On Term Selection Techniques for Patent Prior Art Search

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dc.contributor.authorGolestan Far, Mona
dc.contributor.authorSanner, Scott
dc.contributor.authorBouadjenek, Mohamed Reda
dc.contributor.authorFerraro, Gabriela
dc.contributor.authorHawking, David
dc.coverage.spatialSantiago, Chile
dc.date.accessioned2016-06-14T23:21:12Z
dc.date.createdAugust 9-13, 2015
dc.date.issued2015
dc.date.updated2016-06-14T09:02:45Z
dc.description.abstractIn this paper, we investigate the influence of term selection on retrieval performance on the CLEF-IP prior art test collection, using the Description section of the patent query with Language Model (LM) and BM25 scoring functions. We find that an oracular relevance feedback system that extracts terms from the judged relevant documents far outperforms the baseline and performs twice as well on MAP as the best competitor in CLEF-IP 2010. We find a very clear term selection value threshold for use when choosing terms. We also noticed that most of the useful feedback terms are actually present in the original query and hypothesized that the baseline system could be substantially improved by removing negative query terms. We tried four simple automated approaches to identify negative terms for query reduction but we were unable to notably improve on the baseline performance with any of them. However, we show that a simple, minimal interactive relevance feedback approach where terms are selected from only the first retrieved relevant document outperforms the best result from CLEF-IP 2010 suggesting the promise of interactive methods for term selection in patent prior art search.
dc.identifier.isbn9781450336215
dc.identifier.urihttp://hdl.handle.net/1885/103764
dc.publisherAssociation for Computing Machinery (ACM)
dc.relation.ispartofseries38th Annual ACM SIGIR Conference SIGIR2015
dc.sourceOn Term Selection Techniques for Patent Prior Art Search
dc.titleOn Term Selection Techniques for Patent Prior Art Search
dc.typeConference paper
local.bibliographicCitation.lastpage4
local.bibliographicCitation.startpage1
local.contributor.affiliationGolestan Far, Mona, College of Engineering and Computer Science, ANU
local.contributor.affiliationSanner, Scott, College of Engineering and Computer Science, ANU
local.contributor.affiliationBouadjenek, Mohamed Reda, INRIA & LIRMM
local.contributor.affiliationFerraro, Gabriela, College of Engineering and Computer Science, ANU
local.contributor.affiliationHawking, David, College of Engineering and Computer Science, ANU
local.contributor.authoremailu5122080@anu.edu.au
local.contributor.authoruidGolestan Far, Mona, u5122080
local.contributor.authoruidSanner, Scott, u1817461
local.contributor.authoruidFerraro, Gabriela, u5422389
local.contributor.authoruidHawking, David, a109750
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080609 - Information Systems Management
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
local.identifier.ariespublicationu4334215xPUB1479
local.identifier.doi10.1145/2766462.2767801
local.identifier.scopusID2-s2.0-84953774730
local.identifier.uidSubmittedByu4334215
local.type.statusPublished Version

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