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- W2953600524 startingPage "100941" @default.
- W2953600524 abstract "Early opportunity identification is critical for technology-based firms seeking to develop technology or product strategies for competitive advantage in the future. This research develops a patent mining approach based on the novelty detection statistical technique to identify unusual patents that may provide a fresh idea for potential opportunities. A natural language processing technique, latent semantic analysis, is applied to extract hidden relations between words in patent documents for alleviating the vocabulary mismatch problem and reducing the cumbersome efforts of keyword selection by experts. The angle-based outlier detection method, a novelty detection statistical technique, is used to determine outlier patents that are distinct from the majority of collected patent documents in a high-dimensional data space. Finally, visualization tools are developed to analyze the identified outlier patents for exploring potential technological opportunities. The developed methodology is applied in the telehealth industry and research findings can help telehealth firms formulate their technology strategies." @default.
- W2953600524 created "2019-07-12" @default.
- W2953600524 creator A5066796679 @default.
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- W2953600524 date "2019-10-01" @default.
- W2953600524 modified "2023-10-14" @default.
- W2953600524 title "A novelty detection patent mining approach for analyzing technological opportunities" @default.
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- W2953600524 doi "https://doi.org/10.1016/j.aei.2019.100941" @default.
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