Knowledge Discovery For Business Information Systems
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| Author | : Witold Abramowicz |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 442 |
| Release | : 2006-04-18 |
| Genre | : Computers |
| ISBN | : 030646991X |
Current database technology and computer hardware allow us to gather, store, access, and manipulate massive volumes of raw data in an efficient and inexpensive manner. In addition, the amount of data collected and warehoused in all industries is growing every year at a phenomenal rate. Nevertheless, our ability to discover critical, non-obvious nuggets of useful information in data that could influence or help in the decision making process, is still limited. Knowledge discovery (KDD) and Data Mining (DM) is a new, multidisciplinary field that focuses on the overall process of information discovery from large volumes of data. The field combines database concepts and theory, machine learning, pattern recognition, statistics, artificial intelligence, uncertainty management, and high-performance computing. To remain competitive, businesses must apply data mining techniques such as classification, prediction, and clustering using tools such as neural networks, fuzzy logic, and decision trees to facilitate making strategic decisions on a daily basis. Knowledge Discovery for Business Information Systems contains a collection of 16 high quality articles written by experts in the KDD and DM field from the following countries: Austria, Australia, Bulgaria, Canada, China (Hong Kong), Estonia, Denmark, Germany, Italy, Poland, Singapore and USA.
| Author | : Krzysztof J. Cios |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 508 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461555892 |
Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.
| Author | : O. Maimon |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 192 |
| Release | : 2000-12-31 |
| Genre | : Computers |
| ISBN | : 9780792366478 |
This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).
| Author | : Kweku-Muata Osei-Bryson |
| Publisher | : CRC Press |
| Total Pages | : 404 |
| Release | : 2015-03-16 |
| Genre | : Business & Economics |
| ISBN | : 1482212382 |
Although the terms "data mining" and "knowledge discovery and data mining" (KDDM) are sometimes used interchangeably, data mining is actually just one step in the KDDM process. Data mining is the process of extracting useful information from data, while KDDM is the coordinated process of understanding the business and mining the data in order to id
| Author | : Malcolm Atkinson |
| Publisher | : John Wiley & Sons |
| Total Pages | : 423 |
| Release | : 2013-03-19 |
| Genre | : Computers |
| ISBN | : 1118540301 |
Complete guidance for mastering the tools and techniques of the digital revolution With the digital revolution opening up tremendous opportunities in many fields, there is a growing need for skilled professionals who can develop data-intensive systems and extract information and knowledge from them. This book frames for the first time a new systematic approach for tackling the challenges of data-intensive computing, providing decision makers and technical experts alike with practical tools for dealing with our exploding data collections. Emphasizing data-intensive thinking and interdisciplinary collaboration, The Data Bonanza: Improving Knowledge Discovery in Science, Engineering, and Business examines the essential components of knowledge discovery, surveys many of the current research efforts worldwide, and points to new areas for innovation. Complete with a wealth of examples and DISPEL-based methods demonstrating how to gain more from data in real-world systems, the book: Outlines the concepts and rationale for implementing data-intensive computing in organizations Covers from the ground up problem-solving strategies for data analysis in a data-rich world Introduces techniques for data-intensive engineering using the Data-Intensive Systems Process Engineering Language DISPEL Features in-depth case studies in customer relations, environmental hazards, seismology, and more Showcases successful applications in areas ranging from astronomy and the humanities to transport engineering Includes sample program snippets throughout the text as well as additional materials on a companion website The Data Bonanza is a must-have guide for information strategists, data analysts, and engineers in business, research, and government, and for anyone wishing to be on the cutting edge of data mining, machine learning, databases, distributed systems, or large-scale computing.
| Author | : Usama M. Fayyad |
| Publisher | : |
| Total Pages | : 638 |
| Release | : 1996 |
| Genre | : Computers |
| ISBN | : |
Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.
| Author | : Rajput, Dharmendra Singh |
| Publisher | : IGI Global |
| Total Pages | : 355 |
| Release | : 2018-08-31 |
| Genre | : Business & Economics |
| ISBN | : 1522550003 |
In the era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through online collaborative media. However, conducting sentiment analysis on these platforms can be challenging, especially for business professionals who are using them to collect vital data. Sentiment Analysis and Knowledge Discovery in Contemporary Business is an essential reference source that discusses applications of sentiment analysis as well as data mining, machine learning algorithms, and big data streams in business environments. Featuring research on topics such as knowledge retrieval and knowledge updating, this book is ideally designed for business managers, academicians, business professionals, researchers, graduate-level students, and technology developers seeking current research on data collection and management to drive profit.
| Author | : Witold Abramowicz |
| Publisher | : Springer |
| Total Pages | : 453 |
| Release | : 2016-06-27 |
| Genre | : Computers |
| ISBN | : 3319394266 |
This book contains the refereed proceedings of the 19th International Conference on Business Information Systems, BIS 2016, held in Leipzig, Germany, in July 2016. The BIS conference series follows trends in academia and business research; thus the theme of the BIS 2016 conference was Smart Business Ecosystems". This recognizes that no business is an island and competition is increasingly taking place between business networks and no longer between individual companies. A variety of aspects is relevant for designing and understanding smart business ecosystems. They reach from new business models, value chains and processes to all aspects of analytical, social and enterprise applications and platforms as well as cyber-physical infrastructures. The 33 full and 1 short papers were carefully reviewed and selected from 87 submissions. They are grouped into sections on ecosystems; big and smart data; smart infrastructures; process management; business and enterprise modeling; service science; social media; and applications.
| Author | : |
| Publisher | : |
| Total Pages | : 2287 |
| Release | : 2010 |
| Genre | : Business |
| ISBN | : |
"This four-volume reference offers a complete view of current business information systems within organizations and the advancements that technology has provided to the business community, including how technological advancements have revolutionized financial transactions, management infrastructure, and knowledge workers"--Provided by publisher.
| Author | : Khosrow-Pour D.B.A., Mehdi |
| Publisher | : IGI Global |
| Total Pages | : 2734 |
| Release | : 2020-09-29 |
| Genre | : Business & Economics |
| ISBN | : 1799834743 |
For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication.
