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Spatial Data Mining

edition in 2006 and the second in 2013). It offers a systematic and practical overview of spatial data mining, which combines computer science;

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Advanced Data Mining and Applications

algorithms, mining on data streams, graph mining, spatial data mining, multimedia data mining, Web mining, the Internet of Things, health informatics;

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Quality Aspects in Spatial Data Mining

Describes the State-of-the-Art in Spatial Data Mining, Focuses on Data Quality Substantial progress has been made toward developing;

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Quality Aspects in Spatial Data Mining

Describes the State-of-the-Art in Spatial Data Mining, Focuses on Data Quality Substantial progress has been made toward developing;

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Preference-based Spatial Co-location Pattern Mining

The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous;

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Uncertainty Modelling and Quality Control for Spatial Data

aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book;

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Uncertainty Modelling and Quality Control for Spatial Data

aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book;

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Data Mining

Thorough in its coverage from basic to advanced topics, this book presents the key algorithms and techniques used in data mining. An;

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Geographic Data Mining and Knowledge Discovery

first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and;

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Advances in Data and Web Management

, P2P systems, sensor networks, spatial and temporal databases, Web mining, XML and semi-structured data, privacy and security, as well as data;

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Advances in Geo-Spatial Information Science

-spatial information science (such as spatial data mining, mobile data modeling, and location-based services). The book contains selected and;

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Spatial Data Handling in Big Data Era

discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data;

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Advances in Knowledge Discovery and Data Mining

uncertain and imprecise data; mining temporal and spatial data; feature extraction and selection; mining heterogeneous, high-dimensional, and;

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Advances in Knowledge Discovery and Data Mining

uncertain and imprecise data; mining temporal and spatial data; feature extraction and selection; mining heterogeneous, high-dimensional and;

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Spatial Data Management

Spatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric;

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Spatial Data Handling in Big Data Era

discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data;

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Advanced Data Mining and Applications

; Recommender Systems; Social Network and Social Media; Behavior Modeling and User Profiling; Text and Multimedia Mining; Spatial-Temporal Data; Medical;

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Data Mining

This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications;

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Data Mining

This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications;

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Advances in Knowledge Discovery and Data Mining

multi-media/multi-dimensional data; application; mining graph and network data; anomaly detection and analytics; mining spatial, temporal;

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Advances in Knowledge Discovery and Data Mining

multi-media/multi-dimensional data; application; mining graph and network data; anomaly detection and analytics; mining spatial, temporal;

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Spatial Big Data Science

Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management;

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Contrast Data Mining

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and;

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Data Analytics for Drilling Engineering

This book presents the signal processing and data mining challenges encountered in drilling engineering, and describes the methods used to;

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Data Analytics for Drilling Engineering

This book presents the signal processing and data mining challenges encountered in drilling engineering, and describes the methods used to;

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Foundations of Intelligent Systems

informatics, intelligent information systems, knowledge-based systems, mining temporal, spatial and spatio-temporal data, text and Web mining;

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Database Systems for Advanced Applications

management; indexing and distributed systems; network embedding; trajectory and time series data processing; data mining; query processing and;

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