This book constitutes the thoroughly refereed proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015, held in Lisbon, Portugal, in November 2015. The 25 full papers presented together with 2 invited papers were carefully reviewed and selected from 280 submissions. The papers are organized in topical sections on knowledge discovery and information retrieval; knowledge engineering and ontology development; and knowledge management and information sharing.

This book constitutes the proceedings of the Third International Conference on Internet of Things (IoT) Technologies for HealthCare, HealthyIoT 2016, held in Vasteras, Sweden, October 18-19, 2016. The conference also included the First Workshop on Emerging eHealth through Internet of Things (EHIoT 2016). IoT as a set of existing and emerging technologies, notions and services provides many solutions to delivery of electronic healthcare, patient care, and medical data management. The 31 revised full papers presented along with 9 short papers were carefully reviewed and selected from 43 submissions in total. The papers cover topics such as healthcare support for the elderly, real-time monitoring systems, security, safety and communication, smart homes and smart caring environments, intelligent data processing and predictive algorithms in e-Health, emerging eHealth IoT applications, signal processing and analysis, and smartphones as a healthy thing.

This book constitutes the proceedings of the 5th International Conference on Analysis of Images, Social Networks and Texts, AIST 2016, held in Yekaterinburg, Russia, in April 2016. The 23 full papers, 7 short papers, and 3 industrial papers were carefully reviewed and selected from 142 submissions. The papers are organized in topical sections on machine learning and data analysis; social networks; natural language processing; analysis of images and video.

This book constitutes the refereed proceedings of the Third International Workshop on Management of Information, Process and Cooperation, MiPAC 2016, held in Hangzhou, China, in September 2016. The 8 revised full papers were carefully reviewed and selected from 14 submissions. The papers are organized in topical sections on process modeling, process enactment, and data driven service computing.

This book constitutes revised proceedings of the 17th International Conference on E-Commerce and Web Technologies, EC-Web 2016, held in Porto, Portugal, in September 2016, in conjunction with DEXA. The 13 papers presented in this volume were carefully reviewed and selected from 21 submissions. They were organized in topical sections named: recommender systems; data management and data analysis; and business processes, Web services and cloud computing.

The two-volume set LNCS 10132 and 10133 constitutes the thoroughly refereed proceedings of the 23rd International Conference on Multimedia Modeling, MMM 2017, held in Reykjavik, Iceland, in January 2017. Of the 149 full papers submitted, 36 were selected for oral presentation and 33 for poster presentation; of the 34 special session papers submitted, 24 were selected for oral presentation and 2 for poster presentation; in addition, 5 demonstrations were accepted from 8 submissions, and all 7 submissions to VBS 2017. All papers presented were carefully reviewed and selected from 198 submissions. MMM is a leading international conference for researchers and industry practitioners for sharing new ideas, original research results and practical development experiences from all MMM related areas, broadly falling into three categories: multimedia content analysis; multimedia signal processing and communications; and multimedia applications and services.

Learn to use Apache Pig to develop lightweight big data applications easily and quickly. This book shows you many optimization techniques and covers every context where Pig is used in big data analytics. Beginning Apache Pig shows you how Pig is easy to learn and requires relatively little time to develop big data applications.The book is divided into four parts: the complete features of Apache Pig; integration with other tools; how to solve complex business problems; and optimization of tools.You'll discover topics such as MapReduce and why it cannot meet every business need; the features of Pig Latin such as data types for each load, store, joins, groups, and ordering; how Pig workflows can be created; submitting Pig jobs using Hue; and working with Oozie. You'll also see how to extend the framework by writing UDFs and custom load, store, and filter functions. Finally you'll cover different optimization techniques such as gathering statistics about a Pig script, joining strategies, parallelism, and the role of data formats in good performance. What You Will Learn* Use all the features of Apache Pig* Integrate Apache Pig with other tools* Extend Apache Pig* Optimize Pig Latin code* Solve different use cases for Pig LatinWho This Book Is ForAll levels of IT professionals: architects, big data enthusiasts, engineers, developers, and big data administrators

This volume addresses the emerging area of human computation, The chapters, written by leading international researchers, explore existing and future opportunities to combine the respective strengths of both humans and machines in order to create powerful problem-solving capabilities. The book bridges scientific communities, capturing and integrating the unique perspective and achievements of each. It coalesces contributions from industry and across related disciplines in order to motivate, define, and anticipate the future of this exciting new frontier in science and cultural evolution. Readers can expect to find valuable contributions covering Foundations; Application Domains; Techniques and Modalities; Infrastructure and Architecture; Algorithms; Participation; Analysis; Policy and Security and the Impact of Human Computation. Researchers and professionals will find the Handbook of Human Computation a valuable reference tool. The breadth of content also provides a thorough foundation for students of the field.

This book constitutes the refereed post-conference proceedings of the First International Workshop on Spectral and Shape Analysis in Medical Imaging, SeSAMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The 10 submitted full papers presented in this volume were carefully reviewed. The papers reflect the following topics: spectral methods; longitudinal methods; and shape methods.

The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, September 29th, 2016. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.

This book constitutes the refereed proceedings of the 51st Annual Convention of the Computer Society of India, CSI 2016, held in Coimbatore, India, in December 2016. The 23 revised papers presented were carefully reviewed and selected from 74 submissions. The theme of CSI 2016, Digital Connectivity - Social Impact, has been selected to highlight the importance of technology in solving social problems and thereby creating a long term impact on society. The papers are organized in topical sections on information science; computational intelligence; network computing; IT for society.

This book provides a comprehensive introduction and practical look at the concepts and techniques readers need to get the most out of their data in real-world, large-scale data mining projects. It also guides readers through the data-analytic thinking necessary for extracting useful knowledge and business value from the data. The book is based on the Soft Computing and Data Mining (SCDM-16) conference, which was held in Bandung, Indonesia on August 18th-20th 2016 to discuss the state of the art in soft computing techniques, and offer participants sufficient knowledge to tackle a wide range of complex systems. The scope of the conference is reflected in the book, which presents a balance of soft computing techniques and data mining approaches. The two constituents are introduced to the reader systematically and brought together using different combinations of applications and practices. It offers engineers, data analysts, practitioners, scientists and managers the insights into the concepts, tools and techniques employed, and as such enables them to better understand the design choice and options of soft computing techniques and data mining approaches that are necessary to thrive in this data-driven ecosystem.

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 29th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains four revised selected regular papers. Topics covered include optimization and cluster validation processes for entity matching, business intelligence systems, and data profiling in the Semantic Web.

The papers in this volume are the refereed papers presented at AI-2016, the Thirty-sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2016 in both the technical and the application streams. They present new and innovative developments and applications, divided into technical stream sections on Knowledge Discovery and Data Mining, Sentiment Analysis and Recommendation, Machine Learning, AI Techniques, and Natural Language Processing, followed by application stream sections on AI for Medicine and Disability, Legal Liability and Finance, Telecoms and eLearning, and Genetic Algorithms in Action. The volume also includes the text of short papers presented as posters at the conference. This is the thirty-third volume in the Research and Development in Intelligent Systems series, which also incorporates the twenty-fourth volume in the Applications and Innovations in Intelligent Systems series. These series are essential reading for those who wish to keep up to date with developments in this important field.

This book constitutes the refereed proceedings of the 10th Metadata and Semantics Research Conference, MTSR 2016, held in Goettingen, Germany, in November 2016. The 26 full papers and 6 short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in several sessions and tracks: Digital Libraries, Information Retrieval, Linked and Social Data, Metadata and Semantics for Open Repositories, Research Information Systems and Data Infrastructures, Metadata and Semantics for Agriculture, Food and Environment, Metadata and Semantics for Cultural Collections and Applications, European and National Projects.

The two-volume set CCIS 662 and CCIS 663 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition, CCPR 2016, held in Chengdu, China, in November 2016.The 121 revised papers presented in two volumes were carefully reviewed and selected from 199 submissions. The papers are organized in topical sections on robotics; computer vision; basic theory of pattern recognition; image and video processing; speech and language; emotion recognition.

This volume provides a comprehensive introduction to the Translation Process Research Database (TPR-DB), which was compiled by the Centre for Research and Innovation in Translation and Technologies (CRITT). The TPR-DB is a unique resource featuring more than 500 hours of recorded translation process data, augmented with over 200 different rich annotations. Twelve chapters describe the diverse research directions this data can support, including the computational, statistical and psycholinguistic modeling of human translation processes.In the first chapters of this book, the reader is introduced to the CRITT TPR-DB. This is followed by two main parts, the first of which focuses on usability issues and details of implementing interactive machine translation. It also discusses the use of external resources and translator-information interaction. The second part addresses the cognitive and statistical modeling of human translation processes, including co-activation at the lexical, syntactic and discourse levels, translation literality, and various annotation schemata for the data.

This book constitutes the refereed proceedings of the Second International Conference on Technologies and Innovation, CITI 2016, held in Guayaquil, Ecuador, in November 2016. The 21 revised full papers presented were carefully reviewed and selected from 65 submissions. The papers are organized in topical sections on knowledge representation and natural language processing; Cloud and mobile computing; software engineering; expert systems and soft computing.

This book explores how PPPM, clinical practice, and basic research could be best served by information technology (IT). A use-case was developed for hepatocellular carcinoma (HCC). The subject was approached with four interrelated tasks: (1) review of clinical practices relating to HCC; (2) propose an IT system relating to HCC, including clinical decision support and research needs; (3) determine how a clinical liver cancer center can contribute; and, (4) examine the enhancements and impact that the first three tasks will have on the management of HCC. An IT System for Personalized Medicine (ITS-PM) for HCC will provide the means to identify and determine the relative value of the wide number of variables, including clinical assessment of the patient -- functional status, liver function, degree of cirrhosis, and comorbidities; tumor biology, at a molecular, genetic and anatomic level; tumor burden and individual patient response; medical and operative treatments and their outcomes.

This book constitutes the refereed proceedings of the 17th International Symposium, KSS 2016, held in Kobe, Japan, in November 2016. The 21 revised full papers presented were carefully reviewed and selected from 48 submissions. The papers cover topics such as: Algorithms for Big Data; Big Data and education; Big Data and healthcare; Big Data and tourism; Big Data and social media oriented knowledge discovery and data mining, text mining, recommendation system, etc; Big Data, social media and societal management; creation of agent-based social systems sciences; collective intelligence; complex system modeling and complexity; decision analysis and decision support systems; internet+ and agriculture; internet+ and open innovation; knowledge creation, creativity support, awareness support, etc.; knowledge systems engineering and knowledge management; meta-synthesis and advanced modeling; opinion dynamics and opinion mining; OR on knowledge and systems sciences; problem structuring methods and system methodologies toward wicked problems; service systems science; smart city; social dynamic network modeling; Web intelligence.

The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23-25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.

This book constitutes the thoroughly refereed post conference proceedings of the third edition of the Semantic Web Evaluation Challenge, SemWebEval 2016, co-located with the 13th European Semantic Web conference, held in Heraklion, Crete, Greece, in May/June 2016. This book includes the descriptions of all methods and tools that competed at SemWebEval 2016, together with a detailed description of the tasks, evaluation procedures and datasets. The contributions are grouped in the areas: Open Knowledge Extraction (OKE 2016); Semantic Sentiment Analysis (SSA 2016); Question Answering over Linked Data (QALD 6); Top-K Shortest Path in Large Typed RDF Graphs Datasets; Semantic Publishing (SemPub2016).

This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to communities of open source software developers, biometric template generation as well as analysis of user behavior within heterogeneous environments of cultural educational centers. Addressing these challenging applications is what makes this edited volume of interest to researchers and students focused on social media and social network analysis.

This carefully edited and reviewed volume addresses the increasingly popular demand for seeking more clarity in the data that we are immersed in. It offers excellent examples of the intelligent ubiquitous computation, as well as recent advances in systems engineering and informatics. The content represents state-of-the-art foundations for researchers in the domain of modern computation, computer science, system engineering and networking, with many examples that are set in industrial application context. The book includes the carefully selected best contributions to APCASE 2014, the 2nd Asia-Pacific Conference on Computer Aided System Engineering, held February 10-12, 2014 in South Kuta, Bali, Indonesia. The book consists of four main parts that cover data-oriented engineering science research in a wide range of applications: computational models and knowledge discovery; communications networks and cloud computing; computer-based systems; and data-oriented and software-intensive systems.

Prevalent types of data in scientific visualization are volumetric data, vector field data, and particle-based data. Particle data typically originates from measurements and simulations in various fields, such as life sciences or physics. The particles are often visualized directly, that is, by simple representants like spheres. Interactive rendering facilitates the exploration and visual analysis of the data. With increasing data set sizes in terms of particle numbers, interactive high-quality visualization is a challenging task. This is especially true for dynamic data or abstract representations that are based on the raw particle data. This book covers direct particle visualization using simple glyphs as well as abstractions that are application-driven such as clustering and aggregation. It targets visualization researchers and developers who are interested in visualization techniques for large, dynamic particle-based data. Its explanations focus on GPU-accelerated algorithms for high-performance rendering and data processing that run in real-time on modern desktop hardware. Consequently, the implementation of said algorithms and the required data structures to make use of the capabilities of modern graphics APIs are discussed in detail. Furthermore, it covers GPU-accelerated methods for the generation of application-dependent abstract representations. This includes various representations commonly used in application areas such as structural biology, systems biology, thermodynamics, and astrophysics.