The proceedings of the 5th International Workshop on Parallel Tools for High Performance Computing provide an overview on supportive software tools and environments in the fields of System Management, Parallel Debugging and Performance Analysis. In the pursuit to maintain exponential growth for the performance of high performance computers the HPC community is currently targeting Exascale Systems. The initial planning for Exascale already started when the first Petaflop system was delivered. Many challenges need to be addressed to reach the necessary performance. Scalability, energy efficiency and fault-tolerance need to be increased by orders of magnitude. The goal can only be achieved when advanced hardware is combined with a suitable software stack. In fact, the importance of software is rapidly growing. As a result, many international projects focus on the necessary software.

This book constitutes the thoroughly refereed conference proceedings of the 9th International Conference on Rough Sets and Knowledge Technology, RSKT 2014, held in Shanghai, China, in October 2014. The 70 papers presented were carefully reviewed and selected from 162 submissions. The papers in this volume cover topics such as foundations and generalizations of rough sets, attribute reduction and feature selection, applications of rough sets, intelligent systems and applications, knowledge technology, domain-oriented data-driven data mining, uncertainty in granular computing, advances in granular computing, big data to wise decisions, rough set theory, and three-way decisions, uncertainty, and granular computing.

This book constitutes the refereed proceedings of the Workshops held at the 8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2012, in Halkidiki, Greece, in September 2012. The book includes a total of 66 interesting and innovative research papers from the following 8 workshops: the Second Artificial Intelligence Applications in Biomedicine Workshop (AIAB 2012), the First AI in Education Workshop: Innovations and Applications (AIeIA 2012), the Second International Workshop on Computational Intelligence in Software Engineering (CISE 2012), the First Conformal Prediction and Its Applications Workshop (COPA 2012), the First Intelligent Innovative Ways for Video-to-Video Communiccation in Modern Smart Cities Workshop (IIVC 2012), the Third Intelligent Systems for Quality of Life Information Services Workshop (ISQL 2012), the First Mining Humanistic Data Workshop (MHDW 2012), and the First Workshop on Algorithms for Data and Text Mining in Bioinformatics (WADTMB 2012).

Statistics and hypothesis testing are routinely used in areas (such as linguistics) that are traditionally not mathematically intensive. In such fields, when faced with experimental data, many students and researchers tend to rely on commercial packages to carry out statistical data analysis, often without understanding the logic of the statistical tests they rely on. As a consequence, results are often misinterpreted, and users have difficulty in flexibly applying techniques relevant to their own research - they use whatever they happen to have learned. A simple solution is to teach the fundamental ideas of statistical hypothesis testing without using too much mathematics. This book provides a non-mathematical, simulation-based introduction to basic statistical concepts and encourages readers to try out the simulations themselves using the source code and data provided (the freely available programming language R is used throughout). Since the code presented in the text almost always requires the use of previously introduced programming constructs, diligent students also acquire basic programming abilities in R. The book is intended for advanced undergraduate and graduate students in any discipline, although the focus is on linguistics, psychology, and cognitive science. It is designed for self-instruction, but it can also be used as a textbook for a first course on statistics. Earlier versions of the book have been used in undergraduate and graduate courses in Europe and the US. "Vasishth and Broe have written an attractive introduction to the foundations of statistics. It is concise, surprisingly comprehensive, self-contained and yet quite accessible. Highly recommended." Harald Baayen, Professor of Linguistics, University of Alberta, Canada "By using the text students not only learn to do the specific things outlined in the book, they also gain a skill set that empowers them to explore new areas that lie beyond the book's coverage." Colin Phillips, Professor of Linguistics, University of Maryland, USA

This book constitutes the refereed conference proceedings of the 13th International Conference on Intelligent Data Analysis, which was held in October/November 2014 in Leuven, Belgium. The 33 revised full papers together with 3 invited papers were carefully reviewed and selected from 70 submissions handling all kinds of modeling and analysis methods, irrespective of discipline. The papers cover all aspects of intelligent data analysis, including papers on intelligent support for modeling and analyzing data from complex, dynamical systems.

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques - genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries. The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.

This book constitutes the thoroughly revised selected papers of the 4th and 5th workshops on Big Data Benchmarks, Performance Optimization, and Emerging Hardware, BPOE 4 and BPOE 5, held respectively in Salt Lake City, in March 2014, and in Hangzhou, in September 2014. The 16 papers presented were carefully reviewed and selected from 30 submissions. Both workshops focus on architecture and system support for big data systems, such as benchmarking; workload characterization; performance optimization and evaluation; emerging hardware.

Data mining applications range from commercial to social domains, with novel applications appearing swiftly; for example, within the context of social networks. The expanding application sphere and social reach of advanced data mining raise pertinent issues of privacy and security. Present-day data mining is a progressive multidisciplinary endeavor. This inter- and multidisciplinary approach is well reflected within the field of information systems. The information systems research addresses software and hardware requirements for supporting computationally and data-intensive applications. Furthermore, it encompasses analyzing system and data aspects, and all manual or automated activities. In that respect, research at the interface of information systems and data mining has significant potential to produce actionable knowledge vital for corporate decision-making. The aim of the proposed volume is to provide a balanced treatment of the latest advances and developments in data mining; in particular, exploring synergies at the intersection with information systems. It will serve as a platform for academics and practitioners to highlight their recent achievements and reveal potential opportunities in the field. Thanks to its multidisciplinary nature, the volume is expected to become a vital resource for a broad readership ranging from students, throughout engineers and developers, to researchers and academics.

This book constitutes revised post-proceedings of the 4th International Symposium on Pervasive Computing Paradigms for Mental Health, MindCare 2014, held in Tokyo, Japan, in May 2014. The 11 full and 5 short papers presented were carefully reviewed and selected from 26 submissions for inclusion in the proceedings. The papers are organized in topical sections on recognition and assessment, mental health management, improving communication, depression, and self-applied treatments.

This book constitutes the proceedings of the 11th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2014, held in Tokyo, Japan, in October 2014. The 19 revised full papers presented together with an invited paper were carefully reviewed and selected from 38 submissions. They deal with the theory and tools for modeling decisions, as well as applications that encompass decision making processes and information fusion techniques and are organized in topical sections on aggregation operators and decision making, optimization, clustering and similarity, and data mining and data privacy.

Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.

This book constitutes the refereed proceedings of the Second International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2014, held in Cairo, Egypt, in November 2014. The 49 full papers presented were carefully reviewed and selected from 101 initial submissions. The papers are organized in topical sections on machine learning in Arabic text recognition and assistive technology; recommendation systems for cloud services; machine learning in watermarking/authentication and virtual machines; features extraction and classification; rough/fuzzy sets and applications; fuzzy multi-criteria decision making; Web-based application and case-based reasoning construction; social networks and big data sets.

"Foundations of Large-Scale Multimedia Information Management and Retrieval: Mathematics of Perception" covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and multimodal fusion. Part II - Scalability Issues presents indexing and distributed methods for scaling up these components for high-dimensional data and Web-scale datasets. The book presents some real-world applications and remarks on future research and development directions. The book is designed for researchers, graduate students, and practitioners in the fields of Computer Vision, Machine Learning, Large-scale Data Mining, Database, and Multimedia Information Retrieval. Dr. Edward Y. Chang was a professor at the Department of Electrical & Computer Engineering, University of California at Santa Barbara, before he joined Google as a research director in 2006. Dr. Chang received his M.S. degree in Computer Science and Ph.D degree in Electrical Engineering, both from Stanford University.

This book is about inductive databases and constraint-based data mining, emerging research topics lying at the intersection of data mining and database research. The aim of the book as to provide an overview of the state-of- the art in this novel and - citing research area. Of special interest are the recent methods for constraint-based mining of global models for prediction and clustering, the uni?cation of pattern mining approaches through constraint programming, the clari?cation of the re- tionship between mining local patterns and global models, and the proposed in- grative frameworks and approaches for inducive databases. On the application side, applications to practically relevant problems from bioinformatics are presented. Inductive databases (IDBs) represent a database view on data mining and kno- edge discovery. IDBs contain not only data, but also generalizations (patterns and models) valid in the data. In an IDB, ordinary queries can be used to access and - nipulate data, while inductive queries can be used to generate (mine), manipulate, and apply patterns and models. In the IDB framework, patterns and models become "?rst-class citizens" and KDD becomes an extended querying process in which both the data and the patterns/models that hold in the data are queried.

This book constitutes the tutorial lectures of the 4th European Business Intelligence Summer School, eBISS 2014, held in Berlin, Germany, in July 2014. The tutorials presented here in an extended and refined format were given by renowned experts and cover topics including requirements engineering for decision-support systems, visual analytics of large data sets, linked data and semantic technologies, supervised classification on data streams, and knowledge reuse in large organizations.

This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination. Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection. This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.

This book constitutes the refereed proceedings of the workshops held at the 16th Asia-Pacific Web Conference, APWeb 2014, in Changsha, China, in September 2014. The 34 full papers were carefully reviewed and selected from 59 submissions. This volume presents the papers that have been accepted for the following workshops: First International Workshop on Social Network Analysis, SNA 2014; First International Workshop on Network and Information Security, NIS 2014; First International Workshop on Internet of Things Search, IoTS 2014. The papers cover various issues in social network analysis, security and information retrieval against the heterogeneous big data.

This book constitutes the refereed proceedings of the 16th Asia-Pacific Conference APWeb 2014 held in Changsha, China, in September 2014. The 34 full papers and 23 short papers presented were carefully reviewed and selected from 134 submissions. The papers address research, development and advanced applications of large-scale data management, web and search technologies, and information processing.

This book constitutes the proceedings of the 15th International Conference on Web Information Systems Engineering, WISE 2014, held in Thessaloniki, Greece, in October 2014. The 52 full papers, 16 short and 14 poster papers, presented in the two-volume proceedings LNCS 8786 and 8787 were carefully reviewed and selected from 196 submissions. They are organized in topical sections named: Web mining, modeling and classification; Web querying and searching; Web recommendation and personalization; semantic Web; social online networks; software architectures amd platforms; Web technologies and frameworks; Web innovation and applications; and challenge.

This book constitutes the proceedings of the 21st International Symposium on String Processing and Information Retrieval, SPIRE 2014, held in Ouro Preto, Brazil, in October 2014. The 20 full and 6 short papers included in this volume were carefully reviewed and selected from 45 submissions. The papers focus not only on fundamental algorithms in string processing and information retrieval, but address also application areas such as computational biology, Web mining and recommender systems. They are organized in topical sections on compression, indexing, genome and related topics, sequences and strings, search, as well as on mining and recommending.

This book constitutes the refereed proceedings of the 8th International Conference on Web Reasoning and Rule Systems, RR 2014, held in Athens, Greece in September 2014. The 9 full papers, 9 technical communications and 5 poster presentations presented together with 3 invited talks, 3 doctoral consortial papers were carefully reviewed and selected from 33 submissions. The conference covers a wide range of the following: semantic Web, rule and ontology languages, and related logics, reasoning, querying, searching and optimization, incompleteness, inconsistency and uncertainty, non-monotonic, common sense, and closed-world reasoning for the web, dynamic information, stream reasoning and complex event processing, decision making, planning, and intelligent agents, machine learning, knowledge extraction and information retrieval, data management, data integration and reasoning on the web of data, ontology-based data access, system descriptions, applications and experiences.

This book constitutes the proceedings of the 15th International Conference on Web Information Systems Engineering, WISE 2014, held in Thessaloniki, Greece, in October 2014. The 52 full papers, 16 short and 14 poster papers, presented in the two-volume proceedings LNCS 8786 and 8787 were carefully reviewed and selected from 196 submissions. They are organized in topical sections named: Web mining, modeling and classification; Web querying and searching; Web recommendation and personalization; semantic Web; social online networks; software architectures amd platforms; Web technologies and frameworks; Web innovation and applications; and challenge.

This book constitutes the refereed proceedings of the 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the latest research, results, and ideas in these areas.

This volume covers some of the topics that are related to the rapidly growing field of biomedical informatics. In June 11-12, 2010 a workshop entitled 'Optimization and Data Analysis in Biomedical Informatics' was organized at The Fields Institute. Following this event invited contributions were gathered based on the talks presented at the workshop, and additional invited chapters were chosen from world's leading experts. In this publication, the authors share their expertise in the form of state-of-the-art research and review chapters, bringing together researchers from different disciplines and emphasizing the value of mathematical methods in the areas of clinical sciences. This work is targeted to applied mathematicians, computer scientists, industrial engineers, and clinical scientists who are interested in exploring emerging and fascinating interdisciplinary topics of research. It is designed to further stimulate and enhance fruitful collaborations between scientists from different disciplines.