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Full-Text Articles in Technology and Innovation
Tree-Based Algorithm For Stable And Efficient Data Clustering, Hasan Aljabbouli, Abdullah Albizri, Antoine Harfouche
Tree-Based Algorithm For Stable And Efficient Data Clustering, Hasan Aljabbouli, Abdullah Albizri, Antoine Harfouche
Department of Information Management and Business Analytics Faculty Scholarship and Creative Works
The K-means algorithm is a well-known and widely used clustering algorithm due to its simplicity and convergence properties. However, one of the drawbacks of the algorithm is its instability. This paper presents improvements to the K-means algorithm using a K-dimensional tree (Kd-tree) data structure. The proposed Kd-tree is utilized as a data structure to enhance the choice of initial centers of the clusters and to reduce the number of the nearest neighbor searches required by the algorithm. The developed framework also includes an efficient center insertion technique leading to an incremental operation that overcomes the instability problem of the K-means …
Subjectivity Of Diamond Prices In Online Retail: Insights From A Data Mining Study, Stanislav Mamonov, Tamilla Triantoro
Subjectivity Of Diamond Prices In Online Retail: Insights From A Data Mining Study, Stanislav Mamonov, Tamilla Triantoro
Department of Information Management and Business Analytics Faculty Scholarship and Creative Works
Diamonds belong to a unique product category whose perceived value is largely dependent on socially constructed beliefs. To explore the degree to which the physical properties of a diamond can be used to predict the diamond price, we perform data mining on a large dataset of loose diamonds scraped from an online diamond retailer. We find that diamond weight, color and clarity are the key characteristics that influence diamond prices. The data mining results also suggest a high degree of subjectivity in diamond pricing that may reflect price obfuscation strategies employed by diamond retailers.
Chapter Xii: A Comparison And Scenario Analysis Of Leading Data Mining Software, John Wang, Xiaohua Hu, Kimberly Hollister, Dan Zhu
Chapter Xii: A Comparison And Scenario Analysis Of Leading Data Mining Software, John Wang, Xiaohua Hu, Kimberly Hollister, Dan Zhu
Department of Information Management and Business Analytics Faculty Scholarship and Creative Works
Finding the right software is often hindered by different criteria as well as by technology changes. We performed an analytic hierarchy process (AHP) analysis using Expert Choice to determine which data mining package was best suitable for us. Deliberating a dozen alternatives and objectives led us to a series of pair-wise comparisons. When further synthesizing the results, Expert Choice helped us provide a clear rationale for the decision. The issue is that data mining technology is changing very rapidly. Our article focused only on the major suppliers typically available in the market place. The method and the process that we …