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Applying Deep Learning Models to Analyze Users' Aspects, Sentiment, and Semantic Features for Product Recommendation

Chin-Hui Lai, Kuo-Chiuan Tseng
2022 Applied Sciences  
The proposed method can precisely and efficiently extract the sentiments and semantics of each aspect from review texts and enhance the prediction performance of rating predictions.  ...  This work proposes a method called the aspect-based deep learning rating prediction method (ADLRP), which can extract the aspects, sentiment, and semantic features from users' and items' reviews.  ...  Conflicts of Interest: The authors declare no conflict of interest. Appl. Sci. 2022, 12, 2118  ... 
doi:10.3390/app12042118 fatcat:qvu6jzwx5beo7hgpn5o7gxtyzm

Understanding Rating Behaviour and Predicting Ratings by Identifying Representative Users [article]

Rahul Kamath, Masanao Ochi, Yutaka Matsuo
2016 arXiv   pre-print
While previous approaches to obtaining product ratings require either a large number of user ratings or a few review texts, we show that it is possible to predict ratings with few user ratings and no review  ...  We learn a set of users that represent each of these dimensions and use their ratings to predict product ratings.  ...  This enables us to predict ratings for new products by just looking at the ratings of a small set of users, even when no review text is available.  ... 
arXiv:1604.05468v1 fatcat:jv7bnkv3svgkbnle6xvfvwqhr4

RACRec: Review Aware Cross-Domain Recom-mendation for Fully-Cold-Start User

Yaru Jin, Shoubin Dong, Yong Cai, Jinlong Hu
2020 IEEE Access  
On the other hand, the product feature vector in the target domain, which is generated from review texts by encoder and decoder, is combined with preference vectors of the cold-start user to make the rating  ...  Traditional recommendation algorithms such as matrix factorization, collaborative filtering perform poorly when lack of interactive information of user and product, known as the user cold-start problem  ...  REVIEW-AWARE RECOMMENDER SYSTEM The review text written by a user for a product contains rich information such as the description of the preference of the user, the feature of the product, and how much  ... 
doi:10.1109/access.2020.2982037 fatcat:ntqxbsmu3vgmvcqcl4nbalpzwe

An Informational Search for Review through Data Analytics

Preetha A. S, Swathi K, Jeya Selvi C | Elangovan G
2018 International Journal of Trend in Scientific Research and Development  
With the help of this, the user can get the best product by comparing it with other products.  ...  quality of a product.  ...  The user can get the review for every product. Credible because the prediction is based on majority reviews shared by social media users.  ... 
doi:10.31142/ijtsrd15770 fatcat:6nhb4kbhyvcrzfyocai55uh264

Review Rating Prediction Based on User Context and Product Context

Bingkun Wang, Shufeng Xiong, Yongfeng Huang, Xing Li
2018 Applied Sciences  
In order to solve the issue, we propose a review rating prediction method based on user context and product context by incorporating user information and product information into review texts.  ...  The first part is a global review rating prediction model, which is shared by all users and all products, and it can be learned from training datasets of all users and all products.  ...  Conflicts of Interest: The authors declare no conflict of interest. Appl. Sci. 2018, 8, 1849  ... 
doi:10.3390/app8101849 fatcat:fkmioqk6rzhkfn6xzklh5lqx3y

Review Rating Prediction on Location-Based Social Networks Using Text, Social Links, and Geolocations

Yuehua WANG, Zhinong ZHONG, Anran YANG, Ning JING
2018 IEICE transactions on information and systems  
To address this problem, we develop a review rating prediction framework named TSG by utilizing users' review Text, Social links and the Geolocation information with machine learning techniques.  ...  Most existing methods for review rating prediction on Location-Based Social Networks only capture the semantics of texts, but ignore user information (social links, geolocations, etc.), which makes them  ...  Most of the works are oriented to the traditional review site by utilizing the semantics of review texts.  ... 
doi:10.1587/transinf.2017edp7180 fatcat:anr56xjkg5aeddwhycmfhvtmtu

Review Based Rating Prediction [article]

Tal Hadad
2016 arXiv   pre-print
We introduce a review-based recommendation approach that obtains contextual information by mining user reviews.  ...  As an example application, we used our method to mine contextual data from customers' reviews of movies and use it to produce review-based rating prediction.  ...  CF is a method of making automatic predictions (filtering) about the interests of a user by collecting preferences or taste information from many users (collaborating).  ... 
arXiv:1607.00024v4 fatcat:nkeg3cttc5dmjfenogflkgcgiu

Improving the quality of predictions using textual information in online user reviews

Gayatree Ganu, Yogesh Kakodkar, Amélie Marian
2013 Information Systems  
Online reviews are often accessed by users deciding to buy a product, see a movie, or go to a restaurant.  ...  Our results show that using textual information results in better review score predictions than those derived from the coarse numerical star ratings given by the users.  ...  Acknowledgment This work was partially supported by a Google Research Award and NSF grant IIS-0844935.  ... 
doi:10.1016/ fatcat:saapiaoenff6fizynrwvhtk5um

Leveraging Aspect Phrase Embeddings for Cross-Domain Review Rating Prediction [article]

Aiqi Jiang, Arkaitz Zubiaga
2018 arXiv   pre-print
Online review platforms are a popular way for users to post reviews by expressing their opinions towards a product or service, as well as they are valuable for other users and companies to find out the  ...  These reviews tend to be accompanied by a rating, where the star rating has become the most common approach for users to give their feedback in a quantitative way, generally as a likert scale of 1-5 stars  ...  An approach that predicts review ratings from the review text alone is that by (Fan & Khademi, 2014) .  ... 
arXiv:1811.05689v1 fatcat:7742lznberesza4t2w33fesupm

Prediction of Opinion Keywords and Their Sentiment Strength Score Using Latent Space Learning Methods

Esteban García-Cuesta, Daniel Gómez-Vergel, Luis Gracia-Expósito, Jose M. López-López, María Vela-Pérez
2020 Applied Sciences  
This proposal makes use of natural language processing (NLP) tools for analyzing the text reviews and is based on the assumption that there exist common user tastes which can be represented by latent review  ...  This information often includes both ratings and text reviews expressing somehow their tastes and can be used to predict their future opinions on items not yet reviewed.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app10124196 fatcat:nbblvhy6unbuxe6uafjqlx4bxe

Prediction of User Opinion for Products - A Bag-of-Words and Collaborative Filtering based Approach

Esteban García-Cuesta, Daniel Gómez-Vergel, Luis Gracias Expósito, María Vela-Pérez
2017 Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods  
We will show how users' reviews can be predicted by using a set of words related to their opinions.  ...  In this paper, we intend to extract the intrinsic opinion subspace from users' text reviews -by means of collaborative filtering techniquesin order to capture their tastes and predict their future opinions  ...  Special thanks to Hugo Seage for developing a significant part of the code used for experimentation, and to Jose M. López and Javier García-Blas for their insightful comments.  ... 
doi:10.5220/0006209602330238 dblp:conf/icpram/Garcia-CuestaGE17 fatcat:hnfx54cnqfeatdpml2muf26ska

Modeling and Prediction of Online Product Review Helpfulness: A Survey

Gerardo Ocampo Diaz, Vincent Ng
2018 Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
This survey paper provides an overview of the most relevant work on product review helpfulness prediction and understanding in the past decade, discusses gained insights, and provides guidelines for future  ...  As the popularity of free-form usergenerated reviews in e-commerce and review websites continues to increase, there is a growing need for automatic mechanisms that sift through the vast number of reviews  ...  Acknowledgments We thank the three anonymous reviewers for their detailed and insightful comments on an earlier draft of the paper. This work was supported in part by USAF Grant FA9550-15-1-0346.  ... 
doi:10.18653/v1/p18-1065 dblp:conf/acl/NgD18 fatcat:dd7azocpkrcjpby55meufzx25e

Beyond the stars

Niklas Jakob, Stefan Hagen Weber, Mark Christoph Müller, Iryna Gurevych
2009 Proceeding of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion - TSA '09  
We propose a new technique, topic profile collaborative filtering, where we build user profiles from users' review texts and use these profiles to filter other review texts with the eyes of this user.  ...  error when predicting ratings and a better approximation of user preference orders.  ...  For two products A and B let sr i,A = sr i,B be the two star ratings corresponding to the reviews left by user i.  ... 
doi:10.1145/1651461.1651473 fatcat:z2qwiy6nsnhb3d6actvznltaaq

Review Analysis of Products and Recommendation System

Maria Ann Toms, Manu P S, Mohammed Ashique, Ms. Sajitha
2020 Zenodo  
In this paper, we first classify the text reviews given by different users on different products. There will be a wide variety of reviews about different products in the market.  ...  Later we are performing a collaborative approach to find out the possible list of products a user tend to buy and also the potential customers who are more likely to buy a particular product..  ...  Hence this turns out to be an appropriate prediction based on the interest of a particular user by collecting the taste and preferences from the other users in the system.  ... 
doi:10.5281/zenodo.3892904 fatcat:vrgpmgdavrfmhaxumsjlwjebsa

User-Personalized Review Rating Prediction Method Based on Review Text Content and User-Item Rating Matrix

Bingkun Wang, Bing Chen, Li Ma, Gaiyun Zhou
2018 Information  
With the explosive growth of product reviews, review rating prediction has become an important research topic which has a wide range of applications.  ...  Therefore, we propose a user-personalized review rating prediction method by integrating the review text and user-item rating matrix information.  ...  Conflicts of Interest: The authors declare that there is no conflict of interests regarding the publication of this paper.  ... 
doi:10.3390/info10010001 fatcat:ylb5yk2g4vgotdurtprxzrcduu
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