Data mining

Ready to take your IT skills to the healthcare industry?

To help you navigate the large number of new data tools available, this guide describes 60 of the most recent innovations, from NoSQL databases and MapReduce approaches to machine learning and visualization tools.

Learn how to leverage MongoDB with your Python applications, using the hands-on recipes in this book.

Today's mobile devices have GPS and standard APIs to give you access to coordinatesbut what can you do with that data?

If you're looking for a scalable storage solution to accommodate a virtually endless amount of data, this book shows you how Apache HBase can fulfill your needs.

Arguably the most capable of all the open source databases, PostgreSQL is an object-relational database management system first developed in 1977 by the University of California at Berkeley.

Arguably the most capable of all the open source databases, PostgreSQL is an object-relational database management system first developed in 1977 by the University of California at Berkeley.

Getting started with MongoDB is easy, but once you begin building applications with it, you'll face some complex issues.

Getting started with MongoDB is easy, but once you begin building applications with it, you'll face some complex issues.

This practical guide offers a short course on scaling CouchDB to meet the capacity needs of your distributed application.

This practical guide offers a short course on scaling CouchDB to meet the capacity needs of your distributed application.

To help you navigate the large number of new data tools available, this guide describes 60 of the most recent innovations, from NoSQL databases and MapReduce approaches to machine learning and visualization tools.

Learn how to leverage MongoDB with your Python applications, using the hands-on recipes in this book.

Today's mobile devices have GPS and standard APIs to give you access to coordinatesbut what can you do with that data?

Create a MongoDB cluster that will grow to meet the needs of your application.

Create a MongoDB cluster that will grow to meet the needs of your application.

Millions of public Twitter streams harbor a wealth of data, and once you mine them, you can gain some valuable insights.

Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need.

This book constitutes revised papers from the International Workshops held at the 20th International Conference on Business Process Management, BPM 2022, in Munster, Germany, during September 11-15, 2022.

The University of Arizona Artificial Intelligence Lab (AI Lab) Dark Web project is a long-term scientific research program that aims to study and understand the international terrorism (Jihadist) phenomena via a computational, data-centric approach.

Complex systems are systems that comprise many interacting parts with the ability to generate a new quality of collective behavior through self-organization, e.

From fundamental techniques to advanced strategies for handling big data, visualization, and more, this book equips you with skills to excel in real-world data analysis projects.

This book discusses various partitioning strategies tailored for traditional machine learning algorithms.

The Data Preparation Journey: Finding Your Way With R introduces the principles of data preparation within in a systematic approach that follows a typical data science or statistical workflow.

Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research.

The papers in this volume are the refereed papers presented at AI-2012, the Thirty-second SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2012 in both the technical and the application streams.

Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation.

Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry.

The availability of geographic and geospatial information and services, especially on the open Web has become abundant in the last several years with the proliferation of online maps, geo-coding services, geospatial Web services and geospatially enabled applications.

Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research.

It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society.

Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers.

This book is about inductive databases and constraint-based data mining, emerging research topics lying at the intersection of data mining and database research.

Data mining is the process of extracting hidden patterns from data, and it's commonly used in business, bioinformatics, counter-terrorism, and, increasingly, in professional sports.

Managing and Mining Graph Data is a comprehensive survey book in graph management and mining.

The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades.

Intelligence and Security Informatics (ISI) is defined as the study of the development and use of advanced information systems and technologies for national, international, and societal security-related applications.

Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems.

Data Mining and Multi agent Integration aims to re?

Social computing is concerned with the study of social behavior and social c- text based on computational systems.

Earth Observation interacts with space, remote sensing, communication, and information technologies, and plays an increasingly significant role in Earth related scientific studies, resource management, homeland security, topographic mapping, and development of a healthy, sustainable environment and community.

Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data.

In order to be effective for their users, information retrieval (IR) systems should be adapted to the specific needs of particular environments.

A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today's often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures.

Shadow Algorithms Data Miner provides a high-level understanding of the complete set of shadow concepts and algorithms, addressing their usefulness from a larger graphics system perspective.

Data-intensive science has the potential to transform scientific research and quickly translate scientific progress into complete solutions, policies, and economic success.