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Investigating technology opportunities: the use of SAOx analysis

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Abstract

A patent is regarded as one of the most reliable data sources to investigate such opportunities and has been analyzed in numerous ways. The recent trend of patent analysis has focused on the unstructured part of patent information to extract detailed technological information. In particular, information regarding the purpose or effect of technology, which can be pulled from the unstructured part of patent information, is expected to offer useful insights into expanding its application to other areas. Some previous attempts have been made to systematically use this information to identify new technology opportunities, partly due to difficulties in analyzing the unstructured text data in patent documents. To overcome the limitations of previous studies, this study aims to develop a new method, namely Subject–Action–Object–others (SAOx), which enables an in-depth examination of the purpose and effect of the technology in an efficient manner by analyzing “for” and “to” phrases as well as gerund forms for an object element. We also introduce 39 engineering parameters of TRIZ and technology-designative terms of patent documents to define SAO sets and improve information accuracy. The proposed method is applied to human–machine interaction technologies to understand technology trends and explore technology opportunities based on topic modeling. Methodologically, the research findings contribute to patent engineering by extending the range of information extracted from patent information. Practically, the proposed approach will support corporate decision making in R&D investment by providing comprehensive information regarding the purpose or effect of technology in a structured form, fully extracted from patent documents.

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Acknowledgements

This paper was funded by National Research Foundation of Korea (NRF-2016R1D1A1B03933943).

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Authors and Affiliations

  1. Department of Industrial Engineering, Ajou University, Worldcup-ro 206, Yeongtong-gu, Suwon, 16499, Republic of Korea

    Kyuwoong Kim, Kyeongmin Park & Sungjoo Lee

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  1. Kyuwoong Kim
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  2. Kyeongmin Park
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  3. Sungjoo Lee
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Corresponding author

Correspondence to Sungjoo Lee.

Appendices

Appendix 1

To compare the performance of information retrieval using designative terms (D-type terms) and non-designative terms (ND-type terms), we obtained the recall and precision values for the two approaches. For this analysis, we first collected the top 20 patents retrieved from the USPTO website using the following search terms: ABST/((infotainment or (digital and cluster) or ((human or man or user) and (interface or interact))) and (car or vehicle or automobile)) andnot virus and apd/1/1/2012 → 31/12/2016. Then, a list of SAOs were constructed based on the abstracts of the 20 patents; a total of 72 SAOs, including 42 with D-type terms and 38 with ND-type terms, were extracted. At the same time, we also reviewed the content of those SAOs and classified them into two groups: SAOs accurately providing information about a corresponding invention (True-type) and SAOs providing other information (False-type); out of the 72 SAOs, 49 (30 D-type and 19 ND-type) were classified as True-type, whereas the rest 23 (11 D-type and 12 ND-type) were found to be False-type. Accordingly, the precision and recall values were 0.90 (= 38/42) and 0.78 (= 38/49) when D-type terms were used. On the other hand, the precision and recall values corresponded to 0.37 (= 11/30) and 0.22 (11/49) when ND-type terms were used.

Appendix 2: List of promising topics

See Table 7.

Table 7 Action words to classify SAOs into two types of information
Full size table

Appendix 3: List of promising topics

See Table 8.

Table 8 List of promising topics
Full size table

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Kim, K., Park, K. & Lee, S. Investigating technology opportunities: the use of SAOx analysis. Scientometrics 118, 45–70 (2019). https://doi.org/10.1007/s11192-018-2962-9

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