Text Mining Based Patent Analysis and Forecasting

• Main Author: 邵子安
• Other Authors: 張適宇
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/71796476357523935057

碩士 === 國立清華大學 === 通訊工程研究所 === 100 === MIMO (multiple-input and multiple-output) technology has attracted attention in wireless communications because it provides significant increases in link range and data throughput without increasing transmission power or additional bandwidth. The goal can be achieved by spreading the same total transmission power over the antennas to reach an array gain that improves the spectral efficiency or to reach a diversity gain that improves the link reliability. MIMO is an important part of modern wireless communication standards (IEEE 802.11n (Wi-Fi), 4G, 3GPP Long Term Evolution, WiMAX (Worldwide Interoperability for Microwave Access) and HSPA+) because of these properties. Although MIMO is an important part of modern wireless communication standards, still no one has researching into MIMO technology forecasting or MIMO patent analysis. Patent analysis is a good way in competitive analysis and technology trend analysis. Lots of paper using patent information in competitive analysis and technology trend analysis because patents are an ample source of technical and commercial knowledge. R&;D practitioners, specialists and researchers can take the results of patent analysis to plan strategies to assess competitive position and to avoid infringement. This research first proposes a logistic regression algorithm to forecast the trend of the MIMO technology and then derive patent maps of the MIMO technology by using the text mining algorithm. Finally ant colony optimization (ACO) algorithm will be proposed to solve minimum spanning tree (MST) problem. The competence set will be expanded for a MIMO design house to help a firm for achieving marketing success.