These three volumes (CCIS 442, 443, 444) constitute the proceedings of the 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2014, held in Montpellier, France, July 15-19, 2014. The 180 revised full papers presented together with five invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on uncertainty and imprecision on the web of data; decision support and uncertainty management in agri-environment; fuzzy implications; clustering; fuzzy measures and integrals; non-classical logics; data analysis; real-world applications; aggregation; probabilistic networks; recommendation systems and social networks; fuzzy systems; fuzzy logic in boolean framework; management of uncertainty in social networks; from different to same, from imitation to analogy; soft computing and sensory analysis; database systems; fuzzy set theory; measurement and sensory information; aggregation; formal methods for vagueness and uncertainty in a many-valued realm; graduality; preferences; uncertainty management in machine learning; philosophy and history of soft computing; soft computing and sensory analysis; similarity analysis; fuzzy logic, formal concept analysis and rough set; intelligent databases and information systems; theory of evidence; aggregation functions; big data - the role of fuzzy methods; imprecise probabilities: from foundations to applications; multinomial logistic regression on Markov chains for crop rotation modelling; intelligent measurement and control for nonlinear systems.

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2014; comprising the International Workshop on Structural and Syntactic Pattern Recognition, SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR. The total of 25 full papers and 22 poster papers included in this book were carefully reviewed and selected from 78 submissions. They are organized in topical sections named: graph kernels; clustering; graph edit distance; graph models and embedding; discriminant analysis; combining and selecting; joint session; metrics and dissimilarities; applications; partial supervision; and poster session.

These three volumes (CCIS 442, 443, 444) constitute the proceedings of the 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2014, held in Montpellier, France, July 15-19, 2014. The 180 revised full papers presented together with five invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on uncertainty and imprecision on the web of data; decision support and uncertainty management in agri-environment; fuzzy implications; clustering; fuzzy measures and integrals; non-classical logics; data analysis; real-world applications; aggregation; probabilistic networks; recommendation systems and social networks; fuzzy systems; fuzzy logic in boolean framework; management of uncertainty in social networks; from different to same, from imitation to analogy; soft computing and sensory analysis; database systems; fuzzy set theory; measurement and sensory information; aggregation; formal methods for vagueness and uncertainty in a many-valued realm; graduality; preferences; uncertainty management in machine learning; philosophy and history of soft computing; soft computing and sensory analysis; similarity analysis; fuzzy logic, formal concept analysis and rough set; intelligent databases and information systems; theory of evidence; aggregation functions; big data - the role of fuzzy methods; imprecise probabilities: from foundations to applications; multinomial logistic regression on Markov chains for crop rotation modelling; intelligent measurement and control for nonlinear systems.

A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given domain relying on a very effective set of content-based features. The effectiveness of the content-based features is also exploited to directly learn from test data structure-based features, with no previous human-driven training, a feature unique to the presented approach. Based on the approach, a number of results are produced to address the IETS problem in an unsupervised fashion. In particular, the authors develop, implement and evaluate distinct IETS methods, namely "ONDUX," "JUDIE" and "iForm."

"ONDUX" (On Demand Unsupervised Information Extraction) is an unsupervised probabilistic approach for IETS that relies on content-based features to bootstrap the learning of structure-based features. "JUDIE" (Joint Unsupervised Structure Discovery and Information Extraction) aims at automatically extracting several semi-structured data records in the form of continuous text and having no explicit delimiters between them. In comparison with other IETS methods, including "ONDUX," "JUDIE" faces a task considerably harder that is, extracting information while simultaneously uncovering the underlying structure of the implicit records containing it." iForm" applies the authors approach to the task of Web form filling. It aims at extracting segments from a data-rich text given as input and associating these segments with fields from a target Web form.

All of these methods were evaluated considering different experimental datasets, which are used to perform a large set of experiments in order to validate the presented approach and methods. These experiments indicate that the proposed approach yields high quality results when compared to state-of-the-art approaches and that it is able to properly support IETS methods in a number of real applications. The findings will prove valuable to practitioners in helping them to understand the current state-of-the-art in unsupervised information extraction techniques, as well as to graduate and undergraduate students of web data management."

This book constitutes the proceedings of the 16th International Conference on Discovery Science, DS 2013, held in Singapore in October 2013, and co-located with the International Conference on Algorithmic Learning Theory, ALT 2013. The 23 papers presented in this volume were carefully reviewed and selected from 52 submissions. They cover recent advances in the development and analysis of methods of automatic scientific knowledge discovery, machine learning, intelligent data analysis, and their application to knowledge discovery.

This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.

This book constitutes the proceedings of the 14th International Conference on Web Information Systems Engineering, WISE 2013, held in Nanjing, China, in October 2013. The 48 full papers, 29 short papers, and 10 demo and 5 challenge papers, presented in the two-volume proceedings LNCS 8180 and 8181, were carefully reviewed and selected from 198 submissions. They are organized in topical sections named: Web mining; Web recommendation; Web services; data engineering and database; semi-structured data and modeling; Web data integration and hidden Web; challenge; social Web; information extraction and multilingual management; networks, graphs and Web-based business processes; event processing, Web monitoring and management; and innovative techniques and creations.

This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.

This two-volume set, consisting of LNCS 8403 and LNCS 8404, constitutes the thoroughly refereed proceedings of the 14th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2014, held in Kathmandu, Nepal, in April 2014. The 85 revised papers presented together with 4 invited papers were carefully reviewed and selected from 300 submissions. The papers are organized in the following topical sections: lexical resources; document representation; morphology, POS-tagging, and named entity recognition; syntax and parsing; anaphora resolution; recognizing textual entailment; semantics and discourse; natural language generation; sentiment analysis and emotion recognition; opinion mining and social networks; machine translation and multilingualism; information retrieval; text classification and clustering; text summarization; plagiarism detection; style and spelling checking; speech processing; and applications.

The two-volume set LNAI 8443 + LNAI 8444 constitutes the refereed proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, held in Tainan, Taiwan, in May 2014. The 40 full papers and the 60 short papers presented within these proceedings were carefully reviewed and selected from 371 submissions. They cover the general fields of pattern mining; social network and social media; classification; graph and network mining; applications; privacy preserving; recommendation; feature selection and reduction; machine learning; temporal and spatial data; novel algorithms; clustering; biomedical data mining; stream mining; outlier and anomaly detection; multi-sources mining; and unstructured data and text mining.

This book constitutes the refereed proceedings of the 7th International Conference on Scalable Uncertainty Management, SUM 2013, held in Washington, DC, USA, in September 2013. The 26 revised full papers and 3 revised short papers were carefully reviewed and selected from 57 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 book constitutes the thoroughly refereed post-conference proceedings of the 6th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2013, held in Barcelona, Spain, in February 2013. The 28 revised full papers presented were carefully reviewed and selected from a total of 392 submissions. The papers cover a wide range of topics and are organized in four general topical sections on biomedical electronics and devices; bioinformatics models, methods and algorithms; bio-inspired systems and signal processing; health informatics.

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 special issue contains extended and revised versions of 4 papers, selected from the 25 papers presented at the satellite events associated with the 17th East-European Conference on Advances in Databases and Information Systems (ADBIS 2013), held on September 1-4, 2013 in Genoa, Italy. The three satellite events were GID 2013, the Second International Workshop on GPUs in Databases; SoBI 2013, the First International Workshop on Social Business Intelligence: Integrating Social Content in Decision Making; and OAIS 2013, the Second International Workshop on Ontologies Meet Advanced Information Systems. The papers cover various topics in large-scale data and knowledge-centered systems, including GPU-accelerated database systems and GPU-based compression for large time series databases, design of parallel data warehouses, and schema matching. The special issue content, which combines both theoretical and application-based contributions, gives a useful overview of some of the current trends in large-scale data and knowledge management and will stimulate new ideas for further research and development within both the scientific and industrial communities.

This book constitutes the proceedings of the 10th International Conference on Advanced Data Mining and Applications, ADMA 2014, held in Guilin, China during December 2014. The 48 regular papers and 10 workshop papers presented in this volume were carefully reviewed and selected from 90 submissions. They deal with the following topics: data mining, social network and social media, recommend systems, database, dimensionality reduction, advance machine learning techniques, classification, big data and applications, clustering methods, machine learning, and data mining and database.

This book constitutes the refereed proceedings of the 9th International Conference on Active Media Technology, AMT 2013, held in Maebashi, Japan, in October 2013. The 26 revised full papers presented together with 2 short papers, 16 workshop papers, and 12 special session papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on active computer systems, interactive systems, and application of AMT based systems; active media machine learning and data mining techniques; AMT for semantic web, social networks, and cognitive foundations. Additionally, the main topic of the workshop papers is: intelligence for strategic foresight; and for the special session papers: technologies and theories of narrative; evolutionary computation and its application; and intelligent media search techniques.

This book constitutes the workshop proceedings of the 18th International Conference on Database Systems for Advanced Applications, DASFAA 2013, held in Wuhan, China, in April 2013. The volume contains three workshops, each focusing on specific area that contributes to the main themes of the DASFAA conference: The First International Workshop on Big Data Management and Analytics (BDMA 2013), the Third International Workshop on Social Networks and Social Web (SNSM 2013) and the International Workshop on Semantic Computing and Personalization (SeCoP 2013).

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.

Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art.

This book constitutes the refereed proceedings of the 13th International Symposium on Spatial and Temporal Databases, SSTD 2013, held in Munich, Germany, in August 2013. The 24 revised full papers presented were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on joins and algorithms; mining and discovery; indexing; trajectories and road network data; nearest neighbours queries; uncertainty; and demonstrations.

This volume constitutes the refereed proceedings of the 9th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2013, held in Lund, Sweden, in August 2013. The 26 revised full papers were carefully reviewed and selected from 40 submissions. The papers are organized in topical sections on Medical Imaging; Image Editing; 3D Reconstruction; Shape Matching; Scene Understanding; Segmentation; Superpixels; Statistical Methods and Learning.

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 book constitutes revised selected papers from the two International Workshops on Artificial Intelligence Approaches to the Complexity of Legal Systems, AICOL IV and AICOL V, held in 2013. The first took place as part of the 26th IVR Congress in Belo Horizonte, Brazil, during July 21-27, 2013; the second was held in Bologna as a joint special workshop of JURIX 2013 on December 11, 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They are organized in topical sections named: social intelligence and legal conceptual models; legal theory, normative systems and software agents; semantic Web technologies, legal ontologies and argumentation; and crowdsourcing and online dispute resolution (ODR).

Beginning Apache Cassandra Development introduces you to one of the most robust and best-performing NoSQL database platforms on the planet. Apache Cassandra is a document database following the JSON document model. It is specifically designed to manage large amounts of data across many commodity servers without there being any single point of failure. This design approach makes Apache Cassandra a robust and easy-to-implement platform when high availability is needed. Apache Cassandra can be used by developers in Java, PHP, Python, and JavaScript-the primary and most commonly used languages. In Beginning Apache Cassandra Development, author and Cassandra expert Vivek Mishra takes you through using Apache Cassandra from each of these primary languages. Mishra also covers the Cassandra Query Language (CQL), the Apache Cassandra analog to SQL. You'll learn to develop applications sourcing data from Cassandra, query that data, and deliver it at speed to your application's users. Cassandra is one of the leading NoSQL databases, meaning you get unparalleled throughput and performance without the sort of processing overhead that comes with traditional proprietary databases. Beginning Apache Cassandra Development will therefore help you create applications that generate search results quickly, stand up to high levels of demand, scale as your user base grows, ensure operational simplicity, and-not least-provide delightful user experiences.

Data mining has emerged as one of the most active areas in information and c- munication technologies(ICT). With the boomingof the global economy,and ub- uitouscomputingandnetworkingacrosseverysectorand business,data andits deep analysis becomes a particularly important issue for enhancing the soft power of an organization, its production systems, decision-making and performance. The last ten years have seen ever-increasingapplications of data mining in business, gove- ment, social networks and the like. However, a crucial problem that prevents data mining from playing a strategic decision-support role in ICT is its usually limited decision-support power in the real world. Typical concerns include its actionability, workability, transferability, and the trustworthy, dependable, repeatable, operable and explainable capabilities of data mining algorithms, tools and outputs. This monograph, Domain Driven Data Mining, is motivated by the real-world challenges to and complexities of the current KDD methodologies and techniques, which are critical issues faced by data mining, as well as the ?ndings, thoughts and lessons learned in conducting several large-scale real-world data mining bu- ness applications. The aim and objective of domain driven data mining is to study effective and ef?cient methodologies, techniques, tools, and applications that can discover and deliver actionable knowledge that can be passed on to business people for direct decision-making and action-taking.

This book constitutes the refereed conference proceedings of the Third International Conference on Big Data Analytics, BDA 2014, held in New Delhi, India, in December 2014. The 11 revised full papers and 6 short papers were carefully reviewed and selected from 35 submissions and cover topics on media analytics; geospatial big data; semantics and data models; search and retrieval; graphics and visualization; application-specific big data.