• Title/Summary/Keyword: 선호성

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Generating Pairwise Comparison Set for Crowed Sourcing based Deep Learning (크라우드 소싱 기반 딥러닝 선호 학습을 위한 쌍체 비교 셋 생성)

  • Yoo, Kihyun;Lee, Donggi;Lee, Chang Woo;Nam, Kwang Woo
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.5
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    • pp.1-11
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    • 2022

  • With the development of deep learning technology, various research and development are underway to estimate preference rankings through learning, and it is used in various fields such as web search, gene classification, recommendation system, and image search. Approximation algorithms are used to estimate deep learning-based preference ranking, which builds more than k comparison sets on all comparison targets to ensure proper accuracy, and how to build comparison sets affects learning. In this paper, we propose a k-disjoint comparison set generation algorithm and a k-chain comparison set generation algorithm, a novel algorithm for generating paired comparison sets for crowd-sourcing-based deep learning affinity measurements. In particular, the experiment confirmed that the k-chaining algorithm, like the conventional circular generation algorithm, also has a random nature that can support stable preference evaluation while ensuring connectivity between data.

  • https://doi.org/10.9723/jksiis.2022.27.5.001 인용 PDF KSCI

Point Symbols on Tourist Maps: Cognitive Characteristics with Levels of Symbolization and Preference (관광지도 점기호의 상징수준과 선호도에 나타난 인지특성 연구)

  • Shim, Hye-Kyoung;Jung, In-Chul
    • Journal of the Korean Geographical Society
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    • v.43 no.6
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    • pp.981-1001
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    • 2008

  • This research deals with cognitive characteristics of point symbols on the current tourist maps in terms of the communication theory in considering levels of symbolization and those of preference. The levels of symbolization are examined on the basis of the meaning of point symbols between map-makers and map-users. Preferences of point symbols are investigated by the tourist objects. As a result, when point symbols are expressed in conciseness, the meaning and interpretation about those symbols are highly accorded. And the point symbols that have familiarity by visual experience are preferred. Also, the higher symbolical levels symbols have, the more likely they are preferred. Through that fact, familiarity from the visual experience, conciseness in expression, concreteness of figures expressed in maps, and representativeness of visualized properties were deduced as factors that affect preferences. Those factors work to affect preference complicatedly, but familiarity is prior to simplicity in preferences. Likewise, ways that visualize information, contents that are expressed as images and familiarity in terms of cognitive characteristics make a relative difference in preferences and the levels of symbolization. On the basis of those cognitive characteristics, visual complexity and ambiguity should be removed and the higher symbolical level of point symbols for efficiency of map-reading should be developed.

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