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Data Mining and Data Visualization

Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book;

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Text Mining and Visualization

Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular;

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Text Mining and Visualization

Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular;

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The Text Mining Handbook

visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection in such varied;

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Text Mining

Text Mining: Applications and Theory presents thestate-of-the-art algorithms for text mining from both the academicand industrial;

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Computer Applications in the Mineral Industries

This text covers the use of computer applications in the mineral industries, encompassing topics such as the use of computer visualization;

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5th International Symposium on Data Mining Applications

, algorithms, models, and theory.* Text Mining: Semantic analysis and mining text in Arabic, semi-structured, streaming, multimedia data.* Framework;

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Biodata Mining And Visualization

There is a lack of an exposition on interdisciplinary and innovative methods of data mining and visualization for biodata. This book fills;

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Information Management and Big Data

122 submissions. The papers address topics such as natural language processing and text mining; machine learning; image processing; social;

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Advances in Knowledge Discovery and Data Mining

supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and;

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Advances in Knowledge Discovery and Data Mining

supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and;

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Advances in Knowledge Discovery and Data Mining

supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and;

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Visualizing with Text

space of text in visualization. The book illustrates many new kinds of visualizations, including microtext lines, skim formatting, and;

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Visualizing with Text

space of text in visualization. The book illustrates many new kinds of visualizations, including microtext lines, skim formatting, and;

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Managing Data Mining Technologies in Organizations

their applications for data mining. The chapters illustrate applications of data mining and visualization for credit screening, forecasting;

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Data Fusion and Data Mining for Power System Monitoring

Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining;

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Data Fusion and Data Mining for Power System Monitoring

Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining;

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Introduction to Data Mining and its Applications

This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents;

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Data Mining

, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining Part II;

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Data Mining

, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining Part II;

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Bioinformatics in Personalized Medicine

in topical sections on next-generation sequencing data; genome-wide association studies; high-performanced databases; text-mining; tools for;

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Data Mining and Decision Support

Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area;

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Introduction To Data Mining And Analytics

of big data and of text and image data mining. The text concludes by describing an analyst's steps from planning through execution, ensuring;

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Data Mining for Business Intelligence

literature. computingreviews.com Incorporating a new focus on data visualization and time series forecasting, Data Mining for Business Intelligence;

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Data Science

, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing;

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Bioinformatics Research and Applications

and selected from 131 submissions. They cover topics such as: biomarker discovery; biomedical databases and data integration; biomedical text;

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Data Mining for Business Analytics

, recommender systems, clustering, text mining and network analysis. It also includes: Two new co-authors, Inbal Yahav and Casey Lichtendahl;

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