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Review Based Rating Prediction [article]

Tal Hadad
2016 arXiv   pre-print
Our evaluations suggest that our system can help produce better prediction rating scores in comparison to the standard prediction methods.  ...  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.  ...  time) • review/summary: review summaryreview/text: text of the review Results Commonly, datasets for recommendation system evaluation are sparse dataset, thus a second preprocessing phase has been  ... 
arXiv:1607.00024v4 fatcat:nkeg3cttc5dmjfenogflkgcgiu

Rating

E. Isaac Sparling, Shilad Sen
2011 Proceedings of the fifth ACM conference on Recommender systems - RecSys '11  
Our analysis draws upon 12,847 movie and product review ratings collected from 348 users through an online survey.  ...  Overall, users work harder with more granular rating scales, but these effects are moderated by item domain (product reviews or movies).  ...  The second page asked the user to rate 20 movies or 7 product reviews ( Figure 2 ). 3 Each item contained text relevant to the item (a plot summary for movies, and the review text for the reviews),  ... 
doi:10.1145/2043932.2043961 dblp:conf/recsys/SparlingS11 fatcat:bypnroot75awbk6a72ql5nteau

Rate Movie App: Implementation of K-Nearest Neighbors Algorithm in the Development of Decision Support System for Philippine Movie Rating and Classification

Ian Dexter M. Siñel, Benilda Eleonor V. Comendador
2019 International Journal on Advanced Science, Engineering and Information Technology  
This paper promotes a Decision Support System that can be used in predicting movie classification and rating using historically evaluated movies from 2010 to 2017.  ...  There are many factors that contribute to the classification and rating of a specific movie.  ...  A study developed methodologies for automatic movie rating prediction [23] using the IMDB [6] database.  ... 
doi:10.18517/ijaseit.9.1.7579 fatcat:n2fxpnyvufhshndyok66mf5faq

Online Reviews & Ratings Inter-contradiction based Product's Quality-Prediction through Hybrid Neural Network

2021 Journal of the Institute of Electronics and Computer  
To deals with this problem, we are introducing a methodology that finds out contradiction of reviews and ratings of a product then finds out the actual score/quality of product which can save people's  ...  Another problem with reviews is that contradiction which exists between ratings and reviews of a product for example a person gives 5 star to a product but write a lengthy list of problem exists in that  ...  This will be a tiring process in case of a huge volume of reviews. This research will help them to judge quality by doing automated analysis of these reviews.  ... 
doi:10.33969/jiec.2021.31003 fatcat:nqxdctpqfjfivipezxkpq3dd3e

Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS)

Qiming Diao, Minghui Qiu, Chao-Yuan Wu, Alexander J. Smola, Jing Jiang, Chong Wang
2014 Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '14  
or "What is the quality of the movie in terms of acting?" helps us to understand why certain ratings are generated. This can be used to provide more meaningful recommendations.  ...  Recommendation and review sites offer a wealth of information beyond ratings.  ...  Failure Modes After examining the cases which have higher prediction error rates, we find that one source of errors is the inconsistency of ratings and review words in reviews.  ... 
doi:10.1145/2623330.2623758 dblp:conf/kdd/DiaoQWSJW14 fatcat:hc4kllwa75dptpp77boqo4glbm

Neural Rating Regression with Abstractive Tips Generation for Recommendation

Piji Li, Zihao Wang, Zhaochun Ren, Lidong Bing, Wai Lam
2017 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '17  
While some existing models integrate text information such as item specifications or user reviews into user and item latent factors for improving the rating prediction, no existing works consider tips  ...  In essence, writing some tips and giving a numerical rating are two facets of a user's product assessment action, expressing the user experience and feelings.  ...  It contains 603,668 users, 367,982 items, and 8,887,781 reviews. We regard the field "summary" as tips, and the number of tips texts is same with the number of reviews.  ... 
doi:10.1145/3077136.3080822 dblp:conf/sigir/LiWRBL17 fatcat:vj4akmnyz5cmhgdqgm6ck3eg3u

Rated aspect summarization of short comments

Yue Lu, ChengXiang Zhai, Neel Sundaresan
2009 Proceedings of the 18th international conference on World wide web - WWW '09  
In this paper, we study the problem of generating a "rated aspect summary" of short comments, which is a decomposed view of the overall ratings for the major aspects so that a user could gain different  ...  The proposed methods are quite general and can be used to generate rated aspect summary automatically given any collection of short comments each associated with an overall rating.  ...  RELATED WORK To the best of our knowledge, no previous study has addressed the problem of generating a rated aspect summary from an overall rating.  ... 
doi:10.1145/1526709.1526728 dblp:conf/www/LuZS09 fatcat:oydkclb4vzhuxnozrrvcxgogoy

From Review to Rating: Exploring Dependency Measures for Text Classification [article]

Samuel Cunningham-Nelson, Mahsa Baktashmotlagh, Wageeh Boles
2017 arXiv   pre-print
Thus, we explored using a non-linear dependency measure for feature selection by maximizing the dependence between the text reviews and corresponding scores.  ...  However, these word vectors have a large number of features which aggravates the burden of computational complexity.  ...  A study, that provides valuable insights into text data analysis, looks at predicting movie revenue from ratings written by critics [7] .  ... 
arXiv:1709.00813v1 fatcat:ej3m4kc76rcrjnd7ekuwxm5kom

Rating Prediction of Social Sentiment from Textual Review By Recognizing Contextual Polarity

Pravin Nimbalkar, Komal Sonwalkar
2018 Journal of Advances and Scholarly Researches in Allied Education  
In our system we are proposing the sentimentbased rating prediction method which will improve the recommendation prediction accuracy.  ...  In recent years, we can see various website on user can provide his/her reviews for product they have purchased.  ...  Acquiring consumer and Rating Prediction of Social Sentiment from Textual Review by Recognizing Contextual Polarity public opinions has long been a huge business itself for marketing, public relations,  ... 
doi:10.29070/15/57054 fatcat:xk57i3243rfgfmzilqzqxqq5zm

Why Amazon's Ratings Might Mislead You: The Story of Herding Effects

Ting Wang, Dashun Wang
2014 Big Data  
Recent experimental studies document that disclosing prior collective ratings distorts individuals' decision making as well as their perceptions of quality and value, highlighting a fundamental discrepancy  ...  Using large-scale longitudinal customer rating datasets, we find that our method successfully captures the dynamics of ratings growth, helping us separate social influence bias from inherent values.  ...  The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S.  ... 
doi:10.1089/big.2014.0063 pmid:27442755 fatcat:fra7zglrrfd63hnd5yuhl25xai

Dynamic Effects Among Movie Ratings, Movie Revenues, and Viewer Satisfaction

Sangkil Moon, Paul K Bergey, Dawn Iacobucci
2010 Journal of Marketing  
text reviews.  ...  In other words, a wide rating variability may indicate that a member's choices have been experimental and risky; in such a case, the member can end up with more disappointing movies than members with a  ...  Copyright of Journal of Marketing is the property of American Marketing Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's  ... 
doi:10.1509/jmkg.74.1.108 fatcat:leebbgqghjbrdeufcp3abm32hu

Mining consumer reviews to generate ratings of different product attributes while producing feature-based review-summary

Akshay Kangale, S. Krishna Kumar, Mohd Arshad Naeem, Mark Williams, M. K. Tiwari
2015 International Journal of Systems Science  
Therefore, it is in the best interest of both customers and manufacturers to have a portal where they can read a complete comprehensive summary of these reviews in minimum time.  ...  Our second objective is to develop a predictive model to predict the next week's product sales based on numerical review ratings and textual features embedded in the reviews.  ...  Both these data can be used to predict whether a review is spam or not.  ... 
doi:10.1080/00207721.2015.1116640 fatcat:yjvb56cqjjdyrjbumo5zgxruiq

Deep Interest Network for Click-Through Rate Prediction [article]

Guorui Zhou, Chengru Song, Xiaoqiang Zhu, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, Kun Gai
2018 arXiv   pre-print
Click-through rate prediction is an essential task in industrial applications, such as online advertising.  ...  Besides, we develop two techniques: mini-batch aware regularization and data adaptive activation function which can help training industrial deep networks with hundreds of millions of parameters.  ...  The task is to predict whether user will rate a given movie to be above 3(positive label) based on historical behaviors.  ... 
arXiv:1706.06978v4 fatcat:dwdh2i7xfbaoncxtk2osfkgu3y

Hierarchical Text Interaction for Rating Prediction [article]

Jiahui Wen and Jingwei Ma and Hongkui Tu and Wei Yin and Jian Fang
2020 arXiv   pre-print
Further case studies provide a deep insight into HTI's ability to capture semantic correlations at different levels of granularities for rating prediction.  ...  To address those limitations, we propose a novel Hierarchical Text Interaction model(HTI) for rating prediction.  ...  Despite proven to be effective in rating predictions, those methods simply concatenate all review texts of a user into a single review, which can inevitably introduce noises and incur information loss,  ... 
arXiv:2010.07628v1 fatcat:yugnqn2hsbhotnbrflrqxzkise

Deep Learning Sentiment Analysis of Amazon.Com Reviews and Ratings

Nishit Shrestha, Fatma Nasoz
2019 International Journal on Soft Computing Artificial Intelligence and Applications  
Our study employs sentiment analysis to evaluate the compatibility of Amazon.com reviews with their corresponding ratings.  ...  We also developed a web service application that predicts the rating score for a submitted review using the trained model and if there is a mismatch between predicted rating score and submitted rating  ...  Each review includes information on rating, product id, helpfulness, reviewer id, review title, review time, and review text. The rating is based on a 5-star scale.  ... 
doi:10.5121/ijscai.2019.8101 fatcat:f7v2ewyf25e4leu5jmxspjs4n4
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