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Monetizing Data
Practical guide for deriving insight and commercial gain from data Monetising Data offers a practical guide for anyone working with commercial data but lacking deep knowledge of statistics or data mining. The authors — noted experts in the field — show how to generate extra benefit from data already collected and how to use it to solve business problems. In accessible terms, the book details ways to extract data to enhance business practices and offers information on important topics such as data handling and management, statistical methods, graphics and business issues. The text presents a wide range of illustrative case studies and examples to demonstrate how to adapt the ideas towards...
A Practical Guide to Data Mining for Business and Industry
Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.
Management Intelligent Systems
The 2012 International Symposium on Management Intelligent Systems is believed to be the first international forum to present and discuss original, rigorous and significant contributions on Artificial Intelligence-based (AI) solutions—with a strong, practical logic and, preferably, with empirical applications—developed to aid the management of organizations in multiple areas, activities, processes and problem-solving; i.e., what we propose to be named as Management Intelligent Systems (MiS). The three-day event aimed to bring together researchers interested in this promising interdisciplinary field who came from areas as varied as management, marketing, and business in general, computer ...
Statistical Practice in Business and Industry
This book covers all the latest advances, as well as more established methods, in the application of statistical and optimisation methods within modern industry. These include applications from a range of industries that include micro-electronics, chemical, automotive, engineering, food, component assembly, household goods and plastics. Methods range from basic graphical approaches to generalised modelling, from designed experiments to process control. Solutions cover produce and process design, through manufacture to packaging and delivery, from single responses to multivariate problems.
Advances in Data Mining: Applications and Theoretical Aspects
These are the proceedings of the tenth event of the Industrial Conference on Data Mining ICDM held in Berlin (www.data-mining-forum.de). For this edition the Program Committee received 175 submissions. After the pe- review process, we accepted 49 high-quality papers for oral presentation that are included in this book. The topics range from theoretical aspects of data mining to app- cations of data mining such as on multimedia data, in marketing, finance and telec- munication, in medicine and agriculture, and in process control, industry and society. Extended versions of selected papers will appear in the international journal Trans- tions on Machine Learning and Data Mining (www.ibai-publis...
Advances in Data Mining - Theoretical Aspects and Applications
The papers in this volume represent the proceedings of the 7th Industrial Conference on Data Mining. They are organized into topical sections on aspects of classification and prediction, clustering, web mining, data mining in medicine, applications of data mining, time series and frequent pattern mining, and association rule mining. Readers gain new insights into theories underlying data mining and discover state-of-the-technology applications.
Monetising Data
Practical guide for deriving insight and commercial gain from data Monetising Data offers a practical guide for anyone working with commercial data but lacking deep knowledge of statistics or data mining. The authors - noted experts in the field - show how to generate extra benefit from data already collected and how to use it to solve business problems. In accessible terms, the book details ways to extract data to enhance business practices and offers information on important topics such as data handling and management, statistical methods, graphics and business issues. The text presents a wide range of illustrative case studies and examples to demonstrate how to adapt the ideas towards mon...
Leitfaden Digitaler Dialog
Neben Marketing- und Vertriebsaspekten zeigt dieses Buch Perspektiven auf, die sich aus dem Social Web ergeben. Kundenanfragen über Facebook, Twitter & Co. können von den Unternehmen als Chance zum Dialog genutzt werden. Wer es versteht, die Gespräche mit den Konsumenten authentisch und auf Augenhöhe zu führen, wird zukünftig zu den Gewinnern zählen. Wie das geht, verrät dieses Buch. Die Herausgeberin Gabriele Braun, Geschäftsführerin der marketing-BÖRSE, brachte in diesem Werk 55 Autoren der Branche zusammen, die über ihre Erfahrungen berichten und Praxisbeispiele aufzeigen.
Erfolgreiches Social Media Marketing
Heutzutage lautet die Fragestellung nicht mehr ob, sondern wie Social Media Marketing zu betreiben ist. Ceyp/Scupin stellen bei der Beantwortung dieser Frage eine strategische, entscheidungsorientierte Sichtweise in den Vordergrund. Dabei garantiert die Konzentration auf übergeordnete strategische und operative Fragestellungen die längerfristige Relevanz der Aussagen.
Advances on Data Mining: Applications and Theoretical Aspects
This book constitutes the refereed proceedings of the 11th Industrial Conference on Data Mining, ICDM 2011, held in New York, USA in September 2011. The 22 revised full papers presented were carefully reviewed and selected from 100 submissions. The papers are organized in topical sections on data mining in medicine and agriculture, data mining in marketing, data mining for Industrial processes and in telecommunication, Multimedia Data Mining, theoretical aspects of data mining, Data Warehousing, WebMining and Information Mining.
