By Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li
This publication is especially approximately an leading edge and basic technique referred to as “intelligent wisdom” to bridge the distance among info mining and information administration, very important fields famous through the data expertise (IT) group and company analytics (BA) neighborhood respectively. The publication contains definitions of the “first-order” analytic technique, “second-order” analytic method and clever wisdom, that have now not officially been addressed via both info mining or wisdom administration. in response to those options, that are specifically very important in reference to the present large information circulate, the publication describes a framework of domain-driven clever wisdom discovery. to demonstrate its technical merits for large-scale information, the booklet employs tested techniques, corresponding to a number of standards Programming, aid Vector desktop and determination Tree to spot clever wisdom integrated with human wisdom. The booklet additional indicates its applicability by way of real-life information analyses within the contexts of web company and standard chinese language medicines.
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Extra resources for Intelligent Knowledge: A Study beyond Data Mining
80 variables were designed to reflect the behaviors of the customers. 1 Habitual Domains Characteristics Measures for habitual domain characteristics—level of educational, prior experience with data mining, and areas of specialty—were enabled by asking participants to check the items that best describe their current status. Specifically, to assess subjects’ educational background, we asked each participant to answer one multiple choice question that asks their highest degree (IV1). Second, area of specialty was measured by asking subjects’ current major and research area (IV2).
Fig. 4 Transformation Process of Data–Rough knowledge-Intelligent Knowledge- Actionable Knowledge 27 NUL 7 7 . 6 $FWLRQDEOH. D 7 ,QWHOOLJHQW. $FWLRQDEOH. or wisdom can be used as data source for decision support. The new process of rough knowledge-intelligent knowledge-actionable knowledge begins. However, the new round of knowledge discovery is a higher level of knowledge discovery on the basis of existing knowledge. Therefore, it is a cycle, spiraling process for the organizational knowledge creation, and from the research review, the current data mining and KDD would often be halted when it is up to stage T3 or T4, leading to the fracture of spiral, which is not conducive to the accumulation of knowledge.
To humans, their contexts depict personal characteristics of one engaging in intellectual activities (Pan 2005). 9 Knowledge is called Intelligent Knowledge, denoted as K1 if it is generated from rough knowledge and/or specific, empirical, common sense and situational knowledge, by using a “second-order” analytic process. If data mining is said as the “first-order” analytic process, then the “secondorder” analytic process here means quantitative or qualitative studies are applied to the collection of knowledge for the pre-determined objectives.