Abstract
Patent relationship analysis plays an important role in patent processing service and research. Since most existing analytical methods utilize word co-occurrence to measure patent relationships without considering the semantics of patents, the importance of patent relationships could not be measured precisely. To address this issue, we propose an ontology-based approach to rank relationships between patents. Our approach takes advantage of both lexical term relatedness and lexical co-occurrence for text analysis, and utilizes International Patent Classification (IPC) as domain ontology to calculate technical classification relatedness. Experiments on patents show that our approach performs well since multiple influential factors are taken into consideration.
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Acknowledgements
This work is supported by the National Basic Research Program of China (973 Program, Grant No.2012CB315803), the National High-tech R&D Program of China (863 Program, Grant No.2011AA01A101), the National Natural Science Foundation of China (Grant No.61003100 and No.60972011), and Research Fund for the Doctoral Program of Higher Education of China (Grant No.20100002120018 and No.20100002110033).
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Zheng, HT., Ma, N., Jiang, Y., Xia, ST., Li, HQ. (2013). Exploiting Ontologies to Rank Relationships Between Patents. In: Li, J., Qi, G., Zhao, D., Nejdl, W., Zheng, HT. (eds) Semantic Web and Web Science. Springer Proceedings in Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6880-6_19
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DOI: https://doi.org/10.1007/978-1-4614-6880-6_19
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