Data mining the data processing technologies for inventory management

Chien Wen Shen, Heng Chih Lee, Ching Chih Chou, Chiao Chun Cheng

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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 study adopted the method of nonhierarchical clustering analysis to identify key groups of technologies through the symmetrical matrix of relative correlation strength. Enterprise can refer the findings of clustering to recognize the trend and characteristics of data processing technologies for their strategic technology management.

Original languageEnglish
Pages (from-to)784-791
Number of pages8
JournalJournal of Computers
Volume6
Issue number4
DOIs
StatePublished - Apr 2011

Keywords

  • Data mining
  • Data processing
  • Inventory management
  • Patent analysis

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