Pinned Repositories
1M_Generalization
1M_Generalization is a simple anonymization algorithm for 1:M dataset. It contains two sub-algorithms: Mondrian (for relational part) and Partition (transaction part). Both of them are straight forward, and can be repalced by more powerful algorithm with limtied modification.
AGTpy
Attributed Graph Toolbox for Python
AppStoreCrawler
A crawler for ios app store metadata
BMF_Priors
Python code for "Prior and Likelihood Choices for Bayesian Matrix Factorisation on Small Datasets".
dnmf-python
Unofficial Python implementation of the DNMF overlapping community detection algorithm
ic-eval
Code for our KDD'2015 paper: "Influence at Scale: Distributed Computation of Complex Contagion in Networks"
ITSA
Privacy-preserving trajectory stream publishing [DKE 2014] - anonymize a continuous trajectory data stream for achieving LKC-privacy
PatternExtraction
Prefixspan C++ implementation
SNE
Social Network Embedding framework
Springboot-StudyEnglish
基于SpringBoot+MyBatis的英语学习WEB平台，背单词，听听力，看视频等功能
zshwuhan's Repositories
zshwuhan/BiSheServer
本系统是我的毕业设计项目，题目为“基于用户画像的电影推荐系统的设计与实现”。主要是以Django作为基础框架，采用MTV模式，数据库使用MongoDB、MySQL和Redis，以从豆瓣平台爬取的电影数据作为基础数据源，主要基于用户的基本信息和使用操作记录等行为信息来开发用户标签，并使用Hadoop、Spark大数据组件进行分析和处理的推荐系统。管理系统使用的是Django自带的管理系统，并使用simpleui进行了美化。
zshwuhan/CataBEEM
zshwuhan/CIAH
Co-clustering Interactions via Attentive Hypergraph Neural Network (SIGIR 2022)
zshwuhan/clone_anonymous_github
clone/download repositories from https://anonymous.4open.science/
zshwuhan/EINDM
zshwuhan/FL-TEE
OLIVE: Oblivious and Differentially Private Federated Learning on TEE
zshwuhan/FlutterDouBan
🔥🔥🔥Flutter豆瓣客户端,Awesome Flutter Project,全网最100%还原豆瓣客户端。首页、书影音、小组、市集及个人中心，一个不拉。（ https://img.xuvip.top/douyademo.mp4）
zshwuhan/GNPP-code
The implementation of GNPP model.
zshwuhan/GNTPP
This is the official codebase of `Exploring Generative Neural Temporal Point Process' (Accepted by TMLR).
zshwuhan/gpt4free
decentralising the Ai Industry, just some language model api's...
zshwuhan/hawks
A package for generating synthetic clusters with control over "difficulty"
zshwuhan/Interpretable-Point-Processes
zshwuhan/Journal-Response-Letter-Template-Latex
A Latex template for journal review response (initially designed for IEEE TVCG)
zshwuhan/lda4rec
🧮 Extended Latent Dirichlet Allocation for Collaborative Filtering in Recommender Systems.
zshwuhan/manager-worker-mtsptwr
Official implementation of paper "Learning to Solve Multiple-TSP with Time Window and Rejections via Deep Reinforcement Learning"
zshwuhan/MHP
zshwuhan/Neural-Dynamic-Focused-Topic-Model
zshwuhan/nvib
zshwuhan/OSGM
This code belongs to paper entitled "An Online Semantic-enhanced Graphical Model for Evolving Short Text Stream Clustering"
zshwuhan/particles
Sequential Monte Carlo in python
zshwuhan/pfgmpp
Code for "PFGM++: Unlocking the Potential of Physics-Inspired Generative Models"
zshwuhan/ProtoMF
This repository hosts the code and the additional materials for the paper "ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations" by Alessandro B. Melchiorre, Navid Rekabsaz, Christian Ganhör, and Markus Schedl at RecSys 2022.
zshwuhan/Reading-List
A list of papers for group meeting
zshwuhan/RebuttalLetter
LaTeX template for the rebuttal letter used for the academic journal submission
zshwuhan/retentioneering-tools
Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python.
zshwuhan/skstab
:cookie: Clustering stability analysis in Python with a scikit-learn compatible API.
zshwuhan/StochasticProcessesCourse
Assignments and projects of stochastic processes course - Fall 2022
zshwuhan/textCoclustering
Artefatos da dissertação de Mestrado em Sistemas de Informação
zshwuhan/time-series-forecasting-with-python
A use-case focused tutorial for time series forecasting with python
zshwuhan/Zip-dLBM
This GitHub repository contains the code implementation for the dynamic co-clustering approach proposed in the article "A Deep Dynamic Latent Block Model for the Co-clustering of Zero-Inflated Data Matrices”.