Minyi Guo

Knowledge Graph Convolutional Networks for Recommender Systems

2019

To alleviate sparsity and cold start problem of collaborative filtering based recommender systems, researchers and engineers usually collect attributes of users and items, and design delicate algorithms to exploit these additional information. In general, the …

Characterizing and Balancing the Workloads of Semi-Containerized Clouds

2019

With the development of Cloud computing, many applications are deployed on the Clouds (either public Clouds or private Clouds) for the elastic resource management. A key challenge here is satisfying the Quality-of-Service requirement of online …

Sturgeon: Preference-aware Co-location for Improving Utilization of Power Constrained Computers

2020

Large-scale datacenters often host latency-sensitive services that have stringent Quality-of-Service requirement and experience diurnal load pattern. Co-locating best-effort applications that have no QoS requirement with latency-sensitive services has been widely used to improve the resource …

Accelerating Sparse DNN Models without Hardware-Support via Tile-Wise Sparsity

2020

Network pruning can reduce the high computation cost of deep neural network (DNN) models. However, to maintain their accuracies, sparse models often carry randomly-distributed weights, leading to irregular computations. Consequently, sparse models cannot achieve meaningful …

DKN: Deep Knowledge-Aware Network for News Recommendation

2018 · arXiv (Cornell University)

Online news recommender systems aim to address the information explosion of news and make personalized recommendation for users. In general, news language is highly condensed, full of knowledge entities and common sense. However, existing methods …

RippleNet

2018

To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance. This paper considers the knowledge graph …

Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation

2019

Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to address the issues and improve the performance of recommender systems. In this …

Exploring High-Order User Preference on the Knowledge Graph for Recommender Systems

2019 · ACM Transactions on Information Systems

To address the sparsity and cold-start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve the performance of recommendation. In this article, we consider …

DKN

2018

Online news recommender systems aim to address the information explosion of news and make personalized recommendation for users. In general, news language is highly condensed, full of knowledge entities and common sense. However, existing methods …