Abstract
The U.S. recently adopted a post-grant opposition procedure to encourage third parties to challenge the validity of newly granted patents by providing relevant prior patents that are missed during patent examination (i.e., missing citations). In this paper, we propose a recommendation system for missing citations for newly granted patents. The recommendation system, based on the patent citation network of a newly granted query patent, focuses on paths that start with the references of the query patent in the network. Our approach is to identify the relevancy of a candidate patent to the query patent by its citation relationship (paths) that are distinguished based on the direction, topology and semantics of the paths in the network. We consider six different types of paths between a candidate patent and a query patent based on their citation relationship and define a relevancy score for each path type. Accordingly, we rank candidate patents via a RankSVM model learned by using those relevancy scores as features. The experimental results show our approach significantly improves the average precision and recall performance compared to two baseline methods, i.e., Katz distance and text similarity.
Original language | English (US) |
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Title of host publication | DSAA 2014 - Proceedings of the 2014 IEEE International Conference on Data Science and Advanced Analytics |
Editors | George Karypis, Longbing Cao, Wei Wang, Irwin King |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 442-448 |
Number of pages | 7 |
ISBN (Electronic) | 9781479969913 |
DOIs | |
State | Published - Mar 10 2014 |
Event | 2014 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2014 - Shanghai, China Duration: Oct 30 2014 → Nov 1 2014 |
Other
Other | 2014 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2014 |
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Country/Territory | China |
City | Shanghai |
Period | 10/30/14 → 11/1/14 |
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Information Systems
- Information Systems and Management