Recent developments in recommender systems: A survey
In this technical survey, the latest advancements in the field of recommender systems are
comprehensively summarized. The objective of this study is to provide an overview of the …
comprehensively summarized. The objective of this study is to provide an overview of the …
Result Diversification in Search and Recommendation: A Survey
Diversifying return results is an important research topic in retrieval systems in order to
satisfy both the various interests of customers and the equal market exposure of providers …
satisfy both the various interests of customers and the equal market exposure of providers …
Temporal-structural importance weighted graph convolutional network for temporal knowledge graph completion
Abstract Knowledge graph completion (KGC) tasks are aimed to reason out missing facts in
a knowledge graph. However, knowledge often evolves over time, and static knowledge …
a knowledge graph. However, knowledge often evolves over time, and static knowledge …
Reinforcement recommendation reasoning through knowledge graphs for explanation path quality
Abstract Numerous Knowledge Graphs (KGs) are being created to make Recommender
Systems (RSs) not only intelligent but also knowledgeable. Integrating a KG in the …
Systems (RSs) not only intelligent but also knowledgeable. Integrating a KG in the …
Counterfactual graph augmentation for consumer unfairness mitigation in recommender systems
In recommendation literature, explainability and fairness are becoming two prominent
perspectives to consider. However, prior works have mostly addressed them separately, for …
perspectives to consider. However, prior works have mostly addressed them separately, for …
Knowledge is power, understanding is impact: Utility and beyond goals, explanation quality, and fairness in path reasoning recommendation
Path reasoning is a notable recommendation approach that models high-order user-product
relations, based on a Knowledge Graph (KG). This approach can extract reasoning paths …
relations, based on a Knowledge Graph (KG). This approach can extract reasoning paths …
Improving transformer-based sequential conversational recommendations through knowledge graph embeddings
Conversational Recommender Systems (CRS) have recently drawn attention due to their
capacity of delivering personalized recommendations through multi-turn natural language …
capacity of delivering personalized recommendations through multi-turn natural language …
Hands on explainable recommender systems with knowledge graphs
The goal of this tutorial is to present the RecSys community with recent advances on
explainable recommender systems with knowledge graphs. We will first introduce …
explainable recommender systems with knowledge graphs. We will first introduce …
A generic reinforced explainable framework with knowledge graph for session-based recommendation
Session-based recommendation (SR) has gained increasing attention in recent years. Quite
a great amount of studies have been devoted to designing complex algorithms to improve …
a great amount of studies have been devoted to designing complex algorithms to improve …
Gnnuers: Fairness explanation in gnns for recommendation via counterfactual reasoning
Nowadays, research into personalization has been focusing on explainability and fairness.
Several approaches proposed in recent works are able to explain individual …
Several approaches proposed in recent works are able to explain individual …