Java Data Mining: Strategy, Standard, and Practice PDF Download

Author: Mark F. Hornick
Publisher: Elsevier
ISBN: 0080495915
Category : Computers
Languages : en
Pages : 545

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Book Description
Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component. This book is the essential guide to the usage of the JDM standard interface, written by contributors to the JDM standard. - Data mining introduction - an overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems - JDM essentials - concepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects - JDM in practice - the use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API - Free, downloadable KJDM source code referenced in the book available here

Author: Joe Celko
Publisher: Morgan Kaufmann
ISBN: 008055752X
Category : Computers
Languages : en
Pages : 383

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Book Description
Perfectly intelligent programmers often struggle when forced to work with SQL. Why? Joe Celko believes the problem lies with their procedural programming mindset, which keeps them from taking full advantage of the power of declarative languages. The result is overly complex and inefficient code, not to mention lost productivity.This book will change the way you think about the problems you solve with SQL programs.. Focusing on three key table-based techniques, Celko reveals their power through detailed examples and clear explanations. As you master these techniques, you'll find you are able to conceptualize problems as rooted in sets and solvable through declarative programming. Before long, you'll be coding more quickly, writing more efficient code, and applying the full power of SQL - Filled with the insights of one of the world's leading SQL authorities - noted for his knowledge and his ability to teach what he knows - Focuses on auxiliary tables (for computing functions and other values by joins), temporal tables (for temporal queries, historical data, and audit information), and virtual tables (for improved performance) - Presents clear guidance for selecting and correctly applying the right table technique

Author: W.H. Inmon
Publisher: Elsevier
ISBN: 008055833X
Category : Computers
Languages : en
Pages : 394

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Book Description
DW 2.0: The Architecture for the Next Generation of Data Warehousing is the first book on the new generation of data warehouse architecture, DW 2.0, by the father of the data warehouse. The book describes the future of data warehousing that is technologically possible today, at both an architectural level and technology level. The perspective of the book is from the top down: looking at the overall architecture and then delving into the issues underlying the components. This allows people who are building or using a data warehouse to see what lies ahead and determine what new technology to buy, how to plan extensions to the data warehouse, what can be salvaged from the current system, and how to justify the expense at the most practical level. This book gives experienced data warehouse professionals everything they need in order to implement the new generation DW 2.0. It is designed for professionals in the IT organization, including data architects, DBAs, systems design and development professionals, as well as data warehouse and knowledge management professionals. - First book on the new generation of data warehouse architecture, DW 2.0 - Written by the "father of the data warehouse", Bill Inmon, a columnist and newsletter editor of The Bill Inmon Channel on the Business Intelligence Network - Long overdue comprehensive coverage of the implementation of technology and tools that enable the new generation of the DW: metadata, temporal data, ETL, unstructured data, and data quality control

Author: Sašo Džeroski
Publisher: Springer Science & Business Media
ISBN: 1441977384
Category : Computers
Languages : en
Pages : 458

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Book Description
This book is about inductive databases and constraint-based data mining, emerging research topics lying at the intersection of data mining and database research. The aim of the book as to provide an overview of the state-of- the art in this novel and - citing research area. Of special interest are the recent methods for constraint-based mining of global models for prediction and clustering, the uni?cation of pattern mining approaches through constraint programming, the clari?cation of the re- tionship between mining local patterns and global models, and the proposed in- grative frameworks and approaches for inducive databases. On the application side, applications to practically relevant problems from bioinformatics are presented. Inductive databases (IDBs) represent a database view on data mining and kno- edge discovery. IDBs contain not only data, but also generalizations (patterns and models) valid in the data. In an IDB, ordinary queries can be used to access and - nipulate data, while inductive queries can be used to generate (mine), manipulate, and apply patterns and models. In the IDB framework, patterns and models become ”?rst-class citizens” and KDD becomes an extended querying process in which both the data and the patterns/models that hold in the data are queried.

Author: Satnam Alag
Publisher: Simon and Schuster
ISBN: 163835538X
Category : Computers
Languages : en
Pages : 609

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Book Description
There's a great deal of wisdom in a crowd, but how do you listen to a thousand people talking at once? Identifying the wants, needs, and knowledge of internet users can be like listening to a mob. In the Web 2.0 era, leveraging the collective power of user contributions, interactions, and feedback is the key to market dominance. A new category of powerful programming techniques lets you discover the patterns, inter-relationships, and individual profiles-the collective intelligence--locked in the data people leave behind as they surf websites, post blogs, and interact with other users. Collective Intelligence in Action is a hands-on guidebook for implementing collective intelligence concepts using Java. It is the first Java-based book to emphasize the underlying algorithms and technical implementation of vital data gathering and mining techniques like analyzing trends, discovering relationships, and making predictions. It provides a pragmatic approach to personalization by combining content-based analysis with collaborative approaches. This book is for Java developers implementing Collective Intelligence in real, high-use applications. Following a running example in which you harvest and use information from blogs, you learn to develop software that you can embed in your own applications. The code examples are immediately reusable and give the Java developer a working collective intelligence toolkit. Along the way, you work with, a number of APIs and open-source toolkits including text analysis and search using Lucene, web-crawling using Nutch, and applying machine learning algorithms using WEKA and the Java Data Mining (JDM) standard. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

Author: Michael zur Muehlen
Publisher: Springer
ISBN: 3642205119
Category : Computers
Languages : en
Pages : 800

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Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of nine international workshops held in Hoboken, NJ, USA, in conjunction with the 8th International Conference on Business Process Management, BPM 2010, in September 2010. The nine workshops focused on Reuse in Business Process Management (rBPM 2010), Business Process Management and Sustainability (SusBPM 2010), Business Process Design (BPD 2010), Business Process Intelligence (BPI 2010), Cross-Enterprise Collaboration, People, and Work (CEC-PAW 2010), Process in the Large (IW-PL 2010), Business Process Management and Social Software (BPMS2 2010), Event-Driven Business Process Management (edBPM 2010), and Traceability and Compliance of Semi-Structured Processes (TC4SP 2010). In addition, three papers from the special track on Advances in Business Process Education are also included in this volume. The overall 66 revised full papers presented were carefully reviewed and selected from 143 submissions.

Author: Witold Abramowicz
Publisher: Springer
ISBN: 3642128149
Category : Computers
Languages : en
Pages : 314

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Book Description
This book contains the refereed proceedings of the 13th International Conference on Business Information Systems, BIS 2010, held in Berlin, Germany, in May 2010. The 25 revised full papers were carefully reviewed and selected from more than 80 submissions. Following the theme of the conference "Future Internet Business Services", the contributions detail recent research results and experiences and were grouped in eight sections on search and knowledge sharing, data and information security, Web experience modeling, business processes and rules, services and repositories, data mining for processes, visualization in business process management, and enterprise resource planning and supply chain management.

Author:
Publisher: PediaPress
ISBN:
Category :
Languages : en
Pages : 661

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Book Description

Author: Anne Hakansson
Publisher: Springer
ISBN: 3642016650
Category : Computers
Languages : en
Pages : 884

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Book Description
This volume contains the proceedings of the Third KES Symposium on Agent and Multi-agent Systems – Technologies and Applications (KES-AMSTA 2009)––held at Uppsala University in Sweden during June 3-5, 2009. The symposium was organized by Uppsala University, KES International and its Focus Group on Agent and Multi-agent Systems. The KES-AMSTA Symposium series is a sub-series of the KES Conference series. Following the successes of the First KES Symposium on Agent and Multi-agent Systems – Technologies and Applications (KES-AMSTA 2007), held in Wroclaw, Poland, from May 31 to 1 June 2007––and the Second KES Symposium on Agent and Multi-agent Systems – Technologies and Applications (KES-AMSTA 2008) held in Incheon, Korea, March 26-28, 2008––KES-AMSTA 2009 featured keynote talks, oral and poster presentations, and a number of workshops and invited sessions, closely aligned to the themes of the conference. The aim of the symposium was to provide an international forum for scientific - search into the technologies and applications of agent and multi-agent systems. Agent and multi-agent systems are an innovative type of modern software system and have long been recognized as a promising technology for constructing autonomous, c- plex and intelligent systems. A key development in the field of agent and multi-agent systems has been the specification of agent communication languages and formali- tion of ontologies. Agent communication languages are intended to provide standard declarative mechanisms for agents to communicate knowledge and make requests of each other, whereas ontologies are intended for conceptualization of the knowledge domain.

Author: Glenn J. Myatt
Publisher: John Wiley & Sons
ISBN: 0470222808
Category : Mathematics
Languages : en
Pages : 325

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Book Description
A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series (www.makingsenseofdata.com) provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization.