This book delves into the challenges of data availability in data mining, presenting data fusion as a solution. It begins by explaining data fusion as a way to combine information from different sources into a single data set for further data mining. The author highlights that while significant work has been done on data fusion in the past, most research has been performed outside the data mining community. The book introduces basic terminology, focusing on the statistical matching approach. It distinguishes between internal and external evaluation, providing a comprehensive understanding of data fusion evaluation techniques. A real-world case study is presented, demonstrating the practical application of data fusion in the context of database marketing. The author emphasizes the significance of evaluating the quality of the fusion to ensure it is valid and useful for further analysis. The work concludes by discussing the importance of data fusion as both a key enabling technology and an interesting research topic for data mining. It highlights future research opportunities and the potential for incorporating data fusion into predictive modeling methods. This book offers valuable insights for researchers and practitioners in data mining, providing a deeper understanding of data fusion and its applications in enhancing the value of data mining.
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Excerpt from Data Fusion Through Statistical Matching
One may claim that the exponential growth in the amount of data provides great Opportunities for data mining. Reality can be different though. In many real world applications, the number of sources over which this information is fragmented grows at an even faster rate, resulting in barriers to widespread application of data mining and missed business opportunities. Let us illustrate this paradox with a motivating example from database marketing.
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Paperback. Condición: New. Print on Demand. This book delves into the challenges of data availability in data mining, presenting data fusion as a solution. It begins by explaining data fusion as a way to combine information from different sources into a single data set for further data mining. The author highlights that while significant work has been done on data fusion in the past, most research has been performed outside the data mining community. The book introduces basic terminology, focusing on the statistical matching approach. It distinguishes between internal and external evaluation, providing a comprehensive understanding of data fusion evaluation techniques. A real-world case study is presented, demonstrating the practical application of data fusion in the context of database marketing. The author emphasizes the significance of evaluating the quality of the fusion to ensure it is valid and useful for further analysis. The work concludes by discussing the importance of data fusion as both a key enabling technology and an interesting research topic for data mining. It highlights future research opportunities and the potential for incorporating data fusion into predictive modeling methods. This book offers valuable insights for researchers and practitioners in data mining, providing a deeper understanding of data fusion and its applications in enhancing the value of data mining. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Nº de ref. del artículo: 9781334538728_0
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LW-9781334538728
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LW-9781334538728
Cantidad disponible: 15 disponibles