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Using deep learning to improve recommendation with direct and indirect social trust

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References

  • Koren, Y, “Factor in the neighbors: Scalable and accurate collaborative filtering”, ACM Transactions on Knowledge Discovery from Data, Vol.4 (No. 1), Article No.1 : 2011. doi: 10.1145/1644873.1644874
  • Linden G, Smith B and York J, “Amazon.com recommendations: item-to-item collaborative filtering”, IEEE Internet Computing, Vol. 7(1), pp. 76-80 : 2003. doi: 10.1109/MIC.2003.1167344
  • Herlocker, J, Konstan, L, Terveen, L, Riedl, J, “Evaluating collaborative filtering recommender systems”, ACM Transactions on Information Systems, Vol. 22 (No.1), pp. 5-53 : 2004. doi: 10.1145/963770.963772
  • Wei, J, He, J, Chen, K, Zhou, Y, Tang, Z, “Collaborative filtering and deep learning based recommendation system for cold start items”, Expert Systems with Applications, 69, pp.29-39 : 2017. doi: 10.1016/j.eswa.2016.09.040
  • Su, X, Khoshgoftaar T, “A survey of collaborative filtering techniques, Advances in Artificial Intelligence”, Vol. 2009, Article No. 421425 : 2009. doi: 10.1155/2009/421425
  • LeCun, Y, Bengio, Y, Hinton, G, “Deep learning”, Nature, Vol. 521 (7553), pp. 436–444 : 2015. doi: 10.1038/nature14539
  • Cheng, HT, Koc, L, Harmsen, J, Shaked, T, Chandra, T, Aradhye, H, Anderson, G, Corrado, G, Chai, W, Ispir, M, Anil, R, “Wide & deep learning for recommender systems”, In: Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, ACM, pp. 7-10 : 2016.
  • Covington, P, Adams, J, Sargin, E, “Deep neural networks for youtube recommendations”, In Proceedings of the 10th ACM Conference on Recommender Systems, ACM, pp. 191–198 : 2016.
  • Liu, J, Wu, C, “Deep Learning Based Recommendation: A Survey”, In Information Science and Applications, pp. 451-458 : 2017.
  • Lee, H, Lee, J, “Scalable deep learning-based recommendation systems”, ICT Express : 2018.
  • Zhang, S, Yao, L, Sun, A, “Deep learning based recommender system: A survey and new perspectives”, arXiv preprint arXiv: 1707.07435:2017.
  • Deng, S, Huang, L, Xu, G, Wu, X, Wu, Z, “On deep learning for trustaware recommendations in social networks”, IEEE transactions on neural networks and learning systems, Vol. 28(No. 5), pp.1164-1177:2017. doi: 10.1109/TNNLS.2016.2514368
  • Yuan, J, Shalaby, W, Korayem M, Lin, D, AlJadda, K, Luo, J, “Solving cold-start problem in large-scale recommendation engines: A deep learning approach”, arXiv preprint arXiv: 1611.05480 :2016.
  • Liu, JY, “A Survey of Deep Learning Approaches for Recommendation Systems”, In Journal of Physics: Conference Series, Vol. 1087(No. 6), IOP Publishing: 2018.
  • Wang, X, Wang Y, “Improving content-based and hybrid music recommendation using deep learning”, In: Proceedings of the 22nd ACM international conference on Multimedia , pp. 627-636 : 2014.
  • Dang, Q, Ignat, C, “dTrust: a simple deep learning approach for social recommendation”, IEEE International Conference on Collaboration and Internet Computing :2017.
  • Bello-Orgaz, G, Jung, J, Camacho, D, “Social Big data: Recent achievements and new challenges”, Information Fusion, Elsevier, Vol.28, pp. 45-59 : 2016. doi: 10.1016/j.inffus.2015.08.005
  • Guo, G, Zhang, J, Yorke-Smith, N, “A novel recommendation model regularized with user trust and item ratings”, IEEE transactions on knowledge and data engineering, Vol. 28(No.7), pp.1607-1620 : 2016. doi: 10.1109/TKDE.2016.2528249
  • Tang, J, Sun, J, Wang, C, Yang, Z, “Social Influence Analysis in Largescale Networks”, In: Proceedings of Knowledge Discovery and Data Mining, pp. 807-816 : 2009.
  • Rezaei, M, Boostani, R, Rezaei, M, “An efficient initialization method for nonnegative matrix factorization”, J. Appl. Sci., Vol. 11(No. 2), pp. 354–359 : 2011. doi: 10.3923/jas.2011.354.359
  • Gauri Jain, Manisha Sharma, Basant Agarwal, “Spam Detection in Social Media using Convolutional and Long Short Term Memory Neural Network”, Annals of Mathematics and Artificial Intelligence, Springer, DOI:10.1007/s10472-018-9612-z 2019.
  • Kipf, TN, Welling, M, “Semi-supervised classification with graph convolutional networks”, ICLR : 2017.
  • Tang, J, Gao, H, Liu, H, Sarma, AD, “eTrust: understanding trust evolution in an online world”, In: KDD. ACM, pp. 253–261 :2012.
  • www.trustlet.org/Epinions.html
  • https://snap.stanford.edu/data/soc-LiveJournal1.html
  • Alejandro, B, Parapar, J, “Using graph partitioning techniques for neighbor selection in user-based collaborative filtering”, In: Proceedings of the Sixth ACM conference on Recommender Systems, pp.213-216 : 2012.
  • Jamali, M, Ester, M, “Using a trust network to improve top-N recommendation”, In: Proceedings of the Third ACM conference on Recommender Systems, pp. 181-188 , 2009.
  • Shrawan Ram, Shloak Gupta, Basant Agarwal, “Devanagri Character Recognition Model Using Deep Convolution Neural Network”, In Journal of Statistics and Management Systems, Taylor Francis, 21 (4), pages : 593–599, 2018. doi: 10.1080/09720510.2018.1471264
  • Shikhar Seth, Basant Agarwal, “A hybrid deep learning model for detecting diabetic retinopathy”, In Journal of Statistics and Management Systems, Taylor Francis, 21 (4), pages: 569–574 2018. doi: 10.1080/09720510.2018.1466965

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