Recommendation 第12页

【论文笔记】KGAT：融合知识图谱的 CKG 表示 + 图注意力机制的推荐系统

XiangWang,XiangnanHe,YixinCao,MengLiuandTat-SengChua(2019).KGAT:KnowledgeGraphAttentionNetworkforRecommendation.PaperinACMDLorPaperinarXiv.InKDD

HicSuntLeones·2022-11-26 11:40

【保姆级】论文阅读与分析《Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation》

《LearningHeterogeneousKnowledgeBaseEmbeddingsforExplainableRecommendation》-byQingyaoAi,VahidAzizi,XuChenandYongfengZhang

MercyMeng·2022-11-26 11:39

Re30：读论文 LegalGNN: Legal Information Enhanced Graph Neural Network for Recommendation

诸神缄默不语-个人CSDN博文目录论文标题：LegalGNN:LegalInformationEnhancedGraphNeuralNetworkforRecommendation论文ACM官方下载地址

诸神缄默不语·2022-11-26 11:05

【论文笔记】Explainable Reasoning over Knowledge Graphs for Recommendation

DingxianWang，CanranXu,XiangnanHe,YixinCao,Tat-SengChua原文标题：ExplainableReasoningoverKnowledgeGraphsforRecommendation

BodyCsoulN·2022-11-26 11:04

[IJCAI 2022]Next Point-of-Interest Recommendation with Inferring Multi-step Future Preferences

[IJCAI2022]NextPoint-of-InterestRecommendationwithInferringMulti-stepFuturePreferences介绍文章做的问题是nextpoint-of-interst

yujianke100·2022-11-26 04:28

2014CVPR论文

AcceptedOralsReconstructingStorylineGraphsforImageRecommendationfromWebCommunityPhotos(project,PDF)GunheeKim

clxiaoclxiao·2022-11-26 02:17

吴恩达机器学习作业Python实现(八)：异常检测与推荐系统

目录1异常检测1.1高斯分布1.2高斯分布参数估计1.3选择阈值ε1.4高维数据集2推荐系统2.1电影评分数据集2.2协同过滤算法2.2.1协同过滤代价函数2.2.2协同过滤梯度2.3学习模型2.3.1Recommendations3

Hyxx.·2022-11-25 21:47

Recsys21 | 浅谈推荐系统如何在NLP的肩膀上前进

最近在读Recsys2021上的paper，Transformers4Rec:BridgingtheGapbetweenNLPandSequential/Session-BasedRecommendation

文文学霸·2022-11-24 21:58

11.Session-based Recommendation with Graph Neural Networks论文详解

eligible-zzw·2022-11-24 17:19

13.TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation

一、前言目前已经有很多方法通过将会话建模为序列或图来完成对会话的嵌入，进而对next-item进行预测。这些方法将会话压缩为一个固定的表示向量，而不考虑要预测的目标项。之前的大多数方法的出发点就是通过对会话进行嵌入，期望能够捕获到用户意图信息完成对未来可能产生交互物品的预测。本文的作者认为由于目标物品的多样性和用户的兴趣，固定的向量会限制推荐模型的表示能力。因此在本文中提出了一种新的目标注意图神经

eligible-zzw·2022-11-24 17:19

论文《Session-based Recommendation with Graph Neural Networks》阅读

论文《Session-basedRecommendationwithGraphNeuralNetworks》阅读论文概况IntroductionMethodA.ConstructingSessionGraphsB.LearningItemEmbeddingsonSessionGraphsC.GeneratingSessionEmbeddingsD.MakingRecommendationandMo

wzj1212123·2022-11-24 17:48

NARM:Neural Attentive Session-based Recommendation简析

NeuralAttentiveSession-basedRecommendation介绍作者提出之前的工作只考虑了用户的序列表现，但是对用户的主要目的并没有明显地强调，因此作者提出NeuralAttentiveRecommendationMachine

loserChen.·2022-11-24 17:41

论文阅读——《Global Context Enhanced Graph Neural Networks for Session-based Recommendation》

《GlobalContextEnhancedGraphNeuralNetworksforSession-basedRecommendation》基于会话推荐的全局上下文增强图神经网络摘要:基于会话的推荐

I have a lemon·2022-11-24 17:39

论文阅读——《Session-aware Linear Item-Item Models for Session-based Recommendation》

I have a lemon·2022-11-24 17:39

Session-based Recommendation with Graph Neural Networks，SR-GNN代码分析

preprocessutilsinitgenerate_batchget_sliceModelGetitemembeddingGNNforwardSessionGraphforwardGetSessionembedding模型评估Session-basedRecommendationwithGraphNeuralNetworks

hhmy77·2022-11-24 17:08

Graph Contextualized Self-Attention Network for Session-based Recommendation

GraphContextualizedSelf-AttentionNetworkforSession-basedRecommendation本篇论文主要是在讲图上下文自注意力网络做基于session的推荐

NSSWTT·2022-11-24 17:36

Session-based Recommendation with Graph Neural Networks (SR-GNN 2019)

Session-basedRecommendation

NSSWTT·2022-11-24 17:35

Rething the Item Order in Session-based Recommendation with Graph Neural Networks (FGNN 2019)

RethingtheItemOrderinSession-basedRecommendationwithGraphNeuralNetworks本篇文章讲的仍然是使用图神经网络做基于session的推荐，

NSSWTT·2022-11-24 17:35

DataWhale推荐系统论文组队task3--Session-based Recommendation with Graph Neural Networks

Dr. J·2022-11-24 17:04

ICML2020推荐系统相关论文

GraphConvolutionalNetworkforRecommendationwithLow-passCollaborativeFiltersOptimizationandAnalysisofthepAp

工藤旧一·2022-11-24 12:52

推荐系统----SR-GNN: Session-based Recommendation with Graph Neural Networks

GGNN),最后一个表session,local和全局(整体流程可以抄,更换内部组件.就像:GlobalContextEnhancedGraphNeuralNetworksforSession-basedRecommendation

无意识积累中·2022-11-23 19:20

IEEE会议期刊检索查找

四、点击Searchforupcomingcallforpaper…五、开始查询左侧选择会议（Conferences）或者期刊（Periodicals），中间白色输入框内输入检索关键字，然后点击GetRecommendation

永兴呵呵哒·2022-11-23 14:08

论文《TAGNN：Target Attentive Graph Neural Networks for Session-based Recommendation》阅读

论文《TAGNN：TargetAttentiveGraphNeuralNetworksforSession-basedRecommendation》阅读论文概况IntroductionTheProposedMothod

行者^_^煜煜·2022-11-23 09:05

TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation论文阅读笔记

论文标题：TAGNN:TargetAttentiveGraphNeuralNetworksforSession-basedRecommendation发表于：2020SIGIR作者：FengYu,YanqiaoZhu

调包调参侠·2022-11-23 09:50

SR-GNN

Session-basedRecommendationwithGraphNeuralNetworks一、论文1、理论SR-GNN是一种基于会话序列建模的推荐系统。

Altira·2022-11-23 08:32

#Reading Paper# LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation

#论文题目：LightGCN:SimplifyingandPoweringGraphConvolutionNetworkforRecommendation（LightGCN:简化和增强图卷积网络的推荐）

堇禤·2022-11-23 03:28

#Reading Paper# 【选择偏差】ICML‘16：IPS——Recommendations as Treatments: Debiasing Learning

#论文题目：【选择偏差】IPS——RecommendationsasTreatments:DebiasingLearningandEvaluation（作为治疗的建议:消除学习和评估的偏见）#论文地址：

堇禤·2022-11-23 03:57

2019_WSDM_Session-Based Social Recommendation via Dynamic Graph Attention Networks

[论文阅读笔记]2019_WSDM_Session-BasedSocialRecommendationviaDynamicGraphAttentionNetworks论文下载地址：https://doi.org

XingHe_XingHe_·2022-11-23 03:45

序列推荐模型梳理（Sequential Recommendation）

paper_reader·2022-11-22 23:00

Interest-aware Message-Passing GCN for Recommendation WWW2021

ABSTRACT图卷积网络(GCNS)在推荐方面显示出巨大的潜力。这归功于他们通过利用来自高阶邻居的协作信号来学习好的用户和项目嵌入的能力。与其他GCN模型一样，基于GCN的推荐模型也存在一个臭名昭著的过度平滑问题–当堆叠更多层时，节点嵌入会变得更加相似，最终无法区分，从而导致性能下降。最近提出的LightGCN和LR-GCN在一定程度上缓解了这一问题，然而，我们认为它们忽略了推荐中过度平滑问题的

农场主·2022-11-22 11:51

Graph Neural Networks for Social Recommendation（GraphRec2019）阅读笔记

XWF小弟·2022-11-22 08:22

【DataWhale推荐系统论文组队task2--session-based RS with RNN】

Dr. J·2022-11-22 06:40

2020_WWW_Few-Shot Learning for New User Recommendation in Location-based Social Networks

[论文阅读笔记]2020_WWW_Few-ShotLearningforNewUserRecommendationinLocation-basedSocialNetworks论文下载地址：https:/

XingHe_XingHe_·2022-11-22 01:50

个性化推荐系统_如何开发超个性化的推荐系统

cumian8165·2022-11-22 00:01

SCI审稿过程中的几种状态

此人非常重要，他会在审稿人意见的基础上对文章作个综合评价后，给主编一个recommendation。一般主编都会按照AE的意

持续充电ing·2022-11-21 23:40

推荐系统论文之序列推荐：KERL

KERL:AKnowledge-GuidedReinforcementLearningModelforSequentialRecommendation京东优惠券https://m.fenfaw.net/

nidongla·2022-11-21 22:19

【论文阅读】强化学习与知识图谱结合实现序列推荐

前言论文名称：KERL:AKnowledge-GuidedReinforcementLearningModelforSequentialRecommendation时间：SIGIR2020【目录】前言摘要

chenchenlllll·2022-11-21 22:44

《机器学习算法竞赛实战》整理 | 八、实战案例：Elo Merchant Category Recommendation

机器学习算法竞赛实战（图灵出品）》(王贺，刘鹏，钱乾)【摘要书评试读】-京东图书前言比赛链接：https://www.kaggle.com/competitions/elo-merchant-category-recommendation

飞行模式yu·2022-11-21 21:38

转 2015年~2017年SIGIR，SIGKDD，ICML三大会议的Recsys论文

2018年05月07日22:02:15阅读数：95SIGIR-2015【Title】WEMAREC:AccurateandScalableRecommendationthroughWeightedandEnsembleMatrixApproximation

Catly_hit·2022-11-21 19:58

2015年~2017年SIGIR，SIGKDD，ICML三大会议的Recsys论文

2015年~2017年SIGIR，SIGKDD，ICML三大会议的Recsys论文：SIGIR-2015【Title】WEMAREC:AccurateandScalableRecommendationthroughWeightedandEnsembleMatrixApproximation

凯瑟琳喵·2022-11-21 19:55

2021_AAAI_Knowledge-aware Coupled Graph Neural Network for Social Recommendation

[论文阅读笔记]2021_AAAI_Knowledge-awareCoupledGraphNeuralNetworkforSocialRecommendation论文下载地址：https://ojs.aaai.org

XingHe_XingHe_·2022-11-21 19:47

读论文《Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation》

0Summary:Title:Multi-BehaviorHypergraph-EnhancedTransformerforSequentialRecommendationconference:KDD2022

请站在我身后·2022-11-21 18:43

【Notes】Multi-Behavior Sequential Recommendation with Temporal Graph Transformer（2022）

【Notes】Multi-BehaviorSequentialRecommendationwithTemporalGraphTransformer（2022）XiaL,HuangC,XuY,etal.Multi-BehaviorSequentialRecommendationwithTemporalGraphTransformer

norah要努力·2022-11-21 18:13

2022_WSDM_Long Short-Term Temporal Meta-learning in Online Recommendation

[论文阅读笔记]2022_WSDM_LongShort-TermTemporalMeta-learninginOnlineRecommendation论文下载地址：https://doi.org/10.1145

XingHe_XingHe_·2022-11-21 11:00

论文阅读笔记：Amazon.com Recommendations: Item-to-item collaborative filtering

文章目录Amazon.comRecommendations:Item-to-itemcollaborativefiltering电子商务推荐存在的挑战研究思路相关工作：已有的推荐算法及其不足传统协同过滤

Bai_Yin·2022-11-21 04:57

李宏毅机器学习——回归定义和应用例子

10年股票的变动、新闻咨询、公司并购咨询等输出：预测股市明天的平均值自动驾驶（Self-drivingCar）输入：无人车上的各个sensor的数据，例如路况、测出的车距等输出：方向盘的角度商品推荐（Recommendation

嘚嘚鸟·2022-11-21 03:50

Personalized Re-ranking for Recommendation

总结先用rank模型进行rankinit，然后用itememb;useremb+positionemb得到输入向量，再transformer，再softmax输出细节除了考虑物品，还要考虑user-item,itempair之间的特征input-encoding-outputinputlayer用旧rank模型给出一个序列S=[i1,i2,…,in]\mathcal{S}=[i_1,i_2,\do

KpLn_HJL·2022-11-21 02:52

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