@inproceedings{d412d4de7cfa4b84b39882702a22b3a8,
title = "A two-step agglomerative hierarchical clustering method for patent time-dependent data",
abstract = "Patent data have time-dependent property and also semantic attributes. Technology clustering based on patent time-dependent data processed by trend analysis has been used to help technology relationship identification. However, the raw patent data carry more features than processed data. This paper aims to develop a new methodology to cluster patent frequency data based on its timerelated 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-step 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.",
keywords = "Agglomerative hierarchical clustering, Patent analysis, Patent time-dependent data, Technology clustering",
author = "Hongshu Chen and Guangquan Zhang and Jie Lu and Donghua Zhu",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2014.; 7th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2012 with 1st International Conference on Cognitive Systems and Information Processing, CSIP 2012 ; Conference date: 15-12-2012 Through 17-12-2012",
year = "2014",
doi = "10.1007/978-3-642-37829-4\_10",
language = "English",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "111--121",
editor = "Fuchun Sun and Hongbo Li and Tianrui Li",
booktitle = "Foundations and Applications of Intelligent Systems - The Seventh International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2012, Proceedings",
address = "Germany",
}