A recommendation algorithm of we-media articles

Since the explosive growth1 of we-medias today, personalized recommendation is playing an increasingly important role. How to help users to find their target articles in vast amounts of data, has become a very challenging job. Deep learning, on the other hand, have been shown good results in the image processing, computer vision, natural language processing and other fields. But it's a relatively blank in the application of we-media articles recommendation. Combining with the new features of we-media articles, this paper puts forward a recommendation algorithm of we-media articles based on topic model, Latent Dirichlet Allocation (LDA), and deep learning algorithm, Recurrent Neural Networks (RNNs).

[1]  Shuohang Wang,et al.  Learning Natural Language Inference with LSTM , 2015, NAACL.

[2]  Christopher Kermorvant,et al.  Dropout Improves Recurrent Neural Networks for Handwriting Recognition , 2013, 2014 14th International Conference on Frontiers in Handwriting Recognition.

[3]  이주연,et al.  Latent Dirichlet Allocation (LDA) 모델 기반의 인공지능(A.I.) 기술 관련 연구 활동 및 동향 분석 , 2018 .

[4]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[5]  P J Webros.  BACKPROPAGATION THROUGH TIME: WHAT IT DOES AND HOW TO DO IT , 1990 .

[6]  Vijay Anand Sullare,et al.  Rule Based Recommendation System for Performance Improvement in Engineering Institutions , 2016 .

[7]  Stephen Grossberg,et al.  Recurrent neural networks , 2013, Scholarpedia.

[8]  Greg Linden,et al.  Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .

[9]  Yoshua Bengio,et al.  Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.

[10]  Michael J. Pazzani,et al.  Content-Based Recommendation Systems , 2007, The Adaptive Web.

[11]  Paul J. Werbos,et al.  Backpropagation Through Time: What It Does and How to Do It , 1990, Proc. IEEE.

[12]  G. McLachlan,et al.  The EM algorithm and extensions , 1996 .

[13]  G. McLachlan,et al.  The EM Algorithm and Extensions: Second Edition , 2008 .

[14]  Nitish Srivastava,et al.  Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..

[15]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[16]  Jason Weston,et al.  A Neural Attention Model for Abstractive Sentence Summarization , 2015, EMNLP.

[17]  Hermann Ney,et al.  LSTM Neural Networks for Language Modeling , 2012, INTERSPEECH.