Daryl Hepting

Permanent URI for this collectionhttps://hdl.handle.net/10294/6891

Associate Professor
Department of Computer Science

URL: http://www2.cs.uregina.ca/~hepting/
Email: hepting@cs.uregina.ca
Phone: (306) 585-5210
Fax: (306) 585-4745
Office: College West 308.22

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Browsing Daryl Hepting by Author "Yao, Yiyu"

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    A Linear Model for Three-Way Analysis of Facial Similarity
    (Springer, Cham, 2018-05-18) Hepting, Daryl H.; Bin Amer, Hadeel Hatim; Yao, Yiyu
    Card sorting was used to gather information about facial similarity judgments. A group of raters put a set of facial photos into an unrestricted number of different piles according to each rater’s judgment of similarity. This paper proposes a linear model for 3-way analysis of similarity. An overall rating function is a weighted linear combination of ratings from individual raters. A pair of photos is considered to be similar, dissimilar, or divided, respectively, if the overall rating function is greater than or equal to a certain threshold, is less than or equal to another threshold, or is between the two thresholds. The proposed framework for 3-way analysis of similarity is complementary to studies of similarity based on features of photos.
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    ItemOpen Access
    Three-Way Analysis of Facial Similarity Judgments
    (2017-10-23) Hepting, Daryl H.; Bin Amer, Hadeel Hatim; Yao, Yiyu
    The card sorting problem involves the similarity judgments of pairs of photos, taken from a set of photos, by a group of participants. Given the lack of an objective standard for judging similarity, different participants may be using different strategies in judging the similarity of photos. It could be very useful to identify and study these strategies. In this paper, we present a framework for three-way analysis of judgments of similarity. Based on judgments by the set of participants, we divide all pairs of photos into three classes: a set of similar pairs that are judged by at least 60% of participants as similar; a set of dissimilar pairs that are judged by at least 60% of participants as dissimilar; and a set of undecidable pairs that have conflicting judgments. A more refined three-way classification method is also suggested based on a quantitative description of the quality of similarity judgments. The classification in terms of three classes provides an effective method to examine the notions of similarity, dissimilarity, and disagreement.