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- A hybrid multi-group approach for privacy-preserving data mining. Teng, Zhouxuan; Du, Wenliang // Knowledge & Information Systems;May2009, Vol. 19 Issue 2, p133
In this paper, we propose a hybrid multi-group approach for privacy preserving data mining. We make two contributions in this paper. First, we propose a hybrid approach. Previous work has used either the randomization approach or the secure multi-party computation (SMC) approach. However, these...
- An Agenda- and Justification-Based Framework for Discovery Systems. Livingston, Gary R.; Rosenberg, John M.; Buchanan, Bruce G. // Knowledge & Information Systems;Apr2003, Vol. 5 Issue 2, p133
We propose and evaluate an agenda- and justification-based architecture for discovery systems that selects the next tasks to perform, as well as heuristics for use in discovery systems. This framework has many desirable properties: (1) it selects its own tasks to perform based upon how plausible...
- An Ontology Construction Method for Knowledge Organization in Interdisciplines: - Taking "discipline of computer science and technology" as an example. Zheng Yi; Ying shi // Applied Mechanics & Materials;2014, Issue 513-517, p3781
The existing construction methods for knowledge organization rarely address the development trend of interdisciplinary cross and fusion. In this paper, we propose a method of ontology construction to address fusion of subjects' knowledge for the knowledge management of interdisciplines. We apply...
- DISCOVERING POTENTIAL USER BROWSING BEHAVIORS USING CUSTOM-BUILT APRIORI ALGORITHM. Rawat, Sandeep Singh; Rajamani, Lakshmi // International Journal of Computer Science & Information Technolo;Aug2010, Vol. 2 Issue 4, p28
Most of the organizations put information on the web because they want it to be seen by the world. Their goal is to have visitors come to the site, feel comfortable and stay a while and try to know completely about the running organization. As educational system increasingly requires data...
- Measuring the Interestingness of Classification Rules. Sharma, Sanjeev; Khare, Swati; Sharma, Sudhir // Asian Journal of Information Management;2007, Vol. 1 Issue 2, p43
Data mining tools and techniques provide various applications with novel and significant knowledge. This knowledge can be leveraged to gain competitive advantage. However, the automated nature of data mining algorithms may result in a glut of patterns-the sheer numbers of which contribute to...
- Data mining: On the trail to marketing gold. Thelen, Shawn; Mottner, Sandra; Berman, Barry // Business Horizons;Nov/Dec2004, Vol. 47 Issue 6, p25
What is data mining, and how does it differ from traditional statistical modeling? Along with finding the answers here, managers can take a look at important recent developments in data mining, examine some of its marketing-related applications, and learn how to establish and maintain a data...
- Interactive visual exploration of association rules with rule-focusing methodology. Blanchard, Julien; Guillet, Fabrice; Briand, Henri // Knowledge & Information Systems;Sep2007, Vol. 13 Issue 1, p43
On account of the enormous amounts of rules that can be produced by data mining algorithms, knowledge post-processing is a difficult stage in an association rule discovery process. In order to find relevant knowledge for decision making, the user (a decision maker specialized in the data...
- A fast and effective method to find correlations among attributes in databases. De Sousa, Elaine P. M.; Traina Jr., Caetano; Traina, Agma J. M.; Leejay Wu; Faloutsos, Christos // Data Mining & Knowledge Discovery;Jun2007, Vol. 14 Issue 3, p367
The problem of identifying meaningful patterns in a database lies at the very heart of data mining. A core objective of data mining processes is the recognition of inter-attribute correlations. Not only are correlations necessary for predictions and classifications -- since rules would fail in...
- Frequent pattern mining: current status and future directions. Jiawei Han; Hong Cheng; Dong Xin; Xifeng Yan // Data Mining & Knowledge Discovery;Aug2007, Vol. 15 Issue 1, p55
Frequent pattern mining has been a focused theme in datamining research for over a decade. Abundant literature has been dedicated to this research and tremendous progress has been made, ranging from efficient and scalable algorithms for frequent itemset mining in transaction databases to...