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Information Journal Paper

Title

Design and Implementation of a Tag-oriented Recommender System Based on Deep Neural Networks

Pages

  155-174

Abstract

 The main purposes of this research are to design and develop a tag-oriented deep artificial neural network as recommender system for online shops in order to increase online sale. The chosen research method is design science and experimental in which in the evaluation measurement step design of experiment has been used. In order to improve the performance of the recommender system user tags have been used and Deep Neural networks algorithm has been used to recommend movies to users. An experiment has been designed and implemented in which the designed and developed recommender system has been compared to collaborative filtering method, which is one of the established methods of recommendation, in the evaluation metrics of precision, recall and f1 for the recommendation of movies. The result proves that the developed recommender system with utilizing the tag-oriented deep artificial neural network outperforms the collaborative filtering in all of these metrics.

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    APA: Copy

    ROUHANI, SAEED, Zandvakili, Ramin, & ANSARI, MANOUCHEHR. (2018). Design and Implementation of a Tag-oriented Recommender System Based on Deep Neural Networks. MODERN RESEARCHES IN DECISION MAKING, 3(2 ), 155-174. SID. https://sid.ir/paper/371997/en

    Vancouver: Copy

    ROUHANI SAEED, Zandvakili Ramin, ANSARI MANOUCHEHR. Design and Implementation of a Tag-oriented Recommender System Based on Deep Neural Networks. MODERN RESEARCHES IN DECISION MAKING[Internet]. 2018;3(2 ):155-174. Available from: https://sid.ir/paper/371997/en

    IEEE: Copy

    SAEED ROUHANI, Ramin Zandvakili, and MANOUCHEHR ANSARI, “Design and Implementation of a Tag-oriented Recommender System Based on Deep Neural Networks,” MODERN RESEARCHES IN DECISION MAKING, vol. 3, no. 2 , pp. 155–174, 2018, [Online]. Available: https://sid.ir/paper/371997/en

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