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Multilingual Review-aware Deep Recommender System via Aspect-based Sentiment Analysis
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Improving User Modelling with Content-Based Techniques
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Stacked Cross Attention for Image-Text Matching
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Cross-Lingual Recommendations in a Resource-Based Learning Scenario
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A model to represent users trust in recommender systems using ontologies and fuzzy linguistic modeling
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Joint multi-grain topic sentiment: modeling semantic aspects for online reviews
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Concept-based item representations for a cross-lingual content-based recommendation process
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/taslp.2015.2512041openalex-snapshot
An Unsupervised Cross-Lingual Topic Model Framework for Sentiment Classification
inferredcites →https://doi.org/10.1109/tkde.2018.2831682openalex-snapshot
NAIS: Neural Attentive Item Similarity Model for Recommendation
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Improving recommendation lists through topic diversification
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Factorizing personalized Markov chains for next-basket recommendation
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Cross-lingual keyword recommendation using latent topics
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A new collaborative filtering approach for increasing the aggregate diversity of recommender systems
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Explicit factor models for explainable recommendation based on phrase-level sentiment analysis
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Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS)
inferredcites →https://doi.org/10.1145/2645710.2645728openalex-snapshot
Ratings meet reviews, a combined approach to recommend
inferredcites →https://doi.org/10.1145/2661829.2662019openalex-snapshot
A Cross-Lingual Joint Aspect/Sentiment Model for Sentiment Analysis
inferredcites →https://doi.org/10.1145/2766462.2767694openalex-snapshot
Learning Hierarchical Representation Model for NextBasket Recommendation
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Learning to Rank Features for Recommendation over Multiple Categories
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Convolutional Matrix Factorization for Document Context-Aware Recommendation
inferredcites →https://doi.org/10.1145/3018661.3018665openalex-snapshot
Joint Deep Modeling of Users and Items Using Reviews for Recommendation
inferredcites →https://doi.org/10.1145/3109859.3109890openalex-snapshot
Interpretable Convolutional Neural Networks with Dual Local and Global Attention for Review Rating Prediction
inferredcites →https://doi.org/10.1145/3178876.3186070openalex-snapshot
Neural Attentional Rating Regression with Review-level Explanations
inferredcites →https://doi.org/10.1145/3178876.3186145openalex-snapshot
Aspect-Aware Latent Factor Model
inferredcites →https://doi.org/10.1145/3209978.3210111openalex-snapshot
Review Sentiment-Guided Scalable Deep Recommender System
inferredcites →https://doi.org/10.1145/3219819.3220086openalex-snapshot
Multi-Pointer Co-Attention Networks for Recommendation
inferredcites →https://doi.org/10.1145/3292500.3330906openalex-snapshot
DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation
inferredcites →https://doi.org/10.1145/3298988openalex-snapshot
A Context-Aware User-Item Representation Learning for Item Recommendation
inferredcites →https://doi.org/10.1145/3308558.3313442openalex-snapshot
Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems
inferredcites →https://doi.org/10.1145/3309546openalex-snapshot
Attentive Aspect Modeling for Review-Aware Recommendation
inferredcites →https://doi.org/10.1145/3331184.3331216openalex-snapshot
A Capsule Network for Recommendation and Explaining What You Like and Dislike
inferredcites →https://doi.org/10.1162/tacl_a_00002openalex-snapshot
Multiple Instance Learning Networks for Fine-Grained Sentiment Analysis
inferredcites →https://doi.org/10.18653/v1/d16-1058openalex-snapshot
Attention-based LSTM for Aspect-level Sentiment Classification
inferredcites →https://doi.org/10.18653/v1/d18-1330openalex-snapshot
Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion
inferredcites →https://doi.org/10.18653/v1/d19-1467openalex-snapshot
CAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis
inferredcites →https://doi.org/10.18653/v1/k15-1016openalex-snapshot
Instance Selection Improves Cross-Lingual Model Training for Fine-Grained Sentiment Analysis
inferredcites →https://doi.org/10.18653/v1/n16-1101openalex-snapshot
Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism
inferredcites →https://doi.org/10.18653/v1/p17-1036openalex-snapshot
An Unsupervised Neural Attention Model for Aspect Extraction
inferredcites →https://doi.org/10.18653/v1/s16-1002openalex-snapshot
SemEval-2016 Task 5: Aspect Based Sentiment Analysis
inferredcites →https://doi.org/10.24963/ijcai.2018/521openalex-snapshot
A^3NCF: An Adaptive Aspect Attention Model for Rating Prediction
inferredcites →https://doi.org/10.3115/1220355openalex-snapshot
Proceedings of the 20th international conference on Computational Linguistics - COLING '04
inferredcites →https://doi.org/10.3115/1613715openalex-snapshot
Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08
inferredcites →https://doi.org/10.3115/v1/p15-2128openalex-snapshot
Aspect-Level Cross-lingual Sentiment Classification with Constrained SMT
inferredcites →https://doi.org/10.48550/arxiv.1409.0473openalex-snapshot
Neural Machine Translation by Jointly Learning to Align and Translate
inferredcites →https://doi.org/10.48550/arxiv.1802.07938openalex-snapshot
Aspect-Aware Latent Factor Model: Rating Prediction with Ratings and Reviews
inferredcites →https://doi.org/10.5555/3176764.3176778openalex-snapshot
Explicit document modeling through weighted multiple-instance learning
inferredcites →https://doi.org/10.7551/mitpress/1120.001.0001openalex-snapshot
Advances in Neural Information Processing Systems 14
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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An Improved Recommendation System with Aspect-Based Sentiment Analysis
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Recent approaches for aspect based sentiment analysis: a review
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PRISMA-based approach to study implicit & explicit aspect-based sentiment analysis
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A Contrastive Learning Framework with Tree-LSTMs for Aspect-Based Sentiment Analysis
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Deep shared learning and attentive domain mapping for cross-domain recommendation
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A multi-perspective global–local interaction framework for identifying dialogue acts and sentiments of dialogue utterances jointly
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Twit-CoFiD: a hybrid recommender system based on tweet sentiment analysis
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Transfer learning for aspect based sentiment analysis
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Aspect based sentiment analysis using deep learning approaches: A survey
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Review-based recommendation under preference uncertainty: An asymmetric deep learning framework
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Exploiting deep transformer models in textual review based recommender systems
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Design of news sentiment classification and recommendation system based on multi-model fusion and text similarity
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From uncertain preferences to reliable predictions: A hierarchical preference uncertainty propagation framework for rating prediction
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DIAG: A Deep Interaction-Attribute-Generation model for user-generated item recommendation
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Multi-perspective enhanced representation for effective session-based recommendation
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Unifying aspect-based sentiment analysis BERT and multi-layered graph convolutional networks for comprehensive sentiment dissection
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To Cluster or Not to Cluster: The Impact of Clustering on the Performance of Aspect-Based Collaborative Filtering
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Deep Hotel Recommender System Using Aspect-based Sentiment Analysis of Users’ Reviews
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Context-aware Inductive Graph Matrix Completion with Sentence BERT
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DualGCN: Exploring Syntactic and Semantic Information for Aspect-Based Sentiment Analysis
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Probabilistic Matrix Factorization Recommendation Approach for Integrating Multiple Information Sources
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