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Titlebook: Bisociative Knowledge Discovery; An Introduction to C Michael R. Berthold Book‘‘‘‘‘‘‘‘ 2012 The Editor(s) (if applicable) and the Author(s)

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發(fā)表于 2025-3-21 20:09:51 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Bisociative Knowledge Discovery
期刊簡稱An Introduction to C
影響因子2023Michael R. Berthold
視頻videohttp://file.papertrans.cn/189/188885/188885.mp4
發(fā)行地址Presents the highlights of the BISON project.Serves as a great basis for future work in data mining.Includes supplementary material: .Includes supplementary material:
學科分類Lecture Notes in Computer Science
圖書封面Titlebook: Bisociative Knowledge Discovery; An Introduction to C Michael R. Berthold Book‘‘‘‘‘‘‘‘ 2012 The Editor(s) (if applicable) and the Author(s)
影響因子Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied to originates from one domain. The focus of this book, and the BISON project from which the contributions are originating, is a network based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information networks. Instead of finding well defined global or local patterns they wanted to find domain bridging associations which are, by definition, not well defined since they will be especially interesting if they are sparse and have not been encountered before. The 32 contributions presented in this state-of-the-art volume together with a detailed introduction to the book are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.
Pindex Book‘‘‘‘‘‘‘‘ 2012
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From Information Networks to Bisociative Information Networksr bisociative knowledge discoveries. Finally based on this data structure three different patterns are described that fulfill the requirements of a bisociation by connecting concepts from seemingly unrelated domains.
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發(fā)表于 2025-3-22 01:44:57 | 只看該作者
Discovery of Novel Term Associations in a Document Collectiony dependent pairs that are not likely to be considered novel or interesting by the user..We present experimental results on two collections of documents: one extracted from Wikipedia, and one containing text mining articles with manually assigned term associations. The results indicate that the tpf–
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