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contributor authorJiang, Wei;Zhao, Wu;Du, Lin;Zhang, Kai;Yu, Miao
date accessioned2022-12-27T23:13:00Z
date available2022-12-27T23:13:00Z
date copyright5/17/2022 12:00:00 AM
date issued2022
identifier issn1530-9827
identifier otherjcise_23_2_021002.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4288132
description abstractA crucial part of any recommendation system for manufactured goods is the method used to evaluate the similarity of products. However, despite being central to the performance of many online retailers, current ways of evaluating product similarity are inconsistent with several characteristics of human perception and consequently often generate obvious errors when applied in practice. This paper proposes a new approach that uses the results of a perceptual evaluation of respondents to determine their “inherent knowledge hierarchy.” Using this characterization of the user, we propose a new strategy for determining the perceived similarity of products (PSIM strategy). After a preliminary verification of the proposed approach, we found that the performance of the PSIM strategy is much better than current strategies in terms of both accuracy and robustness. Beyond the application of PSIM in product recommendation systems, the findings of this study have the potential to help designers and companies better understand their customers’ emotional needs.
publisherThe American Society of Mechanical Engineers (ASME)
titleProduct Perceptual Similarity Evaluation: From Attributive Error to Human Knowledge Hierarchy
typeJournal Paper
journal volume23
journal issue2
journal titleJournal of Computing and Information Science in Engineering
identifier doi10.1115/1.4054305
journal fristpage21002
journal lastpage21002_11
page11
treeJournal of Computing and Information Science in Engineering:;2022:;volume( 023 ):;issue: 002
contenttypeFulltext


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