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.

This book constitutes the refereed proceedings of the 8th International Conference on Scalable Uncertainty Management, SUM 2014, held in Oxford, UK, in September 2014. The 20 revised full papers and 6 revised short papers were carefully reviewed and selected from 47 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.

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.

Information extraction (IE) and text summarization (TS) are powerful technologies for finding relevant pieces of information in text and presenting them to the user in condensed form. The ongoing information explosion makes IE and TS critical for successful functioning within the information society. These technologies face particular challenges due to the inherent multi-source nature of the information explosion. The technologies must now handle not isolated texts or individual narratives, but rather large-scale repositories and streams---in general, in multiple languages---containing a multiplicity of perspectives, opinions, or commentaries on particular topics, entities or events. There is thus a need to adapt existing techniques and develop new ones to deal with these challenges. This volume contains a selection of papers that present a variety of methodologies for content identification and extraction, as well as for content fusion and regeneration. The chapters cover various aspects of the challenges, depending on the nature of the information sought---names vs. events,--- and the nature of the sources---news streams vs. image captions vs. scientific research papers, etc. This volume aims to offer a broad and representative sample of studies from this very active research field.

This book presents advances in matrix and tensor data processing in the domain of signal, image and information processing. The theoretical mathematical approaches are discusses in the context of potential applications in sensor and cognitive systems engineering. The topics and application include Information Geometry, Differential Geometry of structured Matrix, Positive Definite Matrix, Covariance Matrix, Sensors (Electromagnetic Fields, Acoustic sensors) and Applications in Cognitive systems, in particular Data Mining.

Innovating in Product/Process Development demonstrates how to achieve true innovation in product development, and how to launch a new product in the quickest and cheapest way. The new approach to product development proposed in this book is based on the most recent research in the field. It suggests the integration of several tools that are currently only used independently, with the aim of stimulating the creation of innovative ideas in general, and specifically in the areas of product/process improvements and problem solving. Innovating in Product/Process Development explores different aspects of innovation processes in twenty-first century industry from a global economic perspective. It presents in detail several approaches to support these processes, from ICT-based systems to collaborative working environments, all of which will be of interest to MBA or advanced students; researchers; and design teams charged with the creation of new product lines.

This book constitutes the thoroughly refereed papers of the Third National Conference of Social Media Processing, SMP 2014, held in Beijing, China, in November 2014. The 14 revised full papers and 9 short papers presented were carefully reviewed and selected from 101 submissions. The papers focus on the following topics: mining social media and applications; natural language processing; data mining; information retrieval; emergent social media processing problems.

Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and last but not least their computational e?ciency compared with several other methods. Although there are several roots and precursors of SVMs, these methods gained particular momentum during the last 15 years since Vapnik (1995, 1998) published his well-known textbooks on statistical learning theory with aspecialemphasisonsupportvectormachines. Sincethen,the?eldofmachine learninghaswitnessedintenseactivityinthestudyofSVMs,whichhasspread moreandmoretootherdisciplinessuchasstatisticsandmathematics. Thusit seems fair to say that several communities are currently working on support vector machines and on related kernel-based methods. Although there are many interactions between these communities, we think that there is still roomforadditionalfruitfulinteractionandwouldbegladifthistextbookwere found helpful in stimulating further research. Many of the results presented in this book have previously been scattered in the journal literature or are still under review. As a consequence, these results have been accessible only to a relativelysmallnumberofspecialists,sometimesprobablyonlytopeoplefrom one community but not the others.

This book constitutes the thoroughly refereed joint proceedings of the Third and Fourth Workshop on Big Data Benchmarking. The third WBDB was held in Xi'an, China, in July 2013 and the Fourth WBDB was held in San Jose, CA, USA, in October, 2013. The 15 papers presented in this book were carefully reviewed and selected from 33 presentations. They focus on big data benchmarks; applications and scenarios; tools, systems and surveys.

This book constitutes the refereed proceedings of 5 workshops of the 15th International Conference on Web-Age Information Management, WAIM 2014, held in Macau, China, June 16-18, 2014. The 38 revised full papers are organized in topical sections on the 5 following workshops: Second International Workshop on Emergency Management in Big Data Age, BigEM 2014; Second International Workshop on Big Data Management on Emerging Hardware, HardBD 2014; International Workshop on Data Management for Next-Generation Location-based Services, DaNoS 2014; International Workshop on Human Aspects of Making Recommendations in Social Ubiquitous Networking Environment, HRSUME 2014; International Workshop on Big Data Systems and Services, BIDASYS 2014.

This book contains the refereed proceedings of the 9th International Conference on Knowledge Management in Organizations (KMO) held in Santiago, Chile, during September 2014. The theme of the conference is "Knowledge Management to Improve Innovation and Competitiveness through Big Data." The KMO conference brings together researchers and developers from industry and academia to discuss and research how knowledge management using big data can improve innovation and competitiveness. The 39 contributions accepted for KMO 2014 were selected from 89 submissions and are organized in sections on: big data and knowledge management, knowledge management practice and case studies, information technology and knowledge management, knowledge management and social networks, knowledge management in organizations, and knowledge transfer, sharing and creation.

This book constitutes the refereed proceedings of the 7th International Workshop on Probabilistic Graphical Models, PGM 2014, held in Utrecht, The Netherlands, in September 2014. The 38 revised full papers presented in this book were carefully reviewed and selected from 44 submissions. The papers cover all aspects of graphical models for probabilistic reasoning, decision making, and learning.

This SpringerBrief discusses the characteristics of spatiotemporal movement data, including uncertainty and scale. It investigates three core aspects of Computational Movement Analysis: Conceptual modeling of movement and movement spaces, spatiotemporal analysis methods aiming at a better understanding of movement processes (with a focus on data mining for movement patterns), and using decentralized spatial computing methods in movement analysis. The author presents Computational Movement Analysis as an interdisciplinary umbrella for analyzing movement processes with methods from a range of fields including GIScience, spatiotemporal databases and data mining. Key challenges in Computational Movement Analysis include bridging the semantic gap, privacy issues when movement data involves people, incorporating big and open data, and opportunities for decentralized movement analysis arising from the internet of things. The interdisciplinary concepts of Computational Movement Analysis make this an important book for professionals and students in computer science, geographic information science and its application areas, especially movement ecology and transportation research.

This book constitutes the refereed proceedings of the 21st International Conference on Case-Based Reasoning Research and Development (ICCBR 2014) held in Cork, Ireland, in September 2014. The 35 revised full papers presented were carefully reviewed and selected from 49 submissions. The presentations cover a wide range of CBR topics of interest both to researchers and practitioners including case retrieval and adaptation, similarity assessment, case base maintenance, knowledge management, recommender systems, multiagent systems, textual CBR, and applications to healthcare and computer games.

This book constitutes the refereed proceedings of the 9th International Conference on Advances in Natural Language Processing, PolTAL 2014, Warsaw, Poland, in September 2014. The 27 revised full papers and 20 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on morphology, named entity recognition, term extraction; lexical semantics; sentence level syntax, semantics, and machine translation; discourse, coreference resolution, automatic summarization, and question answering; text classification, information extraction and information retrieval; and speech processing, language modelling, and spell- and grammar-checking.

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 proceedings of the 20th Collaboration Researchers' International Working Group Conference on Collaboration and Technology, held in Santiago, Chile, in September 2014. The 16 revised papers presented together with 18 progress papers and 3 invited talks were carefully reviewed and selected from 49 submissions. The papers published in proceedings of this year's and past CRIWG conferences reflect the trends in collaborative computing research and its evolution. There was a growing interest in social networks analysis, crowdsourcing and computer support for large communities in general. A special research topic which has been traditionally present in the CRIWG proceedings has been collaborative learning.

The latest inventions in internet technology influence most of business and daily activities. Internet security, internet data management, web search, data grids, cloud computing, and web-based applications play vital roles, especially in business and industry, as more transactions go online and mobile. Issues related to ubiquitous computing are becoming critical. Internet technology and data engineering should reinforce efficiency and effectiveness of business processes. These technologies should help people make better and more accurate decisions by presenting necessary information and possible consequences for the decisions. Intelligent information systems should help us better understand and manage information with ubiquitous data repository and cloud computing. This book is a compilation of some recent research findings in Internet Technology and Data Engineering. This book provides state-of-the-art accounts in computational algorithms/tools, database management and database technologies, intelligent information systems, data engineering applications, internet security, internet data management, web search, data grids, cloud computing, web-based application, and other related topics.

This book constitutes the refereed proceedings of the 17th International Conference on Text, Speech and Dialogue, TSD 2013, held in Brno, Czech Republic, in September 2014. The 70 papers presented together with 3 invited papers were carefully reviewed and selected from 143 submissions. They focus on topics such as corpora and language resources; speech recognition; tagging, classification and parsing of text and speech; speech and spoken language generation; semantic processing of text and speech; integrating applications of text and speech processing; automatic dialogue systems; as well as multimodal techniques and modelling.

This book constitutes the refereed proceedings of the 6th International Conference on Collective Intelligence, ICCCI 2014, held in Seoul, Korea, in September 2014. The 70 full papers presented were carefully reviewed and selected from 205 submissions. They address topics such as knowledge integration, data mining for collective processing, fuzzy, modal and collective systems, nature inspired systems, language processing systems, social networks and semantic web, agent and multi-agent systems, classification and clustering methods, multi-dimensional data processing, Web systems, intelligent decision making, methods for scheduling, image and video processing, collective intelligence in web systems, computational swarm intelligence, cooperation and collective knowledge.

This book constitutes the refereed proceedings of the 2014 Multidisciplinary International Social Networks Research, MISNC 2014, held in Kaohsiung, Taiwan, in September 2014. The 37 full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on electronic commerce, e-business management, and social networks; social networks issues on sociology, politics and statistics; information technology for social networks analysis and mining; social networks for global eHealth and bio-medics; security, open data, e-learning and other related topics; intelligent data analysis and its applications.

This book constitutes the refereed proceedings of the 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

This book constitutes the proceedings of 26th International Conference on Advanced Information Systems Engineering, CAiSE 2014, held in Thessaloniki, Greece in June 2014. The 41 papers and 3 keynotes presented were carefully reviewed and selected from 226 submissions. The accepted papers were presented in 13 sessions: clouds and services; requirements; product lines; requirements elicitation; processes; risk and security; process models; data mining and streaming; process mining; models; mining event logs; databases; software engineering.

This book constitutes the refereed proceedings of the 19th International Conference on Applications of Natural Language to Information Systems, NLDB 2014, held in Montpellier, France, in June 2014. The 13 long papers, 8 short papers, 14 poster papers, and 7 demo papers presented together with 2 invited talks in this volume were carefully reviewed and selected from 73 submissions. The papers cover the following topics: syntactic, lexical and semantic analysis; information extraction; information retrieval and sentiment analysis and social networks.