Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
A patent search and classification system
Proceedings of the fourth ACM conference on Digital libraries
Information Retrieval
Identifying Communities of Practice
Proceedings of the IFIP 17th World Computer Congress - TC8 Stream on Information Systems: The e-Business Challenge
Identifying Communities of Practice through Ontology Network Analysis
IEEE Intelligent Systems
Using the patent co-citation approach to establish a new patent classification system
Information Processing and Management: an International Journal
A patent document retrieval system addressing both semantic and syntactic properties
PATENT '03 Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20
Patent document categorization based on semantic structural information
Information Processing and Management: an International Journal
Grouping of TRIZ Inventive Principles to facilitate automatic patent classification
Expert Systems with Applications: An International Journal
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Exploring the h-index at patent level
Journal of the American Society for Information Science and Technology
Patent priority network: Linking patent portfolio to strategic goals
Journal of the American Society for Information Science and Technology
Pattern-oriented associative rule-based patent classification
Expert Systems with Applications: An International Journal
The impact of awareness and accessibility on expertise retrieval: A multilevel network perspective
Journal of the American Society for Information Science and Technology
Self organization of a massive document collection
IEEE Transactions on Neural Networks
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Effective patent management is essential for organizations to maintain their competitive advantage. The classification of patents is a critical part of patent management and industrial analysis. This study proposes a hybrid-patent-classification approach that combines a novel patent-network-based classification method with three conventional classification methods to analyze query patents and predict their classes. The novel patent network contains various types of nodes that represent different features extracted from patent documents. The nodes are connected based on the relationship metrics derived from the patent metadata. The proposed classification method predicts a query patent's class by analyzing all reachable nodes in the patent network and calculating their relevance to the query patent. It then classifies the query patent with a modified k-nearest neighbor classifier. To further improve the approach, we combine it with content-based, citation-based, and metadata-based classification methods to develop a hybrid-classification approach. We evaluate the performance of the hybrid approach on a test dataset of patent documents obtained from the U.S. Patent and Trademark Office, and compare its performance with that of the three conventional methods. The results demonstrate that the proposed patent-network-based approach yields more accurate class predictions than the patent network-based approach. © 2011 Wiley Periodicals, Inc.