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Advanced Data Mining and Applications

This book constitutes the refereed proceedings of the 13th International Conference on Advanced Data Mining and Applications, ADMA 2017;

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Advanced Analysis and Learning on Temporal Data

classification and clustering with challenging applications on medicine or earth observation data. These works show different ways to consider temporal;

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Foundations of Intelligent Systems

, Special Session on Intelligent Methodologies for Traffic Data Analysis and Mining, and Special Session on Advanced Methods in Machine Learning for;

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Analysis Of Multi-temporal Remote Sensing Images - Proceedings Of The First International Workshop On Multitemp 2001

-temporal remote sensing data and advanced analysis methodologies results in the possibility of solving complex problems related to the monitoring;

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Temporal Data Mining via Unsupervised Ensemble Learning

unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed;

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Introduction to Computational Health Informatics

focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer;

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Introduction to Computational Health Informatics

focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer;

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Foundations of Intelligent Systems

and Soft Clustering for Data Science, Special Session on Knowledge Discovery with Formal Concept Analysis and Related Formalisms, and Special;

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Database Systems for Advanced Applications

index; spatio-temporal data; modern computing platform; social networks; information integration and data quality; information retrieval and;

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Visual Insights

. Readers will learn to apply advanced data mining and visualization techniques to make sense of temporal, geospatial, topical, and network data;

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Web Technologies and Applications

selected from 215 submissions. the focus of the conference was on following subjects: Spatio-temporal, Textual and Multimedia Data;

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Web Technologies and Applications

and Multimedia Data Management Social Media Data Analysis Modelling and Learning with Big Data Streaming and Real-time Data;

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Foundations of Computational Intelligence 06

-III: Applications Part I on Data Click Streams and Temporal Data Mining contains four chapters that describe several approaches in Data Click;

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Database Systems for Advanced Applications

embedding; recommendation; graph and network processing; social network analytics; sequence and temporal data processing; trajectory and streaming;

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Database Systems for Advanced Applications

embedding; recommendation; graph and network processing; social network analytics; sequence and temporal data processing; trajectory and streaming;

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Advances in Spatio-Temporal Analysis

geographical information systems. Spatio-temporal analysis embodies spatial modelling, spatio-temporal modelling and spatial reasoning and data mining;

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Advanced Data Analytics Using Python

Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark;

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Advanced Data Analytics Using Python

Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark;

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Practical Time Series Analysis Prediction with Statistics and Machine Learning

series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use;

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Wide Area Monitoring of Interconnected Power Systems

This book provides a compact yet comprehensive treatment of advanced data-driven signal processing techniques for the analysis and;

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Financial Signal Processing and Machine Learning

market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and;

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Machine Learning on Geographical Data Using Python

Get up and running with the basics of geographic information systems (GIS), geospatial analysis, and machine learning on spatial data;

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Database Systems for Advanced Applications

; index; query analysis; XML data management; privacy protection; and uncertain data management; and in part 2: graph data management; physical;

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Database Systems for Advanced Applications

; index; query analysis; XML data management; privacy protection; and uncertain data management; and in part 2: graph data management; physical;

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Statistics for Spatio-Temporal Data

-Temporal Data is an excellent book for a graduate-level course on spatio-temporal statistics. It is also a valuable reference for researchers and;

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Discovery Science

scientific domains. The papers are organized in the following topical sections: Advanced Machine Learning; Applications; Data and Knowledge;

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Temporal Modelling of Customer Behaviour

This book describes advanced machine learning models - such as temporal collaborative filtering, stochastic models and Bayesian;

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