Graph convolutional networkKnowledge graphLearning resource recommendation? 2024 Elsevier B.V.In recent years, E-learning has gained immense popularity as a prominent mode of education. However, accurately recommending learning resources from a vast amount of data remains a significant challenge. This ...
论文浅析-Reinforcement Learning在Global Illumination的应用 Loui 《Interactive Attention Networks for Aspect-Level Sentiment Classification》笔记 source:IJCAI2016, [pdf] Abstract:本文认为Aspect-level的情感分类任务中,target与context应该具有交互性,即context应该是target-specific的,target也应该是context-specific的,...
Deep learning models can accurately predict molecular properties and help making the search for potential drug candidates faster and more efficient. Many existing methods are purely data driven, focusing on exploiting the intrinsic topology and construct
知识图谱与推荐系统之《Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation》MKR,程序员大本营,技术文章内容聚合第一站。
Knowledge-aware sequence modelling with deep learning for online course recommendation 2023, Information Processing and Management Citation Excerpt : DNN: the deep neural network with course embeddings from the knowledge graph (Svozil et al., 1997). This baseline is a multi-layer feed-forward neural...
知识图谱词嵌入(Knowledge Graph Embedding,KGE)模型:如图6的右侧部分,将知识图谱三元组中的前2个(电影ID和关系实体)作为输入,预测出第3个(目标实体)。 图6 MKR框架 在3个子模型中,最关键的是交叉压缩单元模型。下面就先从该模型开始一步一步地实现MKR框架。
Things2Vec: Semantic modeling in the Internet of Things with graph representation learning. IEEE Internet of Things Journal, 7(3): 1939–1948 Article Google Scholar Huang Z, Xu W, Yu K (2015). Bidirectional LSTM-CRF models for sequence tagging. arXiv preprint. arXiv:1508.01991 Huet A, ...
21|Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation 一、Motivation 现在的推荐方法很多只考虑单一特征,1)复杂的用户行为之间的内部依赖 2) 商品之间的side information。 3)多种类型的用户交互的动态特性。提出框架:KHGT,1)捕获行为内部的信息 2)精确的判断哪些行为对于最终...
Knowledge graph-enhanced molecular contrastive learning with functional prompt This repository is the official implementation of KANO, which is model proposed in a paper: Knowledge graph-enhanced molecular contrastive learning with functional prompt. Brief introduction We propose a Knowledge graph-enhanced mo...
Recommender systems Collaborative filtering Knowledge graph Neural collaborative filtering Knowledge graph representation learning 1. Introduction With the advancement of internet and communication technologies, people are facing increase in data. Obtaining useful information from these big data is one of the ...