EMPLOYING LOCALLY LINEAR NEURO-FUZZY MODEL FOR TRUST PREDICTION

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ABBASIMEHR HOSSEIN

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2018 | Issue:4

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Title

EMPLOYING LOCALLY LINEAR NEURO-FUZZY MODEL FOR TRUST PREDICTION

Author(s)

ABBASIMEHR HOSSEIN

Keywords

TRUST NETWORK

ONLINE COMMUNITY

NEURO-FUZZY

LOCALLY LINEAR NEURO FUZZY MODEL

Abstract

TRUST NETWORK CAN BE USEFUL TOOL FOR IDENTIFICATION OF THE TRUSTFUL SOURCES OF INFORMATION IN A SOCIAL WEB APPLICATION. DESPITE THE USEFULNESS OF A TRUST NETWORK, IT IS USUALLY SPARSE AS USERS ARE GENERALLY RELUCTANT TO EXPRESS THE TRUST RELATIONSHIPS. THEREFORE, ONE APPROACH TO MAKE THE TRUST NETWORK DENSER IS TO IDENTIFY THE POTENTIAL TRUST RELATIONSHIPS BETWEEN USERS AND RECOMMEND THE RELIABLE AND TRUSTFUL PARTICIPANT TO USERS. THE MAIN CONTRIBUTION OF THIS RESEARCH IS THE EXAMINATION OF THE PERFORMANCE OF LOCALLY LINEAR NEURO FUZZY (LLNF) MODEL IN THE TRUST PREDICTION CONTEXT. THEREFORE, LLNF WAS COMPARED WITH TWO CLASSIFICATION TECHNIQUES INCLUDING ANFIS AND C4.5 DECISION TREE. TO CONDUCT EXPERIMENTS, DATA OF EPINIONS NETWORK WERE USED. THE RESULTS OF EXPERIMENTS DEMONSTRATE THAT LLNF ACHIEVES THE HIGHEST PERFORMANCE IN TERMS OF AREA UNDER ROC (AUC). IN ADDITION, LLNF FOLLOWS CLOSELY C4.5 DECISION TREE REGARDING F-MEASURE. LLNF CAN BE A GOOD CANDIDATE FOR TRUST RELATIONSHIPS PREDICTION.

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APA: Copy

ABBASIMEHR, HOSSEIN. (2018). EMPLOYING LOCALLY LINEAR NEURO-FUZZY MODEL FOR TRUST PREDICTION. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/948815/en

Vancouver: Copy

ABBASIMEHR HOSSEIN. EMPLOYING LOCALLY LINEAR NEURO-FUZZY MODEL FOR TRUST PREDICTION. 2018. Available from: https://sid.ir/paper/948815/en

IEEE: Copy

HOSSEIN ABBASIMEHR, “EMPLOYING LOCALLY LINEAR NEURO-FUZZY MODEL FOR TRUST PREDICTION,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2018, [Online]. Available: https://sid.ir/paper/948815/en

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