Knowledge-aware Collaborative Filtering with Pre-trained Language Model for Personalized Review-based Rating Prediction

by   Quanxiu Wang, et al.

Personalized review-based rating prediction aims at leveraging existing reviews to model user interests and item characteristics for rating prediction. Most of the existing studies mainly encounter two issues. First, the rich knowledge contained in the fine-grained aspects of each review and the knowledge graph is rarely considered to complement the pure text for better modeling user-item interactions. Second, the power of pre-trained language models is not carefully studied for personalized review-based rating prediction. To address these issues, we propose an approach named Knowledge-aware Collaborative Filtering with Pre-trained Language Model (KCF-PLM). For the first issue, to utilize rich knowledge, KCF-PLM develops a transformer network to model the interactions of the extracted aspects w.r.t. a user-item pair. For the second issue, to better represent users and items, KCF-PLM takes all the historical reviews of a user or an item as input to pre-trained language models. Moreover, KCF-PLM integrates the transformer network and the pre-trained language models through representation propagation on the knowledge graph and user-item guided attention of the aspect representations. Thus KCF-PLM combines review text, aspect, knowledge graph, and pre-trained language models together for review-based rating prediction. We conduct comprehensive experiments on several public datasets, demonstrating the effectiveness of KCF-PLM.


page 1

page 2

page 5

page 11

page 13


Transformer-Empowered Content-Aware Collaborative Filtering

Knowledge graph (KG) based Collaborative Filtering is an effective appro...

Hierarchical Text Interaction for Rating Prediction

Traditional recommender systems encounter several challenges such as dat...

GRAM: Fast Fine-tuning of Pre-trained Language Models for Content-based Collaborative Filtering

Content-based collaborative filtering (CCF) predicts user-item interacti...

KNNs of Semantic Encodings for Rating Prediction

This paper explores a novel application of textual semantic similarity t...

Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network

Personalized review generation (PRG) aims to automatically produce revie...

CTRL: Connect Tabular and Language Model for CTR Prediction

Traditional click-through rate (CTR) prediction models convert the tabul...

A Capsule Network for Recommendation and Explaining What You Like and Dislike

User reviews contain rich semantics towards the preference of users to f...

Please sign up or login with your details

Forgot password? Click here to reset