This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Analysis, IDA 2012, held in Helsinki, Finland, in October 2012. The 32 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 88 submissions. All current aspects of intelligent data analysis are addressed, including intelligent support for modeling and analyzing data from complex, dynamical systems. The papers focus on novel applications of IDA techniques to, e.g., networked digital information systems; novel modes of data acquisition and the associated issues; robustness and scalability issues of intelligent data analysis techniques; and visualization and dissemination results.

Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and knowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012.

This two volume set LNCS 7446 and LNCS 7447 constitutes the refereed proceedings of the 23rd International Conference on Database and Expert Systems Applications, DEXA 2012, held in Vienna, Austria, September 3-6, 2012. The 49 revised full papers presented together with 37 short papers and 2 keynote talks were carefully reviewed and selected from 179 submissions. These papers discuss a range of topics including: database query processing, in particular XML queries; labelling of XML documents; computational efficiency, data extraction; personalization, preferences, and ranking; security and privacy; database schema evaluation and evolution; semantic Web; privacy and provenance; data mining; data streaming; distributed systems; searching and query answering; structuring, compression and optimization; failure, fault analysis, and uncertainty; predication, extraction, and annotation; ranking and personalisation; database partitioning and performance measurement; recommendation and prediction systems; business processes; social networking.

This book constitutes the refereed proceedings of the 8th International Conference on Intelligent Computing, ICIC 2012, held in Huangshan, China, in July 2012. The 85 revised full papers presented were carefully reviewed and selected from 753 submissions. The papers are organized in topical sections on neural networks, evolutionar learning and genetic algorithms, granular computing and rough sets, biology inspired computing and optimization, nature inspired computing and optimization, cognitive science and computational neuroscience, knowledge discovery and data mining, quantum computing, machine learning theory and methods, healthcare informatics theory and methods, biomedical informatics theory and methods, complex systems theory and methods, intelligent computing in signal processing, intelligent computing in image processing, intelligent computing in robotics, intelligent computing in computer vision, intelligent agent and web applications, special session on advances in information security 2012.

This book constitutes the refereed proceedings of the Third Knowledge Technology Week, KTW 2011, held in Kajang, Malaysia, in July 2011. The 29 revised full papers presented together with 9 short papers were carefully reviewed and selected from 105 submissions. KTW 2011 consisted of a number of co-located events. This volume contains selected papers from the proceedings of the Third Malaysian Joint Conference on Artificial Intelligence (MJCAI 2011), the Third Semantic Technology and Knowledge Engineering (STAKE 2011), and the International Workshop on Semantic Agents (IWSA 2012).

This book constitutes the refereed proceedings of the Third International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2012, held in Vienna, Austria, September 2012, in conjunction with DEXA 2012. The 12 revised long papers and 3 revised short papers presented were carefully reviewed and selected from numerous submissions. The papers address the following topics: medical data mining and information retrieval; metadata models, prediction and mobile applications; systems biology and data mining in bioinformatics. The papers show how broad the spectrum of topics in applications of information technology to biomedical engineering and medical informatics is.

This book constitutes the refereed proceedings of the 14th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2012 held in Vienna, Austria, in September 2012. The 36 revised full papers presented were carefully reviewed and selected from 99 submissions. The papers are organized in topical sections on data warehouse design methodologies, ETL methodologies and tools, multidimensional data processing and management, data warehouse and OLAP extensions, data warehouse performance and optimization, data mining and knowledge discovery techniques, data mining and knowledge discovery applications, pattern mining, data stream mining, data warehouse confidentiality and security, and distributed paradigms and algorithms.

This two volume set LNCS 7446 and LNCS 7447 constitutes the refereed proceedings of the 23rd International Conference on Database and Expert Systems Applications, DEXA 2012, held in Vienna, Austria, September 3-6, 2012. The 49 revised full papers presented together with 37 short papers and 2 keynote talks were carefully reviewed and selected from 179 submissions. These papers discuss a range of topics including: database query processing, in particular XML queries; labelling of XML documents; computational efficiency, data extraction; personalization, preferences, and ranking; security and privacy; database schema evaluation and evolution; semantic Web; privacy and provenance; data mining; data streaming; distributed systems; searching and query answering; structuring, compression and optimization; failure, fault analysis, and uncertainty; predication, extraction, and annotation; ranking and personalisation; database partitioning and performance measurement; recommendation and prediction systems; business processes; social networking.

This book constitutes the refereed proceedings of the 13th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2012, held in Natal, Brazil, in August 2012. The 100 revised full papers presented were carefully reviewed and selected from more than 200 submissions for inclusion in the book and present the latest theoretical advances and real-world applications in computational intelligence.

The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.

Sensor networks comprise of a number of sensors installed across a spatially distributed network, which gather information and periodically feed a central server with the measured data. The server monitors the data, issues possible alarms and computes fast aggregates. As data analysis requests may concern both present and past data, the server is forced to store the entire stream. But the limited storage capacity of a server may reduce the amount of data stored on the disk. One solution is to compute summaries of the data as it arrives, and to use these summaries to interpolate the real data. This work introduces a recently defined spatio-temporal pattern, called trend cluster, to summarize, interpolate and identify anomalies in a sensor network. As an example, the application of trend cluster discovery to monitor the efficiency of photovoltaic power plants is discussed. The work closes with remarks on new possibilities for surveillance enabled by recent developments in sensing technology.

This book constitutes the refereed proceedings of the 31st International Conference on Conceptual Modeling, ER 2012, held in Florence, Italy, in October 2012. The 24 regular papers presented together with 13 short papers, 6 poster papers and 3 keynotes were carefully reviewed and selected from 141 submissions. The papers are organized in topical sections on understandability and cognitive approaches; conceptual modeling for datawarehousing and business intelligence; extraction, discovery and clustering; search and documents; data and process modeling; ontology based approaches; variability and evolution; adaptation, preferences and query refinement; queries, matching and topic search; and conceptual modeling in action.

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.

The two volumes set, CCIS 383 and 384, constitutes the refereed proceedings of the 14th International Conference on Engineering Applications of Neural Networks, EANN 2013, held on Halkidiki, Greece, in September 2013. The 91 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers describe the applications of artificial neural networks and other soft computing approaches to various fields such as pattern recognition-predictors, soft computing applications, medical applications of AI, fuzzy inference, evolutionary algorithms, classification, learning and data mining, control techniques-aspects of AI evolution, image and video analysis, classification, pattern recognition, social media and community based governance, medical applications of AI-bioinformatics and learning.

This book constitutes the thoroughly refereed conference proceedings of the 7th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2013, held in Krabi, Thailand, in December 2013. The 30 full papers were carefully reviewed and selected from 65 submissions and cover topics such as cognitive science, computational intelligence, computational philosophy, game theory, machine learning, multi-agent systems, natural language, representation and reasoning, speech, vision and the web.

The two volumes set, CCIS 383 and 384, constitutes the refereed proceedings of the 14th International Conference on Engineering Applications of Neural Networks, EANN 2013, held on Halkidiki, Greece, in September 2013. The 91 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers describe the applications of artificial neural networks and other soft computing approaches to various fields such as pattern recognition-predictors, soft computing applications, medical applications of AI, fuzzy inference, evolutionary algorithms, classification, learning and data mining, control techniques-aspects of AI evolution, image and video analysis, classification, pattern recognition, social media and community based governance, medical applications of AI-bioinformatics and learning.

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 eighth issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains eight revised selected regular papers focusing on the following topics: scalable data warehousing via MapReduce, extended OLAP multidimensional models, naive OLAP engines and their optimization, advanced data stream processing and mining, semi-supervised learning of data streams, incremental pattern mining over data streams, association rule mining over data streams, frequent pattern discovery over data streams.

Privacy and security risks arising from the application of different data mining techniques to large institutional data repositories have been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique in data mining, which studies the problem of hiding sensitive association rules from within the data.

Association Rule Hiding for Data Mining addresses the problem of "hiding" sensitive association rules, and introduces a number of heuristic solutions. Exact solutions of increased time complexity that have been proposed recently are presented, as well as a number of computationally efficient (parallel) approaches that alleviate time complexity problems, along with a thorough discussion regarding closely related problems (inverse frequent item set mining, data reconstruction approaches, etc.). Unsolved problems, future directions and specific examples are provided throughout this book to help the reader study, assimilate and appreciate the important aspects of this challenging problem.

Association Rule Hiding for Data Mining is designed for researchers, professors and advanced-level students in computer science studying privacy preserving data mining, association rule mining, and data mining. This book is also suitable for practitioners working in this industry.

This book constitutes the refereed proceedings of the 8th International Conference on Rough Sets and Current Trends in Computing, RSCTC, held in Chengdu, China, in August 2012, as one of the co-located conferences of the 2012 Joint Rough Set Symposium, JRS 2012. The 55 revised full papers presented together with one keynote paper were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on rough sets and its applications; current trends in computing; decision-theoretic rough set model and applications; formal concept analysis and granular computing; mining complex data with granular computing; data mining competition.

Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied to originates from one domain. The focus of this book, and the BISON project from which the contributions are originating, is a network based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information networks. Instead of finding well defined global or local patterns they wanted to find domain bridging associations which are, by definition, not well defined since they will be especially interesting if they are sparse and have not been encountered before. The 32 contributions presented in this state-of-the-art volume together with a detailed introduction to the book are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.

This book constitutes the refereed proceedings of the Second International Conference on Theory and Practice of Digital Libraries, TPDL 2012 - the successor of the ECDL (European Conference on Research and Advanced Technology for Digital Libraries) - held in Paphos, Cyprus, in September 2012. The 23 full papers, 19 short papers, 15 posters and 8 demonstrations presented in this volume were carefully reviewed and selected from 139 submissions. The papers are organized in topical sections on user behavior, mobiles and place, heritage and sustainability, preservation, linked data, analysing and enriching documents, content and metadata quality, folksonomy and ontology, information retrieval, organising collections, as well as extracting and indexing.

This book constitutes the thoroughly refereed conference proceedings of the 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2013, held in Halifax, Canada in October 2013 as one of the co-located conference of the 2013 Joint Rough Set Symposium, JRS 2013. The 69 papers (including 44 regular and 25 short papers) included in the JRS proceedings (LNCS 8170 and LNCS 8171) were carefully reviewed and selected from 106 submissions. The papers in this volume cover topics such as inconsistency, incompleteness, non-determinism; fuzzy and rough hybridization; granular computing and covering-based rough sets; soft clustering; image and medical data analysis.

This book constitutes the refereed proceedings of the 9th International Symposium on Bioinformatics Research and Applications, ISBRA 2013, held in Charlotte, NC, USA, in May 2013. The 25 revised full papers presented together with 4 invited talks were carefully reviewed and selected from 46 submissions. The papers cover a wide range of biomedical databases and data integration, high-performance bio-computing, biomolecular imaging, high-throughput sequencing data analysis, bio-ontologies, molecular evolution, comparative genomics and phylogenomics, molecular modeling and simulation, pattern discovery and classification, computational proteomics, population genetics, data mining and visualization, software tools and applications.

This book constitutes the refereed proceedings of the 8th International Conference on Data Integration in the Life Sciences, DILS 2012, held in College Park, MD, USA, on June 28-29, 2012. The 11 revised papers included in this volume were carefully reviewed and selected. The papers cover the following topics: foundations of data integration, new paradigms for data integration, and integrating clinical data.

This book constitutes the refereed proceedings of the 17th International Conference on Applications of Natural Language to Information Systems, held in Groningen, The Netherlands, in June 2012. The 12 full papers, 24 short papers and 16 poster papers presented in this volume together with a full-paper length invited talks were carefully reviewed and selected from 90 submissions. The rapidly evolving state-of-the-art in NLP and the shifting interest to appcliations targeting document and data collections available on the Web, including an increasing amount of user generated content, is reflected in the contributions to this book. Topics covered are information retrieval, text classification and clustering, summarization, normalization of user generated content, "forensic" NLP, ontologies and natural language, sentiment analysis, question answering and information extraction, terminology and named entity recognition, and NLP tools development.