Official code for Next Check-ins Prediction via History and Friendship on Location-Based Social Networks (MDM 2018)

Overview

MUC

Next Check-ins Prediction via History and Friendship on Location-Based Social Networks (MDM 2018)

Performance

Details for Accuracy:

| Dataset    | [email protected]  | [email protected]   | [email protected]     | 
| ---------- | ------------| -------------| ---------------| 
| Foursquare | 0.8389      | 0.9105       | 0.9368         | 
| Gowalla    | 0.7522      | 0.846        | 0.8866         | 
  • The performance of our framework on Foursquare and Gowalla.

The performance of our framework on Foursquare and Gowalla

Requirements

  • python==3.7

Datasets

We use two real-world LBSN datasets from Foursquare and Gowalla.

Statistics:

| Dataset    | Number of users | Number of POIs | Number of check-ins    | Number of social links  |
| ---------- | --------------- | -------------- | ---------------------- |-------------------------|
| Foursquare | 11,326          | 182,968        | 1,385,223              | 47,164                  |
| Gowalla    | 107,092         | 1,280,969      | 6,442,890              | 950,327                 |

- Foursquare_MUC: Foursquare contains check-in data ranging from January 2011 to July 2011. 

- Gowalla_MUC: Gowalla includes check-in data between Feb. 2009 and Oct 2010.

How to run MUC model

1.python loc_prodict_Foursquare.py
2.python loc_prodict_Gowalla.py

Citation

Please cite our paper if you use the code or datasets:

@inproceedings{SuLTXH18,
  title={Next Check-in Location Prediction via Footprints and Friendship on Location-Based Social Networks},
  author={Yijun Su, Xiang Li,  Wei Tang, Ji Xiang and Neng Gao},
  booktitle={IEEE International Conference on Mobile Data Management, {MDM} 2018}, 
  pages={251-256},
  doi={10.1109/MDM.2018.00044},
  year={2018}
}

Contact

If you have any questions, please contact us by [email protected], we will be happy to assist.

Last Update Date: November 18, 2021

Owner
Yijun Su
AI Researcher at JD. Research interest: Location-based Service, Recommender Systems, Spatio-Temporal Data Mining, Knowledge Graphs, Graph Neural Network.
Yijun Su
PyTorch implementation of the WarpedGANSpace: Finding non-linear RBF paths in GAN latent space (ICCV 2021)

Authors official PyTorch implementation of the "WarpedGANSpace: Finding non-linear RBF paths in GAN latent space" [ICCV 2021].

Christos Tzelepis 100 Dec 06, 2022
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models

AdvBox 1.3k Dec 25, 2022
Epidemiology analysis package

zEpid zEpid is an epidemiology analysis package, providing easy to use tools for epidemiologists coding in Python 3.5+. The purpose of this library is

Paul Zivich 111 Jan 08, 2023
joint detection and semantic segmentation, based on ultralytics/yolov5,

Multi YOLO V5——Detection and Semantic Segmentation Overeview This is my undergraduate graduation project which based on ultralytics YOLO V5 tag v5.0.

477 Jan 06, 2023
PhysCap: Physically Plausible Monocular 3D Motion Capture in Real Time

PhysCap: Physically Plausible Monocular 3D Motion Capture in Real Time The implementation is based on SIGGRAPH Aisa'20. Dependencies Python 3.7 Ubuntu

soratobtai 124 Dec 08, 2022
Implementation of FitVid video prediction model in JAX/Flax.

FitVid Video Prediction Model Implementation of FitVid video prediction model in JAX/Flax. If you find this code useful, please cite it in your paper:

Google Research 62 Nov 25, 2022
GNPy: Optical Route Planning and DWDM Network Optimization

GNPy is an open-source, community-developed library for building route planning and optimization tools in real-world mesh optical networks

Telecom Infra Project 140 Dec 19, 2022
Code for approximate graph reduction techniques for cardinality-based DSFM, from paper

SparseCard Code for approximate graph reduction techniques for cardinality-based DSFM, from paper "Approximate Decomposable Submodular Function Minimi

Nate Veldt 1 Nov 25, 2022
Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019

USSS_ICCV19 Code for Universal Semi Supervised Semantic Segmentation accepted to ICCV 2019. Full Paper available at https://arxiv.org/abs/1811.10323.

Tarun K 68 Nov 24, 2022
OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.

English | 简体中文 Documentation: https://mmtracking.readthedocs.io/ Introduction MMTracking is an open source video perception toolbox based on PyTorch.

OpenMMLab 2.7k Jan 08, 2023
Code release for NeX: Real-time View Synthesis with Neural Basis Expansion

NeX: Real-time View Synthesis with Neural Basis Expansion Project Page | Video | Paper | COLAB | Shiny Dataset We present NeX, a new approach to novel

536 Dec 20, 2022
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b

Thuy Ng 474 Dec 19, 2022
This is a template for the Non-autoregressive Deep Learning-Based TTS model (in PyTorch).

Non-autoregressive Deep Learning-Based TTS Template This is a template for the Non-autoregressive TTS model. It contains Data Preprocessing Pipeline D

Keon Lee 13 Dec 05, 2022
Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch

CoCa - Pytorch Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch. They were able to elegantly fit in contras

Phil Wang 565 Dec 30, 2022
Customizable RecSys Simulator for OpenAI Gym

gym-recsys: Customizable RecSys Simulator for OpenAI Gym Installation | How to use | Examples | Citation This package describes an OpenAI Gym interfac

Xingdong Zuo 14 Dec 08, 2022
Neighborhood Reconstructing Autoencoders

Neighborhood Reconstructing Autoencoders The official repository for Neighborhood Reconstructing Autoencoders (Lee, Kwon, and Park, NeurIPS 2021). T

Yonghyeon Lee 24 Dec 14, 2022
Dyalog-apl-docset - Dyalog APL Dash Docset Generator

Dyalog APL Dash Docset Generator o alasa e kili sona kepeken tenpo lili a A Dash

Maciej Goszczycki 1 Jan 10, 2022
Code for "On Memorization in Probabilistic Deep Generative Models"

On Memorization in Probabilistic Deep Generative Models This repository contains the code necessary to reproduce the experiments in On Memorization in

The Alan Turing Institute 3 Jun 09, 2022
Canonical Appearance Transformations

CAT-Net: Learning Canonical Appearance Transformations Code to accompany our paper "How to Train a CAT: Learning Canonical Appearance Transformations

STARS Laboratory 54 Dec 24, 2022
PyTorch implementation for Partially View-aligned Representation Learning with Noise-robust Contrastive Loss (CVPR 2021)

2021-CVPR-MvCLN This repo contains the code and data of the following paper accepted by CVPR 2021 Partially View-aligned Representation Learning with

XLearning Group 33 Nov 01, 2022