|Total results: 80||
|Integration of Data Mining in Business Intelligence Systems
Ana Azevedo, Manuel Filipe Santos.
Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries.
Integration of Data Mining in Business Intelligence Systems investigates the...
Data Science and Simulation in Transportation Research
Davy Janssens, Ansar-Ul-Haque Yasar, Luk Knapen.
Given its effective techniques and theories from various sources and fields, data science is playing a vital role in transportation research and the consequences of the inevitable switch to electronic vehicles. This fundamental insight provides a step towards the solution of this important...
Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding
The prevalence of digital documentation presents some pressing concerns for efficient information retrieval in the modern age. Readers want to be able to access the information they desire without having to search through a mountain of unrelated data, so algorithms and methods for effectively seeking...
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
Shafiq Alam, Gillian Dobbie, Yun Sing Koh, Saeed ur Rehman.
Biologically-inspired data mining has a wide variety of applications in areas such as data clustering, classification, sequential pattern mining, and information extraction in healthcare and bioinformatics. Over the past decade, research materials in this area have dramatically increased, providing...
Data Mining and Analysis in the Engineering Field
Particularly in the fields of software engineering, virtual reality, and computer science, data mining techniques play a critical role in the success of a variety of projects and endeavors. Understanding the available tools and emerging trends in this field is an important consideration for any...
Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems
Xenia Naidenova, Dmitry I. Ignatov.
The consideration of symbolic machine learning algorithms as an entire class will make it possible, in the future, to generate algorithms, with the aid of some parameters, depending on the initial users' requirements and the quality of solving targeted problems in domain applications. Diagnostic Test...
Developments in Data Extraction, Management, and Analysis
Nhung Do, J. Wenny Rahayu, Torab Torabi.
With the improvements of artificial intelligence, processor speeds and database sizes, the rapidly expanding field of data mining continues to provide advancing methods for managing databases and gaining knowledge. Developments in Data Extraction, Management, and Analysis is an essential collection of...
Data Mining: Concepts, Methodologies, Tools, and Applications
Information Resources Management Association.
Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of...
Ethical Data Mining Applications for Socio-Economic Development
Hakikur Rahman, Isabel Ramos.
Organizations that utilize data mining techniques can amass valuable information on clients’ habits and preferences, behavior patterns, purchase patterns, sales patterns, and stock forecasts. Ethical Data Mining Applications for Socio-Economic Development provides an overview of data mining techniques...
Data Mining in Dynamic Social Networks and Fuzzy Systems
Many organizations, whether in the public or private sector, have begun to take advantage of the tools and techniques used for data mining. Utilizing data mining tools, these organizations are able to reveal the hidden and unknown information from available data. Data Mining in Dynamic Social Networks...
Pattern Discovery Using Sequence Data Mining: Applications and Studies
Pradeep Kumar, P. Radha Krishna, S. Bapi Raju.
Sequential data from Web server logs, online transaction logs, and performance measurements is collected each day. This sequential data is a valuable source of information, as it allows individuals to search for a particular value or event and also facilitates analysis of the frequency of certain...
XML Data Mining: Models, Methods, and Applications
The widespread use of XML in business and scientific databases has prompted the development of methodologies, techniques, and systems for effectively managing and analyzing XML data. This has increasingly attracted the attention of different research communities, including database, information...
Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends
David Taniar, Lukman Hakim Iwan.
Data mining is still a relatively young field, expanding at the rate of technology while advancing tools and techniques for gaining knowledge, finding patterns, and managing databases. Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends is an updated look at the state of...
Social Network Mining, Analysis, and Research Trends: Techniques and Applications
I-Hsien Ting, Tzung-Pei Hong, Leon Shyue-Liang Wang.
Social network analysis dates back to the early 20th century, with initial studies focusing on small group behavior from a sociological perspective. The emergence of the Internet and subsequent increase in the use of online social networking applications has caused a shift in the approach to this...
Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies
Leon Shyue-Liang Wang, Tzung-Pei Hong.
As the applications of data mining, the non-trivial extraction of implicit information in a data set, have expanded in recent years, so has the need for techniques that are tolerable to imprecision, uncertainty, and approximation. Intelligent Soft Computation and Evolving Data Mining: Integrating...
Data Mining in Public and Private Sectors: Organizational and Government Applications
Antti Syvajarvi, Jari Stenvall.
The need for both organizations and government agencies to generate, collect, and utilize data in public and private sector activities is rapidly increasing, placing importance on the growth of data mining applications and tools. Data Mining in Public and Private Sectors: Organizational and Government...
An Efficient Method for Discretizing Continuous Attributes
Kelley M. Engle, Aryya Gangopadhyay.
In this paper the authors present a novel method for finding optimal split points for discretization of continuous attributes. Such a method can be used in many data mining techniques for large databases. The method consists of two major steps. In the first step search space is pruned using a bisecting...
Graph-Based Modelling of Concurrent Sequential Patterns
Jing Lu, Weiru Chen, Malcolm Keech.
Structural relation patterns have been introduced recently to extend the search for complex patterns often hidden behind large sequences of data. This has motivated a novel approach to sequential patterns post-processing and a corresponding data mining method was proposed for Concurrent Sequential...
User-Centric Similarity and Proximity Measures for Spatial Personalization
Yanwu Yang, Christophe Claramunt, Marie-Aude Aufaure, Wensheng Zhang.
Spatial personalization can be defined as a novel way to fulfill user information needs when accessing spatial information services either on the web or in mobile environments. The research presented in this paper introduces a conceptual approach that models the spatial information offered to a given...
Introduction to the Experimental Design in the Data Mining Tool KEEL
J. Alcalá-Fdez, F. Herrera, S. García, M.J. del Jesus, L. Sánchez, E. Bernadó-Mansilla, A. Peregrín, S. Ventura.
KEEL is a Data Mining software tool to assess the behaviour of evolutionary learning algorithms in particular and soft computing algorithms in general for different kinds of Data Mining problems including as regression, classification, clustering, pattern mining and so on. It allows us to perform a...
Cat Swarm Optimization Supported Data Mining
Pei-Wei Tsai, Jeng-Shyang Pan, Bin-Yih Liao, Shu-Chuan Chu, Mei-Chiao Lai.
This chapter reviews the basic idea and processes in data mining and some algorithms within the field of evolutionary computing. The authors focus on introducing the algorithms of computational intelligence since they are useful tools for solving problems of optimization, data mining, and many kinds of...