STGCN-POI-Recommendation | Personalized spatio-temporal graph network

by yingtaoluo Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | STGCN-POI-Recommendation Summary

STGCN-POI-Recommendation is a Python library. STGCN-POI-Recommendation has no bugs, it has no vulnerabilities and it has low support. However STGCN-POI-Recommendation build file is not available. You can download it from GitHub.

Update! Another paper of us (STAN: Spatial-Temporal-Attention-Network-for-Next-Location-Recommendation) is accepted to the Web conference 2021. (Repository URL is Data is already uploaded in the repository above. You will be able to run the code with the data smoothly. If not, let me know. Our paper is currently under review of a conference. To follow the double blind review policy, we do not link our paper to this repository nor provide any more information on Github. After acceptance, we shall release the dataset and the paper immediately. :}.

Support

Quality

Security

License

Reuse

Support

STGCN-POI-Recommendation has a low active ecosystem.

It has 12 star(s) with 2 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of STGCN-POI-Recommendation is current.

Quality

STGCN-POI-Recommendation has 0 bugs and 0 code smells.

Security

STGCN-POI-Recommendation has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

STGCN-POI-Recommendation code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

STGCN-POI-Recommendation does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

STGCN-POI-Recommendation releases are not available. You will need to build from source code and install.

STGCN-POI-Recommendation has no build file. You will be need to create the build yourself to build the component from source.

It has 661 lines of code, 42 functions and 6 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed STGCN-POI-Recommendation and discovered the below as its top functions. This is intended to give you an instant insight into STGCN-POI-Recommendation implemented functionality, and help decide if they suit your requirements.

Load traj data
Euclidean distance between two points
Train the model
Convert a NumPy array to a numpy array
Generate a random region
Group a trajectory into a group of locations
Create adjacency list
Calculate the great circle between two points
Compute the layer
Drop out a sparse layer
Perform the forward computation
Concatenate the last item in out_pad
Create data from a csv file
Load the adjacency list from the file
Compute embeddings
Slice a list by index

Get all kandi verified functions for this library.

STGCN-POI-Recommendation Key Features

No Key Features are available at this moment for STGCN-POI-Recommendation.

STGCN-POI-Recommendation Examples and Code Snippets

No Code Snippets are available at this moment for STGCN-POI-Recommendation.

Community Discussions

No Community Discussions are available at this moment for STGCN-POI-Recommendation.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install STGCN-POI-Recommendation

You can download it from GitHub.
You can use STGCN-POI-Recommendation like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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