Author : Usama M. Fayyad
Publisher : Morgan Kaufmann
Page : 446 pages
File Size : 32,18 MB
Release : 2002
Category : Computers
ISBN : 9781558606890
This text surveys research from the fields of data mining and information visualisation and presents a case for techniques by which information visualisation can be used to uncover real knowledge hidden away in large databases.
Author : Simeon Simoff
Publisher : Springer
Page : 417 pages
File Size : 36,57 MB
Release : 2008-07-23
Category : Computers
ISBN : 3540710809
Visual Data Mining—Opening the Black Box Knowledge discovery holds the promise of insight into large, otherwise opaque datasets. Thenatureofwhatmakesaruleinterestingtoauserhasbeendiscussed 1 widely but most agree that it is a subjective quality based on the practical u- fulness of the information. Being subjective, the user needs to provide feedback to the system and, as is the case for all systems, the sooner the feedback is given the quicker it can in?uence the behavior of the system. There have been some impressive research activities over the past few years but the question to be asked is why is visual data mining only now being - vestigated commercially? Certainly, there have been arguments for visual data 2 mining for a number of years – Ankerst and others argued in 2002 that current (autonomous and opaque) analysis techniques are ine?cient, as they fail to - rectly embed the user in dataset exploration and that a better solution involves the user and algorithm being more tightly coupled. Grinstein stated that the “current state of the art data mining tools are automated, but the perfect data mining tool is interactive and highly participatory,” while Han has suggested that the “data selection and viewing of mining results should be fully inter- tive, the mining process should be more interactive than the current state of the 2 art and embedded applications should be fairly automated . ” A good survey on 3 techniques until 2003 was published by de Oliveira and Levkowitz .
Author : Andreas Kerren
Publisher : Springer Science & Business Media
Page : 184 pages
File Size : 48,91 MB
Release : 2008-07-18
Category : Computers
ISBN : 354070955X
This book is the outcome of the Dagstuhl Seminar on "Information Visualization -- Human-Centered Issues in Visual Representation, Interaction, and Evaluation" held at Dagstuhl Castle, Germany, from May 28 to June 1, 2007. Information Visualization (InfoVis) is a relatively new research area, which focuses on the use of visualization techniques to help people understand and analyze data. This book documents and extends the findings and discussions of the various sessions in detail. The seven contributions cover the most important topics: There are general reflections on the value of information visualization; evaluating information visualizations; theoretical foundations of information visualization; teaching information visualization. And specific aspects on creation and collaboration: engaging new audiences for information visualization; process and pitfalls in writing information visualization research papers; and visual analytics: definition, process, and challenges.
Author : Benjamin B. Bederson
Publisher : Morgan Kaufmann
Page : 432 pages
File Size : 34,44 MB
Release : 2003
Category : Computers
ISBN : 1558609156
Information visualization is a rapidly growing field that is emerging from research in human-computer interaction, computer science, graphics, visual design, psychology, and business methods. Information visualization is increasingly applied as a critical component in scientific research, digital libraries, data mining, financial data analysis, market studies, manufacturing production control, and drug discovery.
Author :
Publisher : Elsevier
Page : 660 pages
File Size : 25,17 MB
Release : 2005-05-02
Category : Mathematics
ISBN : 0080459404
Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files. The second section focuses on a variety of statistical methodologies that have proven to be effective in data mining applications. These include clustering, classification, multivariate density estimation, tree-based methods, pattern recognition, outlier detection, genetic algorithms, and dimensionality reduction. The third section focuses on data visualization and covers issues of visualization of high-dimensional data, novel graphical techniques with a focus on human factors, interactive graphics, and data visualization using virtual reality. This book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with a new data paradigm. - Distinguished contributors who are international experts in aspects of data mining - Includes data mining approaches to non-numerical data mining including text data, Internet traffic data, and geographic data - Highly topical discussions reflecting current thinking on contemporary technical issues, e.g. streaming data - Discusses taxonomy of dataset sizes, computational complexity, and scalability usually ignored in most discussions - Thorough discussion of data visualization issues blending statistical, human factors, and computational insights
Author : Markus Hofmann
Publisher : CRC Press
Page : 337 pages
File Size : 40,67 MB
Release : 2016-01-05
Category : Business & Economics
ISBN : 148223758X
Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, RapidMiner, Weka, R, and Python. The contributors-all highly experienced with text mining and open-source software-explain how text data are gathered and processed from a w
Author : Andreas Holzinger
Publisher : Springer
Page : 373 pages
File Size : 22,13 MB
Release : 2014-06-17
Category : Computers
ISBN : 3662439689
One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of = 3; most of the data is high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of methodologies and approaches of two fields offer ideal conditions towards unraveling these problems: Human–Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human capabilities with machine learning./ppThis state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security.
Author : Jude Hemanth
Publisher : Springer
Page : 321 pages
File Size : 48,26 MB
Release : 2019-08-09
Category : Technology & Engineering
ISBN : 3030257975
This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples. Data visualization and engineering has been instrumental in the development of many data-driven products and processes. As such the book promotes basic research on data visualization and knowledge engineering toward data engineering and knowledge. Visual data exploration focuses on perception of information and manipulation of data to enable even non-expert users to extract knowledge. A number of visualization techniques are used in a variety of systems that provide users with innovative ways to interact with data and reveal patterns. A variety of scalable data visualization techniques are required to deal with constantly increasing volume of data in different formats. Knowledge engineering deals with the simulation of the exchange of ideas and the development of smart information systems in which reasoning and knowledge play an important role. Presenting research in areas like data visualization and knowledge engineering, this book is a valuable resource for students, scholars and researchers in the field. Each chapter is self-contained and offers an in-depth analysis of real-world applications. It discusses topics including (but not limited to) spatial data visualization; biomedical visualization and applications; image/video summarization and visualization; perception and cognition in visualization; visualization taxonomies and models; abstract data visualization; information and graph visualization; knowledge engineering; human–machine cooperation; metamodeling; natural language processing; architectures of database, expert and knowledge-based systems; knowledge acquisition methods; applications, case studies and management issues: data administration issues and knowledge; tools for specifying and developing data and knowledge bases using tools based on communication aspects involved in implementing, designing and using KBSs in cyberspace; Semantic Web.
Author : Riccardo Mazza
Publisher : Springer Science & Business Media
Page : 149 pages
File Size : 43,29 MB
Release : 2009-02-28
Category : Computers
ISBN : 184800219X
Information Visualization is a relatively young field that is acquiring more and more concensus in both academic and industrial environments. 'Information Visualization' explores the use of computer-supported interactive graphical representations to explain data and amplify cognition. It provides a means to comunicate ideas or facts about the data, to validate hypotheses, and facilitates the discovery of new facts via exploration. This book introduces the concepts and methods of Information Visualization in an easy-to-understand way, illustrating how to pictorially represent structured and unstructured data, making it easier to comprehend and interpret. Riccardo Mazza focuses on the human aspects of the process of visualization rather than the algorithmic or graphic design aspects.
Author : Wang, John
Publisher : IGI Global
Page : 4092 pages
File Size : 18,9 MB
Release : 2008-05-31
Category : Technology & Engineering
ISBN : 159904952X
In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.
