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Titlebook: Data Engineering; Mining, Information Yupo Chan,John Talburt,Terry M. Talley Book 2010 Springer-Verlag US 2010 Analytics.association.class

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51#
發(fā)表于 2025-3-30 10:10:22 | 只看該作者
52#
發(fā)表于 2025-3-30 15:20:36 | 只看該作者
53#
發(fā)表于 2025-3-30 18:25:15 | 只看該作者
Knowledge Discovery in Textual Databases: A Concept-Association Mining Approach,e of the National Library of Medicine (NLM), contains about 18 million records from more than 7,300 different publications dating from 1965; it is growing by about 400,000 citations each year. The explosive growth of information in textual documents creates great need for techniques for knowledge discovery from text collections.
54#
發(fā)表于 2025-3-30 21:01:30 | 只看該作者
Information Quality Framework for Verifiable Intelligence Products,in their efforts to effectively use the data to improve business processes and to make better decisions. This difficulty is often caused by information quality issues within the organization and other related organizations.
55#
發(fā)表于 2025-3-31 04:29:41 | 只看該作者
Looking Ahead,lytics, and visualization to improve the quality of information-based decision making. We, the editors and the contributing authors, hope that this book will have some impact on the practice of managers and technical personnel immediately upon its publication and in the years to come.
56#
發(fā)表于 2025-3-31 06:01:04 | 只看該作者
Yupo Chan,John Talburt,Terry M. TalleyFirst volume to organize data mining, management, and warehousing into the systematic structure of Data Engineering.Focuses on recent applied research results applicable to a broad industry-research-a
57#
發(fā)表于 2025-3-31 09:38:44 | 只看該作者
International Series in Operations Research & Management Sciencehttp://image.papertrans.cn/d/image/262784.jpg
58#
發(fā)表于 2025-3-31 13:21:18 | 只看該作者
https://doi.org/10.1007/978-1-4419-0176-7Analytics; association; classification; data quality; database; entity resolution; grid computing; performa
59#
發(fā)表于 2025-3-31 18:37:59 | 只看該作者
978-1-4614-2476-5Springer-Verlag US 2010
60#
發(fā)表于 2025-3-31 23:19:47 | 只看該作者
Semantic Data Matching: Principles and Performance,at can match data based upon higher order structure, and is able to handle difficult problems, such as words that have different meanings but the same spelling, are synonymous, or have multiple meanings. Essentially, the technique matches records based upon context, or mathematically quantifying when terms occur in the same record.
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