2.50
Hdl Handle:
http://hdl.handle.net/10547/275677
Title:
Knowledge modeling in prior art search
Authors:
Graf, Erik; Frommholz, Ingo ( 0000-0002-5622-5132 ) ; Lalmas, Mounia; Van Rijsbergen, Keith
Abstract:
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.
Citation:
Graf, E., Frommholz, I., Lalmas, M. van Rijsbergen, K. (2010) 'Knowledge Modeling in Prior Art Search,' in Proceedings of the First Information Retrieval Facility Conference, IRFC 2010, vol. 6107: 31–46
Publisher:
Springer
Issue Date:
2010
URI:
http://hdl.handle.net/10547/275677
DOI:
10.1007/978-3-642-13084-7_4
Additional Links:
http://link.springer.com/chapter/10.1007%2F978-3-642-13084-7_4
Type:
Book chapter
Language:
en
ISBN:
9783642130830
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorGraf, Eriken_GB
dc.contributor.authorFrommholz, Ingoen_GB
dc.contributor.authorLalmas, Mouniaen_GB
dc.contributor.authorVan Rijsbergen, Keithen_GB
dc.date.accessioned2013-03-22T12:50:15Z-
dc.date.available2013-03-22T12:50:15Z-
dc.date.issued2010-
dc.identifier.citationGraf, E., Frommholz, I., Lalmas, M. van Rijsbergen, K. (2010) 'Knowledge Modeling in Prior Art Search,' in Proceedings of the First Information Retrieval Facility Conference, IRFC 2010, vol. 6107: 31–46en_GB
dc.identifier.isbn9783642130830-
dc.identifier.doi10.1007/978-3-642-13084-7_4-
dc.identifier.urihttp://hdl.handle.net/10547/275677-
dc.description.abstractThis 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.en_GB
dc.language.isoenen
dc.publisherSpringeren_GB
dc.relation.urlhttp://link.springer.com/chapter/10.1007%2F978-3-642-13084-7_4en_GB
dc.subjectinformation retrievalen_GB
dc.subjectknowledge modellingen_GB
dc.titleKnowledge modeling in prior art searchen
dc.typeBook chapteren
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