Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Attentive Aspect Modeling for Review-aware Recommendation
Joint Deep Modeling of Users and Items Using Reviews for Recommendation
Tag-aware recommender systems based on deep neural networks
Trust-Aware Recommender Systems
Collaborative filtering with weighted opinion aspects
Attentive Recurrent Social Recommendation
Semantics-aware Content-based Recommender Systems
Aspect and sentiment unification model for online review analysis
A user-centric evaluation framework for recommender systems
Tag-aware recommender systems by fusion of collaborative filtering algorithms
Beyond the Stars: Improving Rating Predictions using Review Text Content
Aspect identification and ratings inference for hotel reviews
Towards latent context-aware recommendation systems
A probabilistic rating inference framework for mining user preferences from reviews
Towards the Extraction of Customer-to-Customer Suggestions from Reviews
Product Recommendation System from Users Reviews using Sentiment Analysis
An Unsupervised Neural Attention Model for Aspect Extraction
Critiquing-based recommenders: survey and emerging trends
Collaborative Recommendation via Adaptive Association Rule Mining
Comparative Study of CNN and LSTM based Attention Neural Networks for Aspect-Level Opinion Mining
Designing and Evaluating Explanations for Recommender Systems
Towards String-to-Tree Neural Machine Translation
An Integrated 802.11p WAVE DSRC and Vehicle Traffic Simulator With Experimentally Validated Urban (LOS and NLOS) Propagation Models
TEM: Tree-enhanced Embedding Model for Explainable Recommendation
Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting
AIsim: Functional Simulator for Analog-to-Information Perceptual Systems