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    KCI등재

    사회네트워크에서 사용자 행위정보를 활용한 퍼지 기반의 신뢰관계망 추론 모형 = A Fuzzy-based Inference Model for Web of Trust Using User Behavior Information in Social Network

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    https://www.riss.kr/link?id=A82571728

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    We are sometimes interacting with people who we know nothing and facing with the difficult task of making decisions involving risk in social network. To reduce risk, the topic of building Web of trust is receiving considerable attention in social network. The easiest approach to build Web of trust will be to ask users to represent level of trust explicitly toward another users. However, there exists sparsity issue in Web of trust which is represented explicitly by users as well as it is difficult to urge users to express their level of trustworthiness. We propose a fuzzy-based inference model for Web of trust using user behavior information in social network. According to the experiment result which is applied in Epinions.com. the proposed model show improved connectivity in resulting Web of trust as well as reduced prediction error of trustworthiness compared to existing computational model.
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    We are sometimes interacting with people who we know nothing and facing with the difficult task of making decisions involving risk in social network. To reduce risk, the topic of building Web of trust is receiving considerable attention in social netw...

    We are sometimes interacting with people who we know nothing and facing with the difficult task of making decisions involving risk in social network. To reduce risk, the topic of building Web of trust is receiving considerable attention in social network. The easiest approach to build Web of trust will be to ask users to represent level of trust explicitly toward another users. However, there exists sparsity issue in Web of trust which is represented explicitly by users as well as it is difficult to urge users to express their level of trustworthiness. We propose a fuzzy-based inference model for Web of trust using user behavior information in social network. According to the experiment result which is applied in Epinions.com. the proposed model show improved connectivity in resulting Web of trust as well as reduced prediction error of trustworthiness compared to existing computational model.

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    목차 (Table of Contents)

    • Abstract
    • 1. 서론
    • 2. 기존연구
    • 3. 신뢰망 추론을 위한 구성개념 정의
    • 4. ANFIS기반 신뢰망 추론모형
    • Abstract
    • 1. 서론
    • 2. 기존연구
    • 3. 신뢰망 추론을 위한 구성개념 정의
    • 4. ANFIS기반 신뢰망 추론모형
    • 5. 실험
    • 6. 결론
    • 참고문헌
    • 저자소개
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    참고문헌 (Reference)

    1 Chang,E, "The Fuzzy and Dynamic Nature of Trust" 2005

    2 Abdul-Rahman,A, "Supporting trust in virtual communities" Proceeding of HICSS’00 6007-6008, 2000

    3 Sabater J, "Review on computing trust and reputation models" 24 : 33-60, 2005

    4 Song,S, "P2P Transactions with Fuzzy Reputation Aggregation" IEEE Internet Computing 18-28, 2005

    5 Jin,Y.W, "On generating flexible,complete,consistens and compact(FC3)fuzzy rules from data using evolution strategies" 29 (29): 829-845, 1999

    6 Bersini,H, "Now comes the time to defuzzify neuro-fuzzy models" 90 : 161-169, 1997

    7 Palit,A.K, "Nonlinear combination of forecasts using artificial neural network,fuzzy logic and neurofuzzy approaches" 566-571, 2000

    8 Babuka,R, "Neurofuzzy methods for nonlinear system identification" 27 : 73-85, 2003

    9 Nauck,D, "Neuro-fuzzy systems for function approximation" 101 : 261-271, 1999

    10 Jang,J, "Neuro-Fuzzy Modeling and Control" 83 (83): 378-406, 1995

    1 Chang,E, "The Fuzzy and Dynamic Nature of Trust" 2005

    2 Abdul-Rahman,A, "Supporting trust in virtual communities" Proceeding of HICSS’00 6007-6008, 2000

    3 Sabater J, "Review on computing trust and reputation models" 24 : 33-60, 2005

    4 Song,S, "P2P Transactions with Fuzzy Reputation Aggregation" IEEE Internet Computing 18-28, 2005

    5 Jin,Y.W, "On generating flexible,complete,consistens and compact(FC3)fuzzy rules from data using evolution strategies" 29 (29): 829-845, 1999

    6 Bersini,H, "Now comes the time to defuzzify neuro-fuzzy models" 90 : 161-169, 1997

    7 Palit,A.K, "Nonlinear combination of forecasts using artificial neural network,fuzzy logic and neurofuzzy approaches" 566-571, 2000

    8 Babuka,R, "Neurofuzzy methods for nonlinear system identification" 27 : 73-85, 2003

    9 Nauck,D, "Neuro-fuzzy systems for function approximation" 101 : 261-271, 1999

    10 Jang,J, "Neuro-Fuzzy Modeling and Control" 83 (83): 378-406, 1995

    11 Sugeno, M, "Industrial applications of fuzzy control" Elsevier Science Pub 1985

    12 Lesani,M., "Fuzzy trust aggregation and personalized trust inference in virtual social networks" 25 (25): 51-83, 2009

    13 Zadeh,L.A, "Fuzzy sets" 8 : 338-353, 1965

    14 Jin,Y, "Fuzzy modeling of high-dimensional systems:complexity reduction and interpretability improvement" 8 (8): 212-221, 2000

    15 Matlab, "Fuzzy logic toolbox 2 user’s guide" The Math Works Inc 2009

    16 Griffiths N, "Fuzzy Trust for Peer-to-Peer Systems" 1 : 73-78, 2006

    17 Chiu,S, "Fuzzy Model Identification Based on Cluster Estimation" 2 (2): 1994

    18 Atsalakis,G.S, "Forecasting stock market short-term trends using a neuro-fuzzy based methodology" 36 : 10696-10707, 2009

    19 Malhotra,R, "Differentiating between good credits and bad credits using neuro-fuzzy systems" 136 : 190-211, 2002

    20 Takagi,T, "Derivation of fuzzy control rules from human operator’s control actions" 55-60, 1983

    21 Golbeck,J.A, "Computing and applying trust in web-based social networks" Doctor of C.S.dissertation,University of Maryland 2005

    22 Kim,Y.A, "Building a Web of trust without explixit trust ratings" 531-536, 2008

    23 Han M, "An improved fuzzy neural network based on T.S model" 34 : 2905-2920, 2008

    24 Riggs,T, "An algorithm for automated ratings of reviewers" 381-387, 2001

    25 Wang, L. X, "Adaptive fuzzy systems and control:Design and stability analysis" Prentice Hall 1994

    26 Jang,J.,S.R, "ANFIS:Adaptive-Networkbased Fuzzy Inference Systems" 23 (23): 665-685, 1993

    27 송희석, "ANFIS에서 생성된 규칙의 해석용이성 평가" 한국지능정보시스템학회 15 (15): 123-140, 2009

    28 Akhter,F, "A fuzzy logic-based system for assessing the level of business-to-consumer(B2C)trust in electronic commerce" 28 : 623-628, 2005

    29 Efendigil,T, "A decision support system for demand forecasting with artificial neural networks and neuro-fuzzy models:A comparative analysis" 36 : 6697-6707, 2009

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
    2026 평가 재인증평가 신청대상 (재인증)
    2020-04-01 학회명변경 한글명 : 한국데이타베이스학회 -> 한국데이터전략학회
    영문명 : 미등록 -> Korea Data Strategy Society
    KCI등재
    2020-01-01 등재 등재학술지 유지 (재인증) KCI등재
    2017-01-01 등재 등재학술지 유지 (계속평가) KCI등재
    2013-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2010-06-22 학술지명변경 한글명 : Journal of Information Technology Applications & Menagement -> Journal of Information Technology Applications & Management
    외국어명 : Journal of Information Technology Applications & Menagement -> Journal of Information Technology Applications & Management
    KCI등재
    2010-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2008-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2005-01-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    2004-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
    2002-01-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    학술지 인용정보

    학술지 인용정보
    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.39 0.39 0.48
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.59 0.56 0.673 0.18
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