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Multimedia information is ubiquitous and essential in many applications, and repositories of multimedia are numerous and extremely large. Consequently, researchers and professionals need new techniques and tools for extracting the hidden, useful knowledge embedded within multimedia collections, thereby helping them discover relationships between the various elements and using this knowledge in decision-making applications. Multimedia Data Mining and Knowledge Discovery, assembling the work of leading academic and professional/industrial researchers worldwide, provides an overview of the current state-of-the-art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research. Consisting of an introductory section and four topical parts, the book describes the objectives and current tendencies in multimedia data mining research and their applications. Each part contains an overview of its chapters and leads the reader with a structured approach through the diverse subjects in the field. Topics and Features: • Features a comprehensive introduction to multimedia data mining and its relevance today • Presents a global perspective of the field and its various components • Provides broad, yet thorough and detailed coverage of the subject • Numerous chapters reference websites with supplementary materials and demonstrations • Explores multimedia data exploration, multimedia data modeling and evaluation, and visualization • Offers an entire part devoted to applications and case studies Written with graduate students in mind, this much needed comprehensive survey of the current state of multimedia data mining and knowledge discovery will also serve as a valuable resource for researchers with interests in multimedia data mining, summarization, indexing, and retrieval.

Data mining. --- Multimedia systems. --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Information storage and retrieval systems --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Computer science. --- Database management. --- Information storage and retrieva. --- Computer Applications. --- Database Management. --- Multimedia Information Systems. --- Information Storage and Retrieval. --- Information Systems Applications (incl. Internet). --- Data Storage Representation. --- Information storage and retrieval. --- 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 --- Electronic data processing --- Informatics --- Science --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Application software. --- Multimedia information systems. --- Data structures (Computer science). --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software

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It is our great pleasure to welcome you to the 2020 ACM International Workshop on Security and Privacy Analytics - IWSPA 2020. This year's workshop is the sixth in the series and continues the tradition of being the premier forum for presentation of research results and experience reports on leading edge issues and applications/adaptations of data analytics (by which we mean techniques drawn from data mining, machine learning, statistics and natural language processing) to security challenges. Data analysis techniques also have serious implications on privacy. Because of these reasons, the first five ACM international workshops on security and privacy analytics were organized in 2015-2019. The mission of IWSPA is to create a forum for interaction between data analytics and security/privacy experts and to examine the questions raised in the previous workshops.The call for papers attracted 18 abstracts and 14 papers from Asia, Europe, and North America. Each paper was assigned to at least three program committee members for review, a total of 46 reviews were obtained with every paper receiving at least three reviews. The quality of the paper submissions was high this year. Consequently, five papers were accepted for presentation as full papers (11-page limit) and three were accepted as short papers (7-page limit). We also have a dataset and benchmarking paper in the proceedings this year.

Artificial intelligence --- Computer security --- Data mining --- Data protection

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Multimedia information is ubiquitous and essential in many applications, and repositories of multimedia are numerous and extremely large. Consequently, researchers and professionals need new techniques and tools for extracting the hidden, useful knowledge embedded within multimedia collections, thereby helping them discover relationships between the various elements and using this knowledge in decision-making applications. Multimedia Data Mining and Knowledge Discovery, assembling the work of leading academic and professional/industrial researchers worldwide, provides an overview of the current state-of-the-art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research. Consisting of an introductory section and four topical parts, the book describes the objectives and current tendencies in multimedia data mining research and their applications. Each part contains an overview of its chapters and leads the reader with a structured approach through the diverse subjects in the field. Topics and Features: ¢ Features a comprehensive introduction to multimedia data mining and its relevance today ¢ Presents a global perspective of the field and its various components ¢ Provides broad, yet thorough and detailed coverage of the subject ¢ Numerous chapters reference websites with supplementary materials and demonstrations ¢ Explores multimedia data exploration, multimedia data modeling and evaluation, and visualization ¢ Offers an entire part devoted to applications and case studies Written with graduate students in mind, this much needed comprehensive survey of the current state of multimedia data mining and knowledge discovery will also serve as a valuable resource for researchers with interests in multimedia data mining, summarization, indexing, and retrieval.

Computer science --- Information systems --- Computer. Automation --- gegevensopslag --- beeldverwerking --- ICT (informatie- en communicatietechnieken) --- IR (information retrieval) --- data mining --- multimedia --- informatiesystemen --- database management --- programmatielogica

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This two-volume set, LNAI 9651 and 9652, constitutes the thoroughly refereed proceedings of the 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, New Zealand, in April 2016. The 91 full papers were carefully reviewed and selected from 307 submissions. They are organized in topical sections named: classification; machine learning; applications; novel methods and algorithms; opinion mining and sentiment analysis; clustering; feature extraction and pattern mining; graph and network data; spatiotemporal and image data; anomaly detection and clustering; novel models and algorithms; and text mining and recommender systems.

Computer Science --- Engineering & Applied Sciences --- Computer science. --- Database management. --- Data mining. --- Information storage and retrieval. --- Artificial intelligence. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Artificial Intelligence (incl. Robotics). --- Information Storage and Retrieval. --- Information Systems Applications (incl. Internet). --- Database Management. --- 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 --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- 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 --- Informatics --- Science --- Artificial Intelligence. --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Data mining --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software

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Big data --- Data mining --- Data sets, Large --- Large data sets --- Data sets