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    Customer Reviews Analysis With Deep Neural Networks for E-Commerce Recommender Systems

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    Author
    SHOJA, BABAK MALEKI; TABRIZI, NASSEH
    Abstract
    An essential prerequisite of an effective recommender system is providing helpful information regarding users and items to generate high-quality recommendations. Written customer review is a rich source of information that can offer insights into the recommender system. However, dealing with the customer feedback in text format, as unstructured data, is challenging. In this research, we extract those features from customer reviews and use them for similarity evaluation of the users and ultimately in recommendation generation. To do so, we developed a glossary of features for each product category and evaluated them for removing irrelevant terms using Latent Dirichlet Allocation. Then, we employed a deep neural network to extract deep features from the reviews-characteristics matrix to deal with sparsity, ambiguity, and redundancy. We applied matrix factorization as the collaborative ltering method to provide recommendations. As the experimental results on the Amazon.com dataset demonstrate, our methodology improves the performance of the recommender system by incorporating information from reviews and produces recommendations with higher quality in terms of rating prediction accuracy compared to the baseline methods.
    URI
    http://hdl.handle.net/10342/7580
    Subject
     Recommender system; review; deep neural networks; recommendation; matrix factorization; latent Dirichlet allocation 
    Date
    2019-08-26
    Citation:
    APA:
    SHOJA, BABAK MALEKI, & TABRIZI, NASSEH. (August 2019). Customer Reviews Analysis With Deep Neural Networks for E-Commerce Recommender Systems. , (), - . Retrieved from http://hdl.handle.net/10342/7580

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    MLA:
    SHOJA, BABAK MALEKI, and TABRIZI, NASSEH. "Customer Reviews Analysis With Deep Neural Networks for E-Commerce Recommender Systems". . . (), August 2019. September 22, 2023. http://hdl.handle.net/10342/7580.
    Chicago:
    SHOJA, BABAK MALEKI and TABRIZI, NASSEH, "Customer Reviews Analysis With Deep Neural Networks for E-Commerce Recommender Systems," , no. (August 2019), http://hdl.handle.net/10342/7580 (accessed September 22, 2023).
    AMA:
    SHOJA, BABAK MALEKI, TABRIZI, NASSEH. Customer Reviews Analysis With Deep Neural Networks for E-Commerce Recommender Systems. . August 2019; (): . http://hdl.handle.net/10342/7580. Accessed September 22, 2023.
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