Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research anddevelopment in the dialogue between academia and business. Presents knowledge, techniques and case studies to bridge the gap between business expectations and research outputs Explores new research issues in data mining, including trust, organizational and social factors Addresses recent applications in areas such as blog mining and social security mining Introduces techniques and methodologies evidenced and validated in real-life enterprise data mining
- ISBN: 978-0-387-79419-8
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 260
- Fecha Publicación: 01/12/2008
- Nº Volúmenes: 1
- Idioma: Inglés