Approaches to intelligent information retrieval
Information Processing and Management: an International Journal - Artificial Intelligence and Information Retrieval
Information retrieval by constrained spreading activation in semantic networks
Information Processing and Management: an International Journal - Artificial Intelligence and Information Retrieval
The vocabulary problem in human-system communication
Communications of the ACM
RUBRIC: a system for rule-based information retrieval
Readings in information retrieval
Application of Spreading Activation Techniques in InformationRetrieval
Artificial Intelligence Review
Associative Document Retrieval Techniques Using Bibliographic Information
Journal of the ACM (JACM)
Simple BM25 extension to multiple weighted fields
Proceedings of the thirteenth ACM international conference on Information and knowledge management
CLEF-IP 2009: retrieval experiments in the intellectual property domain
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Building queries for prior-art search
IRFC'11 Proceedings of the Second international conference on Multidisciplinary information retrieval facility
Scaling up high-value retrieval to medium-volume data
IRFC'10 Proceedings of the First international Information Retrieval Facility conference on Adbances in Multidisciplinary Retrieval
| Hi-index | 0.00 |
This study explores the benefits of integrating knowledge representations in prior art patent retrieval. Key to the introduced approach is the utilization of human judgment available in the form of classifications assigned to patent documents. The paper first outlines in detail how a methodology for the extraction of knowledge from such an hierarchical classification system can be established. Further potential ways of integrating this knowledge with existing Information Retrieval paradigms in a scalable and flexible manner are investigated. Finally based on these integration strategies the effectiveness in terms of recall and precision is evaluated in the context of a prior art search task for European patents. As a result of this evaluation it can be established that in general the proposed knowledge expansion techniques are particularly beneficial to recall and, with respect to optimizing field retrieval settings, further result in significant precision gains.