Discernibility in the Analysis of Binary Card Sort Data

dc.contributor.authorHepting, Daryl
dc.date.accessioned2017-02-22T17:48:49Z
dc.date.available2017-02-22T17:48:49Z
dc.date.issued2013-10-11
dc.description.abstractIn an open card sorting study of 356 facial photographs, each of 25 participants created an unconstrained number of piles. We consider all 63,190 possible pairs of photos: if both photos are in the same pile for a participant, we consider them as rated similar; otherwise we consider them as rated dissimilar. Each pair of photos is an attribute in an information system where the participants are the objects. We consider whether the attribute values permit accurate classification of the objects according to binary decision classes, without loss of generality. We propose a discernibility coefficient to measure the support of an attribute for classification according to a given decision class pair. We hypothesize that decision class pairs with the support of many attributes are more representative of the data than those with the support of few attributes. We present some computational experiments and discuss opportunities for future work.en_US
dc.description.authorstatusFacultyen_US
dc.description.peerreviewyesen_US
dc.description.sponsorshipThis work was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada. Emad Almestadi acknowledges the Ministry of Higher Education in Saudi Arabia and the Saudi Arabian Cultural Bureau in Canada for their support.en_US
dc.identifier.citationHepting D.H., Almestadi E.H. (2013) Discernibility in the Analysis of Binary Card Sort Data. In: Ciucci D., Inuiguchi M., Yao Y., Ślęzak D., Wang G. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2013. Lecture Notes in Computer Science, vol 8170. Springer, Berlin, Heidelbergen_US
dc.identifier.isbn978-3-642-41217-2
dc.identifier.isbn978-3-642-41218-9
dc.identifier.urihttps://hdl.handle.net/10294/7263
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesLecture Notes in Computer Science, Volume 8170en_US
dc.titleDiscernibility in the Analysis of Binary Card Sort Dataen_US
dc.typeBook chapteren_US
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