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
[NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training

Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Code for NeurIPS 2021 paper "Better Safe Than Sorry: Preventing Delu

Lue Tao 29 Sep 20, 2022
PyTorch implementation of Constrained Policy Optimization

PyTorch implementation of Constrained Policy Optimization (CPO) This repository has a simple to understand and use implementation of CPO in PyTorch. A

Sapana Chaudhary 25 Dec 08, 2022
Facestar dataset. High quality audio-visual recordings of human conversational speech.

Facestar Dataset Description Existing audio-visual datasets for human speech are either captured in a clean, controlled environment but contain only a

Meta Research 87 Dec 21, 2022
Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets" (ECCV 2020 Spotlight)

Distribution-Balanced Loss [Paper] The implementation of our paper Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets (

Tong WU 304 Dec 22, 2022
Script for getting information in discord

User-info.py Script for getting information in https://discord.com/ Instalação: apt-get update -y apt-get upgrade -y apt-get install git pkg install

Moleey 1 Dec 18, 2021
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation.

Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi

HYOJINPARK 22 Jan 01, 2023
N-gram models- Unsmoothed, Laplace, Deleted Interpolation

N-gram models- Unsmoothed, Laplace, Deleted Interpolation

Ravika Nagpal 1 Jan 04, 2022
SingleVC performs any-to-one VC, which is an important component of MediumVC project.

SingleVC performs any-to-one VC, which is an important component of MediumVC project. Here is the official implementation of the paper, MediumVC.

谷下雨 26 Dec 28, 2022
TensorFlow2 Classification Model Zoo playing with TensorFlow2 on the CIFAR-10 dataset.

Training CIFAR-10 with TensorFlow2(TF2) TensorFlow2 Classification Model Zoo. I'm playing with TensorFlow2 on the CIFAR-10 dataset. Architectures LeNe

Chia-Hung Yuan 16 Sep 27, 2022
Diverse graph algorithms implemented using JGraphT library.

# 1. Installing Maven & Pandas First, please install Java (JDK11) and Python 3 if they are not already. Next, make sure that Maven (for importing J

See Woo Lee 3 Dec 17, 2022
Mouse Brain in the Model Zoo

Deep Neural Mouse Brain Modeling This is the repository for the ongoing deep neural mouse modeling project, an attempt to characterize the representat

Colin Conwell 15 Aug 22, 2022
Code and datasets for the paper "Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction" (RA-L, 2021)

Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction This is the code for the paper Combining E

Robotics and Perception Group 69 Dec 26, 2022
BasicRL: easy and fundamental codes for deep reinforcement learning。It is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up.

BasicRL: easy and fundamental codes for deep reinforcement learning BasicRL is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up. It is

RayYoh 12 Apr 28, 2022
An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020

UnpairedSR An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020 turn RCAN(modified) -- xmodel(xilinx

JiaKui Hu 10 Oct 28, 2022
Source-to-Source Debuggable Derivatives in Pure Python

Tangent Tangent is a new, free, and open-source Python library for automatic differentiation. Existing libraries implement automatic differentiation b

Google 2.2k Jan 01, 2023
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo

Kyle Hundman 844 Dec 28, 2022
This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"

Fisher Information Loss This repository contains code that can be used to reproduce the experimental results presented in the paper: Awni Hannun, Chua

Facebook Research 43 Dec 30, 2022
SEJE Pytorch implementation

SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering. Contents Inst

0 Oct 21, 2021
SE3 Pose Interp - Interpolate camera pose or trajectory in SE3, pose interpolation, trajectory interpolation

SE3 Pose Interpolation Pose estimated from SLAM system are always discrete, and

Ran Cheng 4 Dec 15, 2022
🔮 Execution time predictions for deep neural network training iterations across different GPUs.

Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's

Geoffrey Yu 44 Dec 27, 2022