526互联

diversity preference-aware recommendations evaluating

DE-RRD: A Knowledge Distillation Framework for Recommender System

目录概DE-RRDDistillation Experts (DE)Relaxed Ranking Distillation (RRD)代码 Kang S., Hwang J., Kweon W. and Yu H. DE-RRD: A knowledge distillation framewor ......
Distillation Recommender Knowledge Framework DE-RRD

Topology Distillation for Recommender System

目录概Topology DistillationFull Topology Distillation (FTD)Hierarchical Topology Distillation (HTD)代码 Kang S., Hwang J., Kweon W. and Yu H. Topology dist ......
Distillation Recommender Topology System for

currently, chromedriver 114.0.5735.90 is recommended for chrome 114.*, so it is advised to delete the driver in PATH and retry

报错原因是驱动和浏览器不匹配 解决办法 1.下载低版本的谷歌浏览器 本次使用的是114 下载地址： https://downzen.com/en/windows/google-chrome/download/11405735199/ 2.下载谷歌浏览器的插件 https://registry.npm ......
chromedriver recommended currently 114 advised

Collaborative Distillation for Top-N Recommendation

目录概符号说明Collaborative distillation (CD) Lee J., Choi M., Lee J. and Shim H. Collaborative distillation for top-N recommendation. ICDM, 2019. 概 Ranking- ......
Recommendation Collaborative Distillation Top-N for

Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System

目录概符号说明Ranking Distillation代码 Tang J. and Wang K. Ranking Distillation: Learning compact ranking models with high performance for recommender system. ......
Ranking Distillation Performance Recommender Learning

安装无限重置插件 报错“Your evaluation license has expired ….”您的评估许可证已过期，IntelliJ IDEA将退出

安装无限重置插件 报错“Your evaluation license has expired ….” 您的评估许可证已过期，IntelliJ IDEA将退出 最近不少小伙伴反馈，已经安装了IDE Eval Reset插件，但是在使用的过程中，仍然报错，弹窗提示：“Your evaluation l ......
evaluation 插件 IntelliJ 许可证 license

Learning Heterogeneous Temporal Patterns of User Preference for Timely Recommendation

目录概符号说明TimelyRecMulti-aspect Time Encoder (MATE)Time-aware History Encoder (TAHE)Prediction代码 Cho J., Hyun D., Kang S. and Yu H. Learning heterogeneou ......
Recommendation Heterogeneous Preference Learning Temporal

Attention Mixtures for Time-Aware Sequential Recommendation

目录概符号说明MOJITO代码 Tran V., Salha-Galvan G., Sguerra B. and Hennequin R. Attention mixtures for time-aware sequential recommendation. SIGIR, 2023. 概 本文希望 ......
Recommendation Time-Aware Sequential Attention Mixtures

hugepages_settings.sh-Shell Script to Calculate Values Recommended Linux HugePages-HugeTLB Configuration_DocID401749.1

Oracle Linux-Shell Script to Calculate Values Recommended Linux HugePages-HugeTLB Configuration_DocID401749.1 ######################################## ......
Configuration_DocID hugepages_settings HugePages-HugeTLB Configuration Recommended

PSR是什么？PHP Standards Recommendations

PHP Standards Recommendations 官网：https://www.php-fig.org/psr/ PSR 是 PHP Standard Recommendations 的简写，由 PHP FIG 组织制定的 PHP 规范，是 PHP 开发的实践标准。 PHP FIG,FIG ......
Recommendations Standards PSR PHP

Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach

原文地址：https://arxiv.org/abs/2305.07001 本文作者将用户偏好、意图等构建为指令，并用这些指令调优一个LLM（3B Flan-T5-XL），该方法对用户友好，用户可以与系统交流获取更准确的推荐。 ## INTRODUCTION LLM是建立在自然语言文本上的，它不能直 ......
Recommendation Instruction Following Empowered Approach

How Expressive are Graph Neural Networks in Recommendation

[TOC] > [Cai X., Xia L., Ren X. and Huang C. How expressive are graph neural networks in recommendation? CIKM, 2023.](http://arxiv.org/abs/2308.11127) ......
Recommendation Expressive Networks Neural Graph

Time Matters Sequential Recommendation with Complex Temporal Information

[TOC] > [Ye W., Wang S., Chen X., Wang X., Qin Z. and Yin D. Time Matters: Sequential recommendation with complex temporal information. SIGIR, 2020.]( ......
Recommendation Information Sequential Temporal Matters

通过提示大语言模型进行个性化推荐LLM-Rec: Personalized Recommendation via Prompting Large Language Models

论文原文地址：https://arxiv.org/abs/2307.15780 本文提出了一种提示LLM并使用其生成的内容增强推荐系统的输入的方法，提高了个性化推荐的效果。 ## LLM-Rec Prompting ![](https://img2023.cnblogs.com/blog/17994 ......
Recommendation Personalized Prompting Language 模型

A Contextualized Temporal Attention Mechanism for Sequential Recommendation

[TOC] > [Wu J., Cai R. and Wang H. D\'ej\`a vu: A contextualized temporal attention mechanism for sequential recommendation. WWW, 2020.](http://arxiv. ......
Contextualized Recommendation Sequential Attention Mechanism

Proj CDeepFuzz Paper Reading: Framework for Evaluating Faithfulness of Local Explanations

## Abstract 本文: Task: 1. study the faithfulness of an explanation system to the underlying prediction model on consistency and sufficiency 2. introduc ......
Faithfulness Explanations Evaluating CDeepFuzz Framework

Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

[TOC] > [Fan Z., Liu Z., Zhang J., Xiong Y., Zheng L. and Yu P. S. Continuous-time sequential recommendation with temporal graph collaborative transfo ......
Continuous-Time Recommendation Collaborative Transformer Continuous

大模型时代的推荐系统Recommender Systems in the Era of Large Language Models (LLMs)

文章地址：https://arxiv.org/abs/2307.02046 笔记中的一些小实验中的模型都是基于GPT-3.5架构的ChatGPT模型。 本文主要讲述了比较具有代表性的方法利用LLM去学习user和item的表示，从预训练、微调和提示三个范式回顾了近期用于增强推荐系统的LLM先进技术， ......
Recommender Language 模型 Systems 时代

Position-Enhanced and Time-aware Graph Convolutional Network for Sequential Recommendations

# Position-Enhanced and Time-aware Graph Convolutional Network for Sequential Recommendations [TOC] > [Huang L., Ma Y., Liu Y., Du B., Wang S. and Li ......
Position-Enhanced Recommendations Convolutional Time-aware Sequential

Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)

长尾问题是个老大难问题了。 在推荐中可以是用户/物料冷启动，在搜索中可以是中低频query、文档，在分类问题中可以是类别不均衡。长尾数据就像机器学习领域的一朵乌云，飘到哪哪里就阴暗一片。今天就介绍来自Google的一篇解决长尾物品推荐的论文。 ......
Recommendation Empowering Decoupling Long-tail Network

Time-aware Path Reasoning on Knowledge Graph for Recommendation

[TOC] > [Zhao Y., Wang X., Chen J., Wang Y., Tang W., He X. and Xie H. Time-aware path reasoning on knowledge graph for recommendation. TOIS, 2022.](h ......
Recommendation Time-aware Knowledge Reasoning Graph

How Can Recommender Systems Benefit from Large Language Models: A Survey 阅读笔记

论文主要从LLM应用在推荐系统哪些部分以及LLM如何应用在推荐系统中，还讨论了目前LLM应用在RS中的一些问题。 ###Where? 推荐系统哪些部分哪里可以应用到大模型？文章中提到了特征工程、特征编码、评分/排序函数、推荐流程控制。 - LLM for Feature Engineering - ......
Recommender Language Benefit Systems 笔记

A Neural Influence Diffusion Model for Social Recommendation

[TOC] > [Wu L., Sun P., Fu Y., Hong R., Wang X. and Wang M. A neural influence diffusion model for social recommendation. SIGIR, 2019.](https://dl.acm ......
Recommendation Influence Diffusion Neural Social

SocialLGN Light graph convolution network for social recommendation

[TOC] > [Liao J., Zhou W., Luo F., Wen J., Gao M., Li X. and Zeng J. SocialLGN: Light graph convolution network for social recommendation. Information ......
recommendation convolution SocialLGN network social

论文解读（SimGCL）《Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation》

Note：[ wechat：Y466551 | 可加勿骚扰，付费咨询 ] 论文信息 论文标题：Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation论文作者：Junliang Yu ......
Graph Recommendation Augmentations Contrastive Necessary

Latent generative landscapes as maps of functional diversity in protein sequence space

## 0. foreword 最近看了一篇比较有意思的文章,而且要讲组会了,认真学习一下顺便做个随笔当做我讲组会的草稿 (文章并不是直接翻译,文章的内容按照自己的理解进行了些改动) ## 1. Abstract 变分自编码器是一种无监督的生成模型,当把它应用在蛋白质数据上的时候,可以利用它按照系统发 ......
generative functional landscapes diversity sequence

论文解读（LightGCL）《LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation》

Note：[ wechat：Y466551 | 可加勿骚扰，付费咨询 ] 论文信息 论文标题：LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation论文作者：Cai, Xuheng and Huang, ......
LightGCL Recommendation Contrastive Effective Learning

HS-GCN Hamming Spatial Graph Convolutional Networks for Recommendation

[TOC] > [Liu H., Wei Y., Yin J. and Nie L. HS-GCN: Hamming spatial graph convolutional networks for recommendation. IEEE TKDE.](https://arxiv.org/pdf/ ......
Recommendation Convolutional Networks Hamming Spatial

Python报错 | ImportError: To be able to use evaluate-metric/seqeval, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance'

**报错信息** 使用`metric = evaluate.load("seqeval")`的时候，报如下错误： ```python ImportError: To be able to use evaluate-metric/seqeval, you need to install the fol ......
seqeval install 39 evaluate-metric dependencies

Diverse Substrings

# Diverse Substrings ## 题面翻译 定义一个数字串是**多变的**当且仅当其中所有数字的重复次数均不超过其中不同数字的种类数。 给定一个由 $0$ 到 $9$ 组成的长为 $n$ 的数字串 $s$，求其不同的**多变的**子串 $s_{[l,r]}$ 的个数。 ## 题目描述 ......
Substrings Diverse
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