Name
Abstract | ||
|---|---|---|
Patents contain important technical, legal and economic information. Their annual publication accounts for a quarter of the books and journals in the world. Along with the growing number of patents, patent clustering analysis is becoming more and more important. We focus on two key issues in patent clustering, namely patent representation and data visualization. Firstly, patents are represented as technology and effect pairs, and then patents are clustered based on technology and effect matrix, finally a multi-layer patent map is generated. The experiments results show that our method has higher efficiency and better clustering effect than traditional vector space model and the visualization of clustering result is more practical and scalable. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/WISA.2013.33 | IEEE WISA |
Keywords | Field | DocType |
clustering result,effect pair,patents,economic information,pattern clustering,legal information,information retrieval,clustering effect,annual publication account,technical information,text representation,technology and effect matrix,patent representation,technology and effect pairs,patent clustering analysis,data visualisation,effect matrix,information extraction,sematic annotation,multi-layer patent map,data visualization,information visualization,multilayer patent map,patent clustering | Data mining,Data visualization,Information retrieval,Information visualization,Visualization,Computer science,Patent map,Vector space model,Conceptual clustering,Cluster analysis,Patent visualisation | Conference |
ISBN | Citations | PageRank |
978-1-4799-3218-4 | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Xu | 1 | 57 | 15.14 |
| Zhiyong Peng | 2 | 395 | 83.65 |
| Liu Bin | 3 | 37 | 2.63 |