Cluster analysis as a technique to guide interface design
International Journal of Man-Machine Studies
The KDD process for extracting useful knowledge from volumes of data
Communications of the ACM
Information Retrieval and Knowledge Discovery Utilizing a BioMedical Patent Semantic Web
IEEE Transactions on Knowledge and Data Engineering
BioPatentMiner: an information retrieval system for biomedical patents
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A Semantic-based Intellectual Property Management System (SIPMS) for supporting patent analysis
Engineering Applications of Artificial Intelligence
Hi-index | 0.01 |
In our days the business, scientific and personal databases are growing in an exponential rate. However, what is truly valuable is the knowledge that can be extracted from the stored data. Knowledge Discovery in patent databases was traditionally based on manual analysis carried out from statistical experts. Nowadays the increasing interest of many actors have led to the development of new tools for discovering and exploiting information related to technological activities and innovation, "hidden" in patent databases. In this paper we present a system that combines efficient and innovative methodologies and tools for the analysis of patent data stored in international databases and the production of scientific and technological indicators.