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This research applied various data mining approaches to investigate the innovations of data processing technologies for inventory management based on the database of the United States Patent and Trademark Office. The first objective of data mining in this study is to find the core technologies by evaluating patent citation matrix and patent strength. This information can help companies to choose suitable tools through the understanding of the most essential innovations. A total of 63 core technologies were identified from 949 patents under the US patent class of 705/28. Besides, a network of patent development paths was also derived to illustrate the correlations of core advancements. Finally, this paper adopted the method of nonhierarchical clustering analysis to identify key groups of technologies through the symmetrical matrix of relative correlation strength.
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