A Two-steps Agglomerative Hierarchical Clustering Method for Patent Time-dependent Data

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Conference Proceeding
The 7th International Conference on Intelligent Systems and Knowledge Engineering, 2014, pp. 111 - 121
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Patent data has time-dependent property and also semantic attributes. Technology clustering based on patent time-dependent data which processed by trend analysis has been used to help technologies relationships identification. However, the raw patent data carries more features than processed data. This paper aims to develop a new methodology to cluster patent frequency data based on its time-related properties. To handle time-dependent attributes of patent data, this study first compares it with typical time-series data to propose preferable similarity measurement approach. It then presents a two-steps agglomerative hierarchical technology clustering method to cluster original patent time-dependent data directly. Finally, a case study using communication-related patents is given to illustrate the clustering method.
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