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Communications of the ACM
Specification-based anomaly detection: a new approach for detecting network intrusions
Proceedings of the 9th ACM conference on Computer and communications security
A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
Unsupervised anomaly detection in network intrusion detection using clusters
ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
Introduction to the special issue on patent processing
Information Processing and Management: an International Journal
On the development of a technology intelligence tool for identifying technology opportunity
Expert Systems with Applications: An International Journal
ACM Computing Surveys (CSUR)
Application of anomaly detection algorithms for detecting SYN flooding attacks
Computer Communications
Identification of promising patents for technology transfers using TRIZ evolution trends
Expert Systems with Applications: An International Journal
A patent intelligence system for strategic technology planning
Expert Systems with Applications: An International Journal
Analyzing interdisciplinarity of technology fusion using knowledge flows of patents
Expert Systems with Applications: An International Journal
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In the competitive business environment, early identification of technological opportunities is crucial for technology strategy formulation and research and development planning. There exist previous studies that identify technological directions or areas from a broad view for technological opportunities, while few studies have researched a way to detect distinctive patents that can act as new technological opportunities at the individual patent level. This paper proposes a method of detecting new technological opportunities by using subject---action---object (SAO)-based semantic patent analysis and outlier detection. SAO structures are syntactically ordered sentences that can be automatically extracted by natural language processing of patent text; they explicitly show the structural relationships among technological components in a patent, and thus encode key findings of inventions and the expertise of inventors. Therefore, the proposed method allows quantification of structural dissimilarities among patents. We use outlier detection to identify unusual or distinctive patents in a given technology area; some of these outlier patents may represent new technological opportunities. The proposed method is illustrated using patents related to organic photovoltaic cells. We expect that this method can be incorporated into the research and development process for early identification of technological opportunities.