Data mining

Similarity-based learning methods have a great potential as an intuitive and ?exible toolbox for mining, visualization,and inspection of largedata sets. They combine simple and human-understandable principles, such as distance-based classi?cation, prototypes, or Hebbian learning, with a large variety of di?erent, problem-adapted design choices, such as a data-optimum topology, similarity measure, or learning mode. In medicine, biology, and medical bioinformatics, more and more data arise from clinical measurements such as EEG or fMRI studies for monitoring brain activity, mass spectrometry data for the detection of proteins, peptides and composites, or microarray pro?les for the analysis of gene expressions. Typically, data are high-dimensional, noisy, and very hard to inspect using classic (e. g. , symbolic or linear) methods. At the same time, new technologies ranging from the possibility of a very high resolution of spectra to high-throughput screening for microarray data are rapidly developing and carry thepromiseofane?cient,cheap,andautomaticgatheringoftonsofhigh-quality data with large information potential. Thus, there is a need for appropriate - chine learning methods which help to automatically extract and interpret the relevant parts of this information and which, eventually, help to enable und- standingofbiologicalsystems,reliablediagnosisoffaults,andtherapyofdiseases such as cancer based on this information. Moreover, these application scenarios pose fundamental and qualitatively new challenges to the learning systems - cause of the speci?cs of the data and learning tasks. Since these characteristics are particularly pronounced within the medical domain, but not limited to it and of principled interest, this research topic opens the way toward important new directions of algorithmic design and accompanying theory.

In recent years, Internet-based systems and applications have become pervasive and have been the focus of many ongoing research efforts. They range from semi-structured information, to multimedia systems and applications, to P2P and ad hoc information sharing networks and service-centric systems and applications. This book p- sents a collection of articles from the best papers presented at the SITIS 2006 International Conference, aiming to cover recent advanced research on distributed information systems, including both theoretical and applied solutions. This volume is designed for a professional audience practitioners and researchers in industry. It is also suitable as a reference or secondary text for advanced-level students in computer science and engineering. The articles in this book are a selection of papers presented at the IMRT and WITDS tracks of the international SITIS 2006 conference. The authors were asked to revise and extend their contributions to take into account the comments and discussions made at the conference. A large number of high-quality papers were submitted to SITIS 2006, demonstrating the growing interest of the - search community for Internet-Based and multimedia information systems. We would like to acknowledge the hard work and dedication of many people. Our deepest gratitude goes to the authors who contributed their work. We appreciate the diligent work of the SITIS Committee members. We are grateful for the help, support and patience of the LNCS publishing team. Finally, thanks to Iwayan Wikacsana for his invaluable help. February 2007 Ernesto Damiani Kokou Yetongnon Richard Chbeir Albert Dipanda

This book constitutes the refereed proceedings of the 5th International Symposium on Bioinformatics Research and Applications, ISBRA 2009, held in Fort Lauderdale, FL, USA, in May 2009. The 26 revised full papers presented together four invited papers were carefully reviewed and selected from a total of 55 submissions. The papers cover a wide range of topics, including clustering and classification, gene expression analysis, gene networks, genome analysis, motif finding, pathways, protein structure prediction, protein domain interactions, phylogenetics, and software tools.

Bachelorarbeit aus dem Jahr 2020 im Fachbereich BWL - Customer-Relationship-Management, CRM, Note: 2,0, Hochschule Wismar, Sprache: Deutsch, Abstract: Das Ziel der Arbeit ist es, aufzuzeigen, wie durch Data Mining das Kundenbeziehungsmanagement verbessert werden kann. Die Einsatzmöglichkeiten im Bereich des CRMs sollen dazu dienen, sowohl den Prozess als auch den Service zu verbessern. Die Wünsche des Kunden müssen beachtet und einbezogen werden. Es soll mithilfe des Data Mining eine gute Beziehung zwischen Kunden und Unternehmen aufgebaut werden, um die Kunden langfristig an das Unternehmen zu binden und Vertrauen aufzubauen. Wichtig ist aufzuzeigen, wie anhand der Methoden und Prozesse die Gewinnung von Daten und die dahinter verborgenen Strukturen und Muster erkannt und gezielt eingesetzt werden können, um sich Vorteile gegenüber den Wettbewerbern zu verschaffen. Ein zentraler Baustein langfristiger Kundenbindung ist die Erkenntnis, wie Kunden in bestimmten Situationen reagieren, um sie bereits vorab bei der Lösung ihrer Probleme unterstützen zu können. Darüber hinaus ist es im Bereich des Kundenbindungslebenszyklus maßgebend zu erkennen, welche Zielgruppen Potenzial aufweisen gewonnen zu werden, welche Kunden gehalten werden sollten und welche Kunden auf Dauer zu viele Ressourcen binden. Stellt sich in einem Unternehmen in dieser Hinsicht ein funktionierender Zyklus dar, ist ein gutes Beziehungsmanagement gewährleistet.

Zementfreie Hüftendoprothese: minimalinvasiver anteriorer ZugangDas Buch: beschreibt die Implantation eines künstlichen Hüftgelenks am Beispiel der  ZimmerBiomet Pfanne Allofit und des Schaftes MLP-Taper. Der Schwerpunkt liegt dabei auf der Praxis: die Operation wird Schritt für Schritt beschrieben. Dabei wird besonderes Augenmerk auf die Fallstricke während der Operation gelegt. Neben den zahlreichen brillanten Grafiken und Fotos, die die Operation visualisieren, wird der Operationsverlauf in einem Gesamtvideo und in 7 Clips zu den einzelnen Operationsschritten demonstriert. So ist die Umsetzung der Theorie in die Praxis auf kurzem Weg möglich.Die Videos: einfach die SN More Media App kostenfrei herunterladen, das Standbild im letzten Kapitel des Buches oder die 7 Standbilder zu den Einzelsequenzen scannen und die Videos streamen.     Aus dem InhaltIndikation - Kontraindikation - Operationsvorbereitung - Lagerung - Hautschnitt - Tiefe Präparation des MTFL und der Gelenkkapsel - Femurosteotomie und Hüftkopfresektion - Präparation Acetabulum und Pfannenimplantation - Präparation proximales Femur und Femurschaftimplantation - Postoperative Mobilisation - Video.    Der AutorProf. Dr. med. M. Rudert, Ärztlicher Direktor der Orthopädischen Klinik, König-Ludwig-Haus Würzburg

This book describes how smart cities can be designed with data at their heart, moving from a broad vision to a consistent city-wide collaborative configuration of activities.

In this groundbreaking work, Seth Stephens-Davidowitz, a Harvard-trained economist, former Google data scientist, and New York Times writer, argues that much of what we thought about people has been dead wrong. The reason? People lie, to friends, lovers, doctors, surveys?and themselves. However, we no longer need to rely on what people tell us. New data from the internet?the traces of information that billions of people leave on Google, social media, dating, and even pornography sites?finally reveals the truth.Everybody Lies combines the informed analysis of Nate Silver's The Signal and the Noise, the storytelling of Malcolm Gladwell's Outliers, and the wit and fun of Stephen Dubner and Steven Levitt's Freakonomics in a book that will change the way you view the world. There is almost no limit to what can be learned about human nature from Big Data?provided, that is, you ask the right questions.

This book constitutes the refereed proceedings of the 8th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, SBP 2015, held in Washington, DC, USA, in March/April 2015. The 24 full papers presented together with 36 poster papers were carefully reviewed and selected from 118 submissions. The goal of the conference was to advance our understanding of human behavior through the development and application of mathematical, computational, statistical, simulation, predictive and other models that provide fundamental insights into factors contributing to human socio-cultural dynamics. The topical areas addressed by the papers are social and behavioral sciences, health sciences, engineering, computer and information science.

This brief presents four practical methods to effectively explore causal relationships, which are often used for explanation, prediction and decision making in medicine, epidemiology, biology, economics, physics and social sciences. The first two methods apply conditional independence tests for causal discovery. The last two methods employ association rule mining for efficient causal hypothesis generation, and a partial association test and retrospective cohort study for validating the hypotheses. All four methods are innovative and effective in identifying potential causal relationships around a given target, and each has its own strength and weakness. For each method, a software tool is provided along with examples demonstrating its use. Practical Approaches to Causal Relationship Exploration is designed for researchers and practitioners working in the areas of artificial intelligence, machine learning, data mining, and biomedical research. The material also benefits advanced students interested in causal relationship discovery.

This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications.The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems. Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource.

This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Cybernetics, Lanzhou, China, in July 2014. The 45 revised full papers presented were carefully reviewed and selected from 421 submissions. The papers are organized in topical sections on classification and semi-supervised learning; clustering and kernel; application to recognition; sampling and big data; application to detection; decision tree learning; learning and adaptation; similarity and decision making; learning with uncertainty; improved learning algorithms and applications.

This book constitutes the refereed proceedings of the 13th Pacific Rim Conference on Artificial Intelligence, PRICAI 2014, held in Gold Coast, Queensland, Australia, in December 2014. The 74 full papers and 20 short papers presented in this volume were carefully reviewed and selected from 203 submissions. The topics include inference; reasoning; robotics; social intelligence. AI foundations; applications of AI; agents; Bayesian networks; neural networks; Markov networks; bioinformatics; cognitive systems; constraint satisfaction; data mining and knowledge discovery; decision theory; evolutionary computation; games and interactive entertainment; heuristics; knowledge acquisition and ontology; knowledge representation, machine learning; multimodal interaction; natural language processing; planning and scheduling; probabilistic.

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.

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.

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.

The two-volume set of LNCS 10941 and 10942 constitutes the proceedings of the 9th International Conference on Advances in Swarm Intelligence, ICSI 2018, held in Shanghai, China, in June 2018. The total of 113 papers presented in these volumes was carefully reviewed and selected from 197 submissions. The papers were organized in topical sections namely: multi-agent systems; swarm robotics; fuzzy logic approaches; planning and routing problems; recommendation in social media; predication; classification; finding patterns; image enhancement; deep learning; theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithm; bacterial foraging optimization; artificial immune system; hydrologic cycle optimization; other swarm-based optimization algorithms; hybrid optimization algorithms; multi-objective optimization; large-scale global optimization.

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 book constitutes the refereed proceedings of the 15th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2014, held in Salamanca, Spain, in September 2014.The 60 revised full papers presented were carefully reviewed and selected from about 120 submissions. These papers provided a valuable collection of recent research outcomes in data engineering and automated learning, from methodologies, frameworks, and techniques to applications. In addition the conference provided a good sample of current topics from methodologies, frameworks, and techniques to applications and case studies. The techniques include computational intelligence, big data analytics, social media techniques, multi-objective optimization, regression, classification, clustering, biological data processing, text processing, and image/video analysis.

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.

Information System Development-Improving Enterprise Communication are the collected proceedings of the 22nd International Conference on Information Systems Development: Improving Enterprise Communication-ISD 2013 Conference, held in Seville, Spain. It follows in the tradition of previous conferences in the series in exploring the connections between industry, research and education.These proceedings represent ongoing reflections within the academic community on established information systems topics and emerging concepts, approaches and ideas. It is hoped that the papers herein contribute towards disseminating research and improving practice.The conference tracks highlighted at the 22nd International Conference on Information Systems Development (ISD 2013) were:ApplicationsData and OntologiesEnd UsersEnterprise EvolutionIndustrial cases in ISDIntelligent Business Process ManagementModel Driven Engineering in ISDNew TechnologiesProcess ManagementQuality

This book constitutes the refereed proceedings of the 8th International Conference on Flexible Query Answering Systems, FQAS 2011, held in Roskilde, Denmark, in October 2011. The 43 papers included in this volume were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on logical approaches to flexible querying, fuzzy logic in spatial and temporal data modeling and querying, knowledge-based approaches, multimedia, data fuzziness, reliability and trust, information retrieval, preference queries, flexible querying of graph data, ranking, ordering and statistics, query recommendation and interpretation, as well as on fuzzy databases and applications (8 papers presented in a special session).

This book constitutes the refereed proceedings of the 14th International Conference on Discovery Science, DS 2011, held in Espoo, Finland, in October 2011 - co-located with ALT 2011, the 22nd International Conference on Algorithmic Learning Theory. The 24 revised full papers presented together with 5 invited lectures were carefully revised and selected from 56 submissions. The papers cover a wide range including the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their application to knowledge discovery.

This book constitutes the thoroughly refereed revised selected papers of the First Workshop on Big Data Benchmarks, WBDB 2012, held in San Jose, CA, USA, in May 2012 and the Second Workshop on Big Data Benchmarks, WBDB 2012, held in Pune, India, in December 2012.The 14 revised papers presented were carefully reviewed and selected from 60 submissions. The papers are organized in topical sections on benchmarking, foundations and tools; domain specific benchmarking; benchmarking hardware and end-to-end big data benchmarks.