Prior art search is a core process of technology management performed by inventors and applicants, patent examiners, and employees in the patent industry. As a result of insufficient academic research on a systematic prior art search methodology, the process has been often carried out depending on the subjective judgment of researchers. Previous studies on exploring prior arts based on semantics have also have the risk of underestimating the similarity of major prior arts due to the nature of patent documents where the same technical ideas are expressed in various terms. In this study, we propose an effective prior art search methodology based on hierarchical citation analysis, which provides a clear criterion for selecting core prior arts by calculating weights according to the relative importance of the collected patents. In order to verify the feasibility of the proposed methodology, a case study was conducted to explore the core prior art of one patent in the display field. As a result, 10 core prior art candidates were selected out of the 206 precedent patents.

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An autonomous vehicle is a convergence of artificial intelligence and a vehicle which can drive itself while analyzing the real-time situation on a road without a driver. A lot of research achievements have been revealed through the media and Google is considered to be the best leading company in this field. The use of patent information which contains various information such as bibliographic data and information about technologies is a good way to find out the R&D direction of a company and develop a reasonable strategy. This study is aimed at investigating the direction to which Google focuses its R&D capabilities and establishing strategies for technology development. Google's patents about autonomous vehicles were collected and the degree of research bias was analyzed using Social Network Analysis based on citations indicating the quality of a patent. Based on the results, the strategies for technology development was eventually proposed. As a result, it was revealed that Google focused its R&D capabilities on the part of hardware control to make up for its lack of hardware-oriented technologies. As of now, Google obtained remarkable achievements, so it seems reasonable that last-movers consider cooperative research with Google.