Domain Driven Data Mining
Cao, Longbing; Yu, Philip S.; Zhang, Chengqi; Zhao, Yanchang
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Description for Domain Driven Data Mining
Hardback. This book offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actionable knowledge discovery. It bridges the gap between business expectations and research output. Num Pages: 264 pages, 50 black & white tables, biography. BIC Classification: KJQ; UNF; UNH. Category: (P) Professional & Vocational. Dimension: 245 x 166 x 21. Weight in Grams: 556.
Data mining has emerged as one of the most active areas in information and c- munication technologies(ICT). With the boomingof the global economy,and ub- uitouscomputingandnetworkingacrosseverysectorand business,data andits deep analysis becomes a particularly important issue for enhancing the soft power of an organization, its production systems, decision-making and performance. The last ten years have seen ever-increasingapplications of data mining in business, gove- ment, social networks and the like. However, a crucial problem that prevents data mining from playing a strategic decision-support role in ICT is its usually limited decision-support power in the real world. Typical concerns include its actionability, workability, transferability, ... Read more
Data mining has emerged as one of the most active areas in information and c- munication technologies(ICT). With the boomingof the global economy,and ub- uitouscomputingandnetworkingacrosseverysectorand business,data andits deep analysis becomes a particularly important issue for enhancing the soft power of an organization, its production systems, decision-making and performance. The last ten years have seen ever-increasingapplications of data mining in business, gove- ment, social networks and the like. However, a crucial problem that prevents data mining from playing a strategic decision-support role in ICT is its usually limited decision-support power in the real world. Typical concerns include its actionability, workability, transferability, ... Read more
Product Details
Format
Hardback
Publication date
2010
Publisher
Springer-Verlag New York Inc. United States
Number of pages
264
Condition
New
Number of Pages
248
Place of Publication
New York, NY, United States
ISBN
9781441957368
SKU
V9781441957368
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Domain Driven Data Mining
From the reviews: “This book offers a comprehensive discussion of domain-driven data mining (D3M), a set of techniques and methodologies that aim to discover actionable knowledge that can be presented to business decision makers in order to enable them to make informed decisions. … The resulting approach is an exploration of possibilities for enhancing the decision-support power of data ... Read more