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The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning technique to train itself in an unsupervised manner. SOMs are different from other artificial neural networks in the sense that they use a neighborhood function to preserve the topological properties of the input space and they have been used to create an ordered representation of multi-dimensional data which simplifies complexity and reveals meaningful relationships. Prof. T. Kohonen in the early 1980s first established the relevant theory and explored possible applications of SOMs. Since then, a number of theoretical and practical applications of SOMs have been reported including clustering, prediction, data representation, classification, visualization, etc. This book was prompted by the desire to bring together some of the more recent theoretical and practical developments on SOMs and to provide the background for future developments in promising directions. The book comprises of 25 Chapters which can be categorized into three broad areas: methodology, visualization and practical applications.
Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data mining
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Contributes to the subject of mining time-changing data streams and addresses the design of learning algorithms for this purpose. This book introduces contributions on several different aspects of the problem, identifying research opportunities and increasing the scope for applications.
Data mining. --- Pattern recognition systems. --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching
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With the recent flourishing research activities on Web search and mining, social network analysis, information network analysis, information retrieval, link analysis, and structural data mining, research on link mining has been rapidly growing, forming a new field of data mining. Traditional data mining focuses on "flat" or “isolated” data in which each data object is represented as an independent attribute vector. However, many real-world data sets are inter-connected, much richer in structure, involving objects of heterogeneous types and complex links. Hence, the study of link mining will have a high impact in various important applications such as Web and text mining, social network analysis, collaborative filtering, and bioinformatics. Link Mining: Models, Algorithms and Applications focuses on the theory and techniques as well as the related applications for link mining, especially from an interdisciplinary point of view. Due to the high popularity of linkage data, extensive applications ranging from governmental organizations to commercial businesses to people's daily life call for exploring the techniques of mining linkage data. This book provides a comprehensive coverage of the link mining models, techniques and applications. Each chapter is contributed from some well known researchers in the field. Link Mining: Models, Algorithms and Applications is designed for researchers, teachers, and advanced-level students in computer science. This book is also suitable for practitioners in industry.
Data mining. --- Marketing -- Data processing. --- Data mining --- Biology --- Engineering & Applied Sciences --- Health & Biological Sciences --- Computer Science --- Biology - General --- Database searching. --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Life sciences. --- Bioinformatics. --- Computational biology. --- Life Sciences. --- Data Mining and Knowledge Discovery. --- Computational Biology/Bioinformatics. --- Computer Appl. in Life Sciences. --- Database searching --- Electronic information resource searching --- Data processing. --- Bio-informatics --- Biological informatics --- Information science --- Computational biology --- Systems biology --- Data processing --- Bioinformatics . --- Computational biology . --- Bioinformatics
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This book deals with knowledge discovery and data mining in spatial and temporal data, seeking to present novel methods that can be employed to discover spatial structures and processes in complex data. Spatial knowledge discovery is examined through the tasks of clustering, classification, association/relationship, and process. Among the covered topics are discovery of spatial structures as natural clusters, identification of separation surfaces and extraction of classification rules from statistical and algorithmic perspectives, detecting local and global aspects of non-stationarity of spatial associations and relationships, unraveling scaling behaviors of time series data, including self-similarity, and long range dependence. Particular emphasis is placed on the treatment of scale, noise, imperfection and mixture distribution. Numerical examples and a wide scope of applications are used throughout the book to substantiate the conceptual and theoretical arguments.
Spatial analysis (Statistics) --- Cluster analysis --- Data mining. --- Data mining --- Management Theory --- Computer Science --- Communities - Urban Groups --- Management --- Engineering & Applied Sciences --- Sociology & Social History --- Business & Economics --- Social Sciences --- Data processing. --- Knowledge acquisition (Expert systems) --- Culture --- Geography. --- Statistics. --- Regional economics. --- Spatial economics. --- Cultural and Media Studies. --- Regional and Cultural Studies. --- Statistics, general. --- Data Mining and Knowledge Discovery. --- Regional/Spatial Science. --- Geography, general. --- Study and teaching. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Acquisition, Knowledge (Expert systems) --- Expertise acquisition (Expert systems) --- Expert systems (Computer science)
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The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time financial data, system control datasets, .... The analysis of this data poses new challenging problems and requires the development of novel statistical models and computational methods, fueling many fascinating and fast growing research areas of modern statistics. The book offers a wide variety of statistical methods and is addressed to statisticians working at the forefront of statistical analysis.
Mathematical statistics -- Data processing -- Congresses. --- Mathematical statistics -- Data processing. --- Mathematical statistics. --- Mathematical statistics --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Data processing --- Database design --- Statistical methods. --- Data base design --- Mathematics. --- Data mining. --- Computer software. --- Statistics. --- Mathematical Software. --- Statistics and Computing/Statistics Programs. --- Statistical Theory and Methods. --- Data Mining and Knowledge Discovery. --- System design --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Software, Computer --- Computer systems --- Statistical methods --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Statistics and Computing. --- Data processing.
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Every business has reams of business data locked away in databases, business systems, and spreadsheets. While you may be able to build some reports by pulling a few of these repositories together, actually performing any kind of analysis on the data that runs your business can range from problematic to impossible. Pro SQL Server 2008 Analysis Services will show you how to pull that data together and present it for reporting and analysis in a way that makes the data accessible to business users, instead of needing to rely on the IT department every time someone needs a different report. Accessible—With a single author's voice, this book conducts a guided tour through the technology that makes it easy to dive into. Solution–oriented—While technically deep, the goal is to focus on practical application of the technologies instead of acting as a technical manual. Comprehensive—This book covers every aspect of analysis services and ancillary technologies to enable you to make the most of SQL Server.
Information Technology --- General and Others --- Client/server computing. --- Computing, Client/server --- SQL server. --- Microsoft SQL server --- Computer science. --- Data mining. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Informatics --- Science --- Electronic data processing --- Distributed processing --- Database management. --- Database Management. --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management
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Intelligent agents (Computer software) --- Distributed artificial intelligence. --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- DAI (Artificial intelligence) --- Distributed AI (Artificial intelligence) --- Artificial intelligence --- Agents, Autonomous (Computer software) --- Agents, Cognitive (Computer software) --- Agents, Intelligent (Computer software) --- Assistants, Cognitive (Computer software) --- Assistants, Intelligent software --- Autonomous agents (Computer software) --- Cognitive agents (Computer software) --- Cognitive assistants (Computer software) --- IAs (Computer software) --- Intelligent agent software --- Intelligent software agents --- Intelligent software assistants --- Software agents (Computer software) --- Special agents (Computer software) --- Computer programs
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Welcome to the Proceedings of the 2010 International Conference on Advanced Software Engineering and Its Applications (ASEA 2010) – one of the partnering events of the Second International Mega-Conference on Future Generation Information Technology (FGIT 2010). ASEA brings together researchers from academia and industry as well as practitioners to share ideas, problems and solutions relating to the multifaceted aspects of software engineering, including its links to computational sciences, mathematics and information technology. In total, 1,630 papers were submitted to FGIT 2010 from 30 countries, which includes 175 papers submitted to ASEA 2010. The submitted papers went through a rigorous reviewing process: 395 of the 1,630 papers were accepted for FGIT 2010, while 40 papers were accepted for ASEA 2010. Of the 640 papers were selected for the special FGIT 2010 volume published by Springer in the LNCS series. 32 papers are published in this volume, and 2 papers were withdrawn due to technical reasons. We would like to acknowledge the great effort of the ASEA 2010 International Advisory Board and members of the International Program Committee, as well as all the organizations and individuals who supported the idea of publishing this volume of proceedings, including SERSC and Springer. Also, the success of the conference would not have been possible without the huge support from our sponsors and the work of the Chairs and Organizing Committee.
Engineering & Applied Sciences --- Computer Science --- Information Technology --- Software Engineering --- Computer science. --- Computer communication systems. --- Software engineering. --- Computer programming. --- Data mining. --- Computer Science. --- Software Engineering. --- Software Engineering/Programming and Operating Systems. --- Computer Communication Networks. --- Data Mining and Knowledge Discovery. --- Information Systems Applications (incl. Internet). --- Programming Techniques. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Computers --- Electronic computer programming --- Electronic data processing --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Computer software engineering --- Engineering --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Informatics --- Science --- Programming --- Distributed processing --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Computer engineering --- Software engineering --- System design
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During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for “Extraction et Gestion des Connaissances” in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.
Data mining --- Knowledge management --- Information retrieval --- Semantic Web --- Engineering & Applied Sciences --- Computer Science --- Data mining. --- Database management. --- Knowledge management. --- Management of knowledge assets --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Soft computing --- Database searching --- Management --- Information technology --- Intellectual capital --- Organizational learning --- Artificial Intelligence.
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Computer programming --- Engineering & Applied Sciences --- Computer Science --- Information Technology --- Software Engineering --- Computer programming. --- Computers --- Electronic computer programming --- Electronic data processing --- Electronic digital computers --- Programming (Electronic computers) --- Programming --- Computer science. --- Software engineering. --- Programming languages (Electronic computers). --- Data mining. --- Management information systems. --- Computer Science. --- Software Engineering/Programming and Operating Systems. --- Programming Languages, Compilers, Interpreters. --- Data Mining and Knowledge Discovery. --- Software Engineering. --- Management of Computing and Information Systems. --- Programming Techniques. --- Coding theory --- Information Systems. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Informatics --- Science --- Computer software engineering --- Engineering --- Computer languages --- Computer program languages --- Computer programming languages --- Machine language --- Languages, Artificial --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Communication systems --- Compilers (Computer programs). --- Compilers and Interpreters. --- IT Operations. --- Management. --- Compiling programs (Computer programs) --- Computer programs --- Programming software --- Systems software
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