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Review-Based Recommender Systems: A Proposed Rating Prediction Scheme Using Word Embedding Representation of Reviews
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-45439-5_16openalex-snapshot
TransRev: Modeling Reviews as Translations from Users to Items
inferredcites →https://doi.org/10.1007/s10115-012-0548-zopenalex-snapshot
Gender, writing and ranking in review forums: a case study of the IMDb
inferredcites →https://doi.org/10.1007/s11257-018-9214-9openalex-snapshot
A comparative analysis of recommender systems based on item aspect opinions extracted from user reviews
inferredcites →https://doi.org/10.1016/j.compeleceng.2018.01.034openalex-snapshot
Ontology and context based recommendation system using Neuro-Fuzzy Classification
inferredcites →https://doi.org/10.1016/j.eswa.2015.07.036openalex-snapshot
ISTS: Implicit social trust and sentiment based approach to recommender systems
inferredcites →https://doi.org/10.1016/j.ipl.2016.08.002openalex-snapshot
Rating prediction using review texts with underlying sentiments
inferredcites →https://doi.org/10.1016/j.is.2012.03.001openalex-snapshot
Improving the quality of predictions using textual information in online user reviews
inferredcites →https://doi.org/10.1016/j.measurement.2016.05.058openalex-snapshot
User based Collaborative Filtering using fuzzy C-means
inferredcites →https://doi.org/10.1109/mis.2007.55openalex-snapshot
Informed Recommender: Basing Recommendations on Consumer Product Reviews
inferredcites →https://doi.org/10.1109/tce.2012.6415015openalex-snapshot
MovieMine: personalized movie content search by utilizing user comments
inferredcites →https://doi.org/10.1145/3209978.3210010openalex-snapshot
Explainable Recommendation via Multi-Task Learning in Opinionated Text Data
inferredcites →https://doi.org/10.1145/3219819.3220086openalex-snapshot
Multi-Pointer Co-Attention Networks for Recommendation
inferredcites →https://doi.org/10.1155/2018/8263704openalex-snapshot
A Sentiment‐Enhanced Hybrid Recommender System for Movie Recommendation: A Big Data Analytics Framework
inferredcites →https://doi.org/10.3390/info10010001openalex-snapshot
User-Personalized Review Rating Prediction Method Based on Review Text Content and User-Item Rating Matrix
inferredcites →https://doi.org/10.48550/arxiv.1607.00024openalex-snapshot
Review Based Rating Prediction
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-91699-2_22openalex-snapshot
Time-Dependent Item Embeddings for Collaborative Filtering
inferred← citeshttps://doi.org/10.1007/978-3-031-14961-0_30openalex-snapshot
AI-Based Recommendation Systems: The Ultimate Solution for Market Prediction and Targeting
inferred← citeshttps://doi.org/10.1007/978-3-031-21689-3_35openalex-snapshot
Interact2Vec: Neural Item and User Embedding for Collaborative Filtering
inferred← citeshttps://doi.org/10.1007/978-3-031-72341-4_14openalex-snapshot
Exploring Task-Specific Dimensions in Word Embeddings Through Automatic Rule Learning
inferred← citeshttps://doi.org/10.1007/978-981-99-3010-4_19openalex-snapshot
Predicting Corresponding Ratings from Goodreads Book Reviews
inferred← citeshttps://doi.org/10.1007/s10772-022-09966-9openalex-snapshot
ArSphere: Arabic word vectors embedded in a polar sphere
inferred← citeshttps://doi.org/10.1007/s41060-026-01103-yopenalex-snapshot
Advancements in text mining based recommender systems: a systematic review
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.113408openalex-snapshot
Interact2Vec — An efficient neural network-based model for simultaneously learning users and items embeddings in recommender systems
inferred← citeshttps://doi.org/10.1109/access.2024.3489658openalex-snapshot
A Comparative Study of Sentiment-Aware Collaborative Filtering Algorithms for Arabic Recommendation Systems
inferred← citeshttps://doi.org/10.1109/icic68054.2025.11309594openalex-snapshot
Data-Driven Destination Intelligence: From Tourist Reviews to Personalized Recommendations with BERT-CNN Sentiment Analysis for Smart Tourism
inferred← citeshttps://doi.org/10.1109/icsse52999.2021.9538423openalex-snapshot
Multi-view Transformation in Recommender Systems
inferred← citeshttps://doi.org/10.1109/icwr51868.2021.9443146openalex-snapshot
Improving Recommender Systems Performances Using User Dimension Expansion by Movies’ Genres and Voting-Based Ensemble Machine Learning Technique
inferred← citeshttps://doi.org/10.1109/tcss.2023.3290558openalex-snapshot
An NLP-Deep Learning Approach for Product Rating Prediction Based on Online Reviews and Product Features
inferred← citeshttps://doi.org/10.1145/3400286.3418253openalex-snapshot
Content-Based Collaborative Filtering using Word Embedding
inferred← citeshttps://doi.org/10.1186/s40537-021-00420-2openalex-snapshot
Evaluation of recent advances in recommender systems on Arabic content
inferred← citeshttps://doi.org/10.1186/s40537-024-00952-3openalex-snapshot
New custom rating for improving recommendation system performance
inferred← citeshttps://doi.org/10.1186/s40537-025-01222-6openalex-snapshot
Combining review elements for modelling various multi-criteria collaborative recommendation models
inferred← citeshttps://doi.org/10.14736/kyb-2022-3-0440openalex-snapshot
A new curve fitting based rating prediction algorithm for recommender systems
inferred← citeshttps://doi.org/10.5753/jbcs.2025.5426openalex-snapshot
Beyond Recommendations: Intrinsic Evaluation Strategies for Item Embeddings in Recommender Systems
inferred← citeshttps://doi.org/10.5753/webmedia.2024.243199openalex-snapshot
Why Ignore Content? A Guideline for Intrinsic Evaluation of Item Embeddings for Collaborative Filtering
inferred← citeshttps://doi.org/10.7717/peerj-cs.1525openalex-snapshot
An experimental study on the performance of collaborative filtering based on user reviews for large-scale datasets
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