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Product Recommendation using Neural Network based Opinion Mining Framework


Raheesa KK , Cochin College of Engineering and Technology; Vijesh K, Cochin College of Engineering and Technology


Deep Learning, Opinion Mining, Sentiment Classification, Neural Networks and Product Recommendation


The opinion mining models are applied to extract customer interest on the products. The product recommendation applications are built to analyze the product reviews submitted by the customers. Product reviews are valuable for upcoming buyers in helping them make decisions. To this end, different opinion mining techniques are applied judging a review sentence’s orientation is one of their key challenges. The deep learning has emerged as an effective means for solving sentiment classification problems. A neural network intrinsically learns a useful representation automatically without human efforts. The success of deep learning highly relies on the availability of large-scale training data. The deep learning framework is constructed for product review sentiment classification which employs prevalently available ratings as weak supervision signals. The framework consists of two steps: learning a high level representation captures the general sentiment distribution of sentences through rating information and adding a classification layer on top of the embedding layer and use labeled sentences for supervised fine-tuning. Two kinds of low level network structure are explored for modeling review sentences, namely, convolution feature extractors and long short-term memory. The recommendation process increases the accuracy level with minimum computational overhead.

Other Details

Paper ID: IJSRDV7I20372
Published in: Volume : 7, Issue : 2
Publication Date: 01/05/2019
Page(s): 329-332

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