Download Intelligent Knowledge: A Study beyond Data Mining by Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li PDF

By Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li

This booklet is principally approximately an leading edge and primary strategy referred to as “intelligent wisdom” to bridge the distance among information mining and information administration, vital fields well-known through the knowledge know-how (IT) group and enterprise analytics (BA) neighborhood respectively. The booklet comprises definitions of the “first-order” analytic approach, “second-order” analytic procedure and clever wisdom, that have now not officially been addressed via both facts mining or wisdom administration. in accordance with those options, that are specifically vital in reference to the present sizeable info flow, the e-book describes a framework of domain-driven clever wisdom discovery. to demonstrate its technical benefits for large-scale info, the booklet employs tested methods, reminiscent of a number of standards Programming, aid Vector desktop and selection Tree to spot clever wisdom included with human wisdom. The publication additional exhibits its applicability via real-life info analyses within the contexts of web enterprise and standard chinese language medicines.

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Extra info for Intelligent Knowledge: A Study beyond Data Mining

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It may degrade in the short term with environmental changes. In addition, there are conflicts sometimes between the knowledge generated from different periods. As a result, as the environment changes the dynamic adaptability can be poor. While rough knowledge is a specific knowledge derived from the analytic data mining process, the human knowledge has extensively been studied in the field of knowledge management. The item knowledge has been defined in many different 20 2 Foundations of Intelligent Knowledge Management ways.

To 3 Affiliation network is a one mode network, which has been first applied to study the southern women and the social events in which they attended. The affiliation network describes how many same events each two of women have attended. , and Faust, K. Social Network Analysis, 1995. 4 The computational process to get the Geary’s C and the adjacency was shown in Appendix C. 01 put it another way, the degree to which individuals agree on classifier’s performance is positively influenced by the similarity between individual’s educational levels.

However, they did not connect the necessary concepts from the filed of knowledge management in order to solve such a problem for practical usage. Conversely, researchers in knowledge management often ignore rough knowledge created outside humans as a valuable knowledge base. Therefore, to bridge the gap between data mining and knowledge management, the proposed study on intelligent knowledge in the paper is new. As discussed above, the transformation from information to rough knowledge T1 is essentially trying to find some existing phenomenological associations among specific data.

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