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{
    "pk": 26304,
    "title": "Extracting Human Face Similarity Judgments: Pairs or Triplets?",
    "subtitle": null,
    "abstract": "Two experimental protocols, pairwise rating and triplet rank-ing, have been commonly used for eliciting perceptual similar-ity judgments for faces and other objects. However, there hasbeen little systematic comparison of the two methods. Pairwiserating has the advantage of greater precision, but triplet rank-ing is potentially a cognitive less taxing task, thus resulting inless noisy responses. Here, we introduce several information-theoretic measures of how useful responses from the two pro-tocols are for the purpose of response prediction and parame-ter estimation. Using face similarity data collected on AmazonMechanical Turk, we demonstrate that triplet ranking is signif-icantly better for extracting subject-specific preferences, whilethe two are comparable when pooling across subjects. Whilethe specific conclusions should be interpreted cautiously, dueto the particularly simple Bayesian model for response gener-ation utilized here, the work provides a information-theoreticframework for quantifying how repetitions within and acrosssubjects can help to combat noise in human responses, as wellas giving some insight into the nature of similarity representa-tion and response noise in humans. More generally, this workdemonstrates that substantial noise and inconsistency corruptsimilarity judgments, both within- and across-subjects, withconsequent implications for experimental design and data in-terpretation.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "similarity judgment"
        },
        {
            "word": "triplet ranking"
        },
        {
            "word": "pairwise rat-ing"
        },
        {
            "word": "information theory"
        },
        {
            "word": "Bayesian modeling"
        }
    ],
    "section": "Papers",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/3bv8j80n",
    "frozenauthors": [
        {
            "first_name": "Linjie",
            "middle_name": "",
            "last_name": "Li",
            "name_suffix": "",
            "institution": "University of California, San Diego",
            "department": ""
        },
        {
            "first_name": "Vicente",
            "middle_name": "",
            "last_name": "Malave",
            "name_suffix": "",
            "institution": "University of California, San Diego",
            "department": ""
        },
        {
            "first_name": "Amanda",
            "middle_name": "",
            "last_name": "Song",
            "name_suffix": "",
            "institution": "University of California, San Diego",
            "department": ""
        },
        {
            "first_name": "Angela",
            "middle_name": "J.",
            "last_name": "Yu",
            "name_suffix": "",
            "institution": "University of California, San Diego",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2016-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26304/galley/15940/download/"
        }
    ]
}