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The aim of the project is to develop recommended systems based on social networks. To find similarity-based between users and compute trust values on different levels of trust. We can extend this work to dynamic levels not fixed to a certain level.

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Recommender-Sytems-Using-Trust-Based-Networks

The aim of the project is to develop recommended systems based on social networks. To find similarity-based between users and compute trust values on different levels of trust. We can extend this work to dynamic levels not fixed to a certain level.

The given solution is generic you can use any dataset which have same column arrangement can work for you.

I uploaded FilmTrust dataset as a sample. You have to set the path of your dataset according to your directory and need to give output path and input path in source code.

The source file (LevelsForTrusting.java) you will find in directory WorkSpace\WorkSpace(Final)\FilmTrust(Fill 1)\src.

If you have any problem regarding code runing you can email me at hassaanbutt67@gmail.com

Please cite our paper if this rsearch is useful for you.

Bib text= @INPROCEEDINGS{9067723, author={M. H. {Farooq Butt} and X. {Zhang} and G. A. {Khan} and A. {Masood} and M. A. {Farooq Butt} and O. {Khudayberdiev}}, booktitle={2019 16th International Computer Conference on Wavelet Active Media Technology and Information Processing}, title={A Novel Recommender Model Using Trust Based Networks}, year={2019}, volume={}, number={}, pages={81-84},}

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The aim of the project is to develop recommended systems based on social networks. To find similarity-based between users and compute trust values on different levels of trust. We can extend this work to dynamic levels not fixed to a certain level.

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