A patent search and classification system
Proceedings of the fourth ACM conference on Digital libraries
Using Taxonomy, Discriminants, and Signatures for Navigating in Text Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Comparison of IPC and USPC classification systems in patent prior art searches
PaIR '10 Proceedings of the 3rd international workshop on Patent information retrieval
Patent search using IPC classification vectors
Proceedings of the 4th workshop on Patent information retrieval
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Searches on patents to determine prior art violations are often cumbersome and require extensive manpower to accomplish successfully. When time is constrained, an automatically generated list of candidate patents may decrease search costs and improve search efficiency. We examine whether semantic relations inferred from the pseudo-hierarchy of patent classifications can contribute to the recognition of related patents. We examine a similarity measure for hierarchically-ordered patent classes and subclasses and return a ranked list of candidate patents, using a similarity measure that has demonstrated its effectiveness when applied to WordNet ontologies. We then demonstrate that this ranked list of candidate patents allows us to better constrain the effort needed to examine for prior art violations on a target patent.