide automated prediction of CMEs, flares, and evolution patterns of sunspot groups. These numerical rules are extracted from the characteristics, associations, and time-series analysis of the available historical solar data. The training of machine learning algorithms is based on data sets created by investigating the associations among sunspots, filaments, flares, and CMEs. Evolution patterns of sunspot areas and McIntosh classifications are analysed using a statistical machine learning method, namely the Hidden Markov Model (HMM).

Forecasting Space Weather Using Deep Learning Techniques

Forecasting Space Weather Using Deep Learning Techniques Book
Author : Sumi Dey
Publisher : Unknown
Release : 2018
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Forecasting Space Weather Using Deep Learning Techniques book written by Sumi Dey, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Machine Learning in Heliophysics

Machine Learning in Heliophysics Book
Author : Thomas Berger,Enrico Camporeale,Bala Poduval,Veronique A. Delouille,Sophie A. Murray
Publisher : Frontiers Media SA
Release : 2021-11-24
ISBN : 2889716716
Language : En, Es, Fr & De

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Book Description :

Download Machine Learning in Heliophysics book written by Thomas Berger,Enrico Camporeale,Bala Poduval,Veronique A. Delouille,Sophie A. Murray, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Magnetohydrodynamic Modeling of the Solar Corona and Heliosphere

Magnetohydrodynamic Modeling of the Solar Corona and Heliosphere Book
Author : Xueshang Feng
Publisher : Springer
Release : 2019-08-01
ISBN : 9811390819
Language : En, Es, Fr & De

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Book Description :

The book covers intimately all the topics necessary for the development of a robust magnetohydrodynamic (MHD) code within the framework of the cell-centered finite volume method (FVM) and its applications in space weather study. First, it presents a brief review of existing MHD models in studying solar corona and the heliosphere. Then it introduces the cell-centered FVM in three-dimensional computational domain. Finally, the book presents some applications of FVM to the MHD codes on spherical coordinates in various research fields of space weather, focusing on the development of the 3D Solar-InterPlanetary space-time Conservation Element and Solution Element (SIP-CESE) MHD model and its applications to space weather studies in various aspects. The book is written for senior undergraduates, graduate students, lecturers, engineers and researchers in solar-terrestrial physics, space weather theory, modeling, and prediction, computational fluid dynamics, and MHD simulations. It helps readers to fully understand and implement a robust and versatile MHD code based on the cell-centered FVM.

The Dynamical Ionosphere

The Dynamical Ionosphere Book
Author : Massimo Materassi,Biagio Forte,Anthea J. Coster,Susan Skone
Publisher : Elsevier
Release : 2019-11-28
ISBN : 0128147830
Language : En, Es, Fr & De

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Book Description :

The Dynamical Ionosphere: A Systems Approach to Ionospheric Irregularity examines the Earth’s ionosphere as a dynamical system with signatures of complexity. The system is robust in its overall configuration, with smooth space-time patterns of daily, seasonal and Solar Cycle variability, but shows a hierarchy of interactions among its sub-systems, yielding apparent unpredictability, space-time irregularity, and turbulence. This interplay leads to the need for constructing realistic models of the average ionosphere, incorporating the increasing knowledge and predictability of high variability components, and for addressing the difficulty of dealing with the worst cases of ionospheric disturbances, all of which are addressed in this interdisciplinary book. Borrowing tools and techniques from classical and stochastic dynamics, information theory, signal processing, fluid dynamics and turbulence science, The Dynamical Ionosphere presents the state-of-the-art in dealing with irregularity, forecasting ionospheric threats, and theoretical interpretation of various ionospheric configurations. Presents studies addressing Earth’s ionosphere as a complex dynamical system, including irregularities and radio scintillation, ionospheric turbulence, nonlinear time series analysis, space-ionosphere connection, and space-time structures Utilizes interdisciplinary tools and techniques, such as those associated with stochastic dynamics, information theory, signal processing, fluid dynamics and turbulence science Offers new data-driven models for different ionospheric variability phenomena Provides a synoptic view of the state-of-the-art and most updated theoretical interpretation, results and data analysis tools of the "worst case" behavior in ionospheric configurations

Space Physics and Aeronomy Magnetospheres in the Solar System

Space Physics and Aeronomy  Magnetospheres in the Solar System Book
Author : Romain Maggiolo,Nicolas André,Hiroshi Hasegawa,Daniel T. Welling
Publisher : John Wiley & Sons
Release : 2021-04-14
ISBN : 1119829984
Language : En, Es, Fr & De

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Book Description :

Überblick über den aktuellen Wissensstand und künftige Forschungsrichtungen in der Magnetosphärenphysik In den sechs Jahrzehnten seit der Einführung des Begriffs ?Magnetosphäre? sind über den magnetisierten Raum, der jeden Körper in unserem Sonnensystem umgibt, viele Theorien entstanden und viele Erkenntnisse gewonnen worden. Jede Magnetosphäre ist einzigartig und verhält sich doch entsprechend den universellen physikalischen Vorgängen. Der Band ?Magnetospheres in the Solar System? enthält Beiträge von Experten für Experimentalphysik, theoretische Physik und numerische Modellierung, die einen Überblick über verschiedene Magnetosphären vermitteln, von der winzigen Magnetosphäre des Merkur bis zu den gewaltigen planetarischen Magnetosphären von Jupiter und Saturn. Das Werk bietet insbesondere: * Einen kompakten Überblick über die Geschichte der Magnetosphäre, ihre Grundsätze und Gleichungen * Eine Zusammenfassung der grundlegenden Prozesse in der Magnetospährenphysik * Instrumente und Techniken zur Untersuchung von Prozessen in der Magnetosphäre * Eine besondere Schwerpunktsetzung auf die Magnetosphäre der Erde und ihre Dynamik * Eine Darstellung der planetaren Magnetfelder und Magnetosphären im gesamten Sonnensystem * Eine Definition der künftigen Forschungsrichtungen in der Magnetosphärenphysik Die Amerikanische Geophysikalische Vereinigung fördert die wissenschaftliche Erforschung der Erde und des Weltraums zum Wohle der Menschheit. In ihren Publikationen werden wissenschaftliche Erkenntnisse veröffentlicht, die Forschern, Studenten und Fachkräften zur Verfügung stehen.

Automated Prediction of Solar Flares

Automated Prediction of Solar Flares Book
Author : Tufan Colak,Rami Qahwaji
Publisher : LAP Lambert Academic Publishing
Release : 2010-07-01
ISBN : 9783838370309
Language : En, Es, Fr & De

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Book Description :

As we rely more on satellites, communication systems and space research, the importance of space weather is increasing continuously. There are many space missions and ground based observatories providing continuous observation of the Sun at many different wavelengths to supply the demand for space weather forecast and research. All the forecasting strategies highly depend on experience of solar physicists and done manually. The results differ from observatories to observatories and subjective. There is a need for automated analysis of Sun and space weather forecasting. The solar activity is the driver of space weather. Thus it is important to be able to predict the violent eruptions such as coronal mass ejections and solar flares. In this book a hybrid system combining image processing and machine learning techniques for the automated short-term prediction of solar flares is presented. The system can also detect, group, and classify sunspots using solar images. The algorithms, implementation, and results are explained in this work.

Space Physics and Aeronomy Solar Physics and Solar Wind

Space Physics and Aeronomy  Solar Physics and Solar Wind Book
Author : Angelos Vourlidas,Nour E. Raouafi
Publisher : John Wiley & Sons
Release : 2021-04-14
ISBN : 1119815487
Language : En, Es, Fr & De

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Book Description :

A comprehensive view of our Sun at the start of a new era in solar and heliospheric physics Humans have been observing and studying our Sun for centuries, yet much is still unknown about the processes that drive its behavior. Thanks to a new generation of space missions and ground telescopes, we are poised to dramatically increase our understanding of the Sun and its environment. Solar Physics and Solar Wind explores advances in solar and heliospheric research over recent decades, as well as the challenges that remain. This comprehensive reference work covers the solar interior, magnetism and radiation, plasma heating and acceleration, the sun's atmosphere, and solar activity. Volume highlights include: Explanations for processes in the solar interior New insights on the solar wind The challenges of measuring the Sun's magnetic field and its radiative output Description of solar atmospheric phenomena such as spicules and jets New developments in understanding flares and coronal mass ejections Ongoing research into how the solar corona is heated The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. Find out more about the Space Physics and Aeronomy collection in this Q&A with the Editors in Chief

Advances in Computational Intelligence

Advances in Computational Intelligence Book
Author : Ignacio Rojas,Gonzalo Joya,Andreu Catala
Publisher : Springer
Release : 2019-06-05
ISBN : 3030205215
Language : En, Es, Fr & De

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Book Description :

This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, held at Gran Canaria, Spain, in June 2019. The 150 revised full papers presented in this two-volume set were carefully reviewed and selected from 210 submissions. The papers are organized in topical sections on machine learning in weather observation and forecasting; computational intelligence methods for time series; human activity recognition; new and future tendencies in brain-computer interface systems; random-weights neural networks; pattern recognition; deep learning and natural language processing; software testing and intelligent systems; data-driven intelligent transportation systems; deep learning models in healthcare and biomedicine; deep learning beyond convolution; artificial neural network for biomedical image processing; machine learning in vision and robotics; system identification, process control, and manufacturing; image and signal processing; soft computing; mathematics for neural networks; internet modeling, communication and networking; expert systems; evolutionary and genetic algorithms; advances in computational intelligence; computational biology and bioinformatics.

Hands On Big Data Modeling

Hands On Big Data Modeling Book
Author : James Lee,Tao Wei,Suresh Kumar Mukhiya
Publisher : Packt Publishing Ltd
Release : 2018-11-30
ISBN : 1788626087
Language : En, Es, Fr & De

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Book Description :

Big data modeling is very challenging to handle using traditional database modeling and management systems. This book will teach you how to model big data using the latest and more efficient tools such as ERWIN, ANACONDA (Python), and WEKA to model data.

Evolution in Computational Intelligence

Evolution in Computational Intelligence Book
Author : Vikrant Bhateja
Publisher : Springer Nature
Release : 2021-12-06
ISBN : 9811557888
Language : En, Es, Fr & De

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Book Description :

Download Evolution in Computational Intelligence book written by Vikrant Bhateja, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Intelligence Science and Big Data Engineering Big Data and Machine Learning Techniques

Intelligence Science and Big Data Engineering  Big Data and Machine Learning Techniques Book
Author : Xiaofei He,Xinbo Gao,Yanning Zhang,Zhi-Hua Zhou,Zhi-Yong Liu,Baochuan Fu,Fuyuan Hu,Zhancheng Zhang
Publisher : Springer
Release : 2015-10-13
ISBN : 3319238620
Language : En, Es, Fr & De

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Book Description :

The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.

Enhanced Flare Prediction by Advanced Feature Extraction from Solar Images

Enhanced Flare Prediction by Advanced Feature Extraction from Solar Images Book
Author : Omar Wahab Ahmed
Publisher : Unknown
Release : 2012
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Space weather has become an international issue due to the catastrophic impactit can have on modern societies. Solar flares are one of the major solar activities thatdrive space weather and yet their occurrence is not fully understood. Research isrequired to yield a better understanding of flare occurrence and enable the developmentof an accurate flare prediction system, which can warn industries most at risk to takepreventative measures to mitigate or avoid the effects of space weather. This thesisintroduces novel technologies developed by combining advances in statistical physics, image processing, machine learning, and feature selection algorithms, with advances insolar physics in order to extract valuable knowledge from historical solar data, related toactive regions and flares. The aim of this thesis is to achieve the followings: i) Thedesign of a new measurement, inspired by the physical Ising model, to estimate themagnetic complexity in active regions using solar images and an investigation of thismeasurement in relation to flare occurrence. The proposed name of the measurement isthe Ising Magnetic Complexity (IMC). ii) Determination of the flare predictioncapability of active region properties generated by the new active region detectionsystem SMART (Solar Monitor Active Region Tracking) to enable the design of a newflare prediction system. iii) Determination of the active region properties that are mostrelated to flare occurrence in order to enhance understanding of the underlying physicsbehind flare occurrence. The achieved results can be summarised as follows: i) The newactive region measurement (IMC) appears to be related to flare occurrence and it has apotential use in predicting flare occurrence and location. ii) Combining machinelearning with SMART's active region properties has the potential to provide moreaccurate flare predictions than the current flare prediction systems i.e. ASAP(Automated Solar Activity Prediction). iii) Reduced set of 6 active region propertiesseems to be the most significant properties related to flare occurrence and they canachieve similar degree of flare prediction accuracy as the full 21 SMART active regionproperties. The developed technologies and the findings achieved in this thesis willwork as a corner stone to enhance the accuracy of flare prediction; develop efficientflare prediction systems; and enhance our understanding of flare occurrence. Thealgorithms, implementation, results, and future work are explained in this thesis.

Soft Computing in Industrial Applications

Soft Computing in Industrial Applications Book
Author : Ashraf Saad,Erel Avineri,Keshav Dahal,Muhammad Sarfraz,Rajkumar Roy
Publisher : Springer Science & Business Media
Release : 2007-08-07
ISBN : 3540707069
Language : En, Es, Fr & De

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Book Description :

Here is a collection of papers presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006. This carefully edited book provides a comprehensive overview of recent advances in the industrial applications of soft computing and covers a wide range of application areas, including data analysis and data mining, computer graphics, intelligent control, systems, pattern recognition, classifiers, as well as modeling optimization.

Progress Toward Implementation of the 2013 Decadal Survey for Solar and Space Physics

Progress Toward Implementation of the 2013 Decadal Survey for Solar and Space Physics Book
Author : National Academies of Sciences, Engineering, and Medicine,Division on Engineering and Physical Sciences,Space Studies Board,Committee on the Review of Progress Toward Implementing the Decadal Survey â¬" Solar and Space Physics: A Science for a Technological Society
Publisher : National Academies Press
Release : 2020-06-29
ISBN : 0309671302
Language : En, Es, Fr & De

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Book Description :

The 2013 report Solar and Space Physics; A Science for a Technological Society outlined a program of basic and applied research for the period 2013-2022. This publication describes the most significant scientific discoveries, technical advances, and relevant programmatic changes in solar and space physics since the publication of that decadal survey. Progress Toward Implementation of the 2013 Decadal Survey for Solar and Space Physics assesses the degree to which the programs of the National Science Foundation and the National Aeronautics and Space Administration address the strategies, goals, and priorities outlined in the 2013 decadal survey, and the progress that has been made in meeting those goals. This report additionally considers steps to enhance career opportunities in solar and space physics and recommends actions that should be undertaken to prepare for the next decadal survey.

Machine Learning and Data Mining in Aerospace Technology

Machine Learning and Data Mining in Aerospace Technology Book
Author : Aboul Ella Hassanien,Ashraf Darwish,Hesham El-Askary
Publisher : Springer
Release : 2019-07-02
ISBN : 3030202127
Language : En, Es, Fr & De

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Book Description :

This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the ‘eagle eyes’ that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites – which can determine satellites’ current status and predict their failure based on telemetry data – is one of the most important current issues in aerospace engineering. This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.

Solar Image Analysis and Visualization

Solar Image Analysis and Visualization Book
Author : Jack Ireland,C. Alex Young
Publisher : Springer Science & Business Media
Release : 2009-08-27
ISBN : 0387981543
Language : En, Es, Fr & De

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Book Description :

The SECCHI A and B instrument suites (Howard et al. , 2006) onboard the two STEREO mission spacecraft (Kaiser, 2005) are each composed of: one Extreme Ultra-Violet Imager (EUVI), two white-light coronagraphs (COR1 and COR2), and two wide-angle heliospheric imagers (HI1 and HI2). Technical descriptions of EUVI, COR1 and the HIs can be found in Wuelser et al. (2004), Thompson et al. (2003), and De?se et al. (2003), respectively. The images produced by SECCHI represent a data visualization challenge: i) the images are 2048×2048 pixels (except for the HIs, which are usually binned onboard 2×2), thus the vast majority of computer displays are not able to display them at full frame and full r- olution, and ii) more importantly, the ?ve instruments of SECCHI A and B were designed to be able to track Coronal Mass Ejections from their onset (with EUVI) to their pro- gation in the heliosphere (with the HIs), which implies that a set of SECCHI images that covers the propagation of a CME from its initiation site to the Earth is composed of im- ?1 ages with very different spatial resolutions – from 1. 7 arcsecondspixel for EUVI to 2. 15 ?1 arcminutespixel for HI2, i. e. 75 times larger. A similar situation exists with the angular scales of the physical objects, since the size of a CME varies by orders of magnitude as it expands in the heliosphere.

Deep Learning for the Earth Sciences

Deep Learning for the Earth Sciences Book
Author : Gustau Camps-Valls,Devis Tuia,Xiao Xiang Zhu,Markus Reichstein
Publisher : John Wiley & Sons
Release : 2021-08-18
ISBN : 1119646162
Language : En, Es, Fr & De

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Book Description :

DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.

Recommender Systems Handbook

Recommender Systems Handbook Book
Author : Francesco Ricci,Lior Rokach,Bracha Shapira
Publisher : Springer
Release : 2015-11-17
ISBN : 148997637X
Language : En, Es, Fr & De

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Book Description :

This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.