KDD2018_MPCN | KDD 2018 Paper Multi-Pointer Co

by vanzytay Python Version: Current License: GPL-3.0

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

kandi X-RAY | KDD2018_MPCN Summary

KDD2018_MPCN is a Python library. KDD2018_MPCN has no vulnerabilities, it has a Strong Copyleft License and it has low support. However KDD2018_MPCN has 1 bugs and it build file is not available. You can download it from GitHub.

Code for our KDD 2018 Paper "Multi-Pointer Co-Attention Networks for Recommendation"

Support

Quality

Security

License

Reuse

Support

KDD2018_MPCN has a low active ecosystem.

It has 140 star(s) with 54 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 11 have been closed. On average issues are closed in 106 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of KDD2018_MPCN is current.

Quality

KDD2018_MPCN has 1 bugs (0 blocker, 0 critical, 1 major, 0 minor) and 188 code smells.

Security

KDD2018_MPCN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

KDD2018_MPCN code analysis shows 0 unresolved vulnerabilities.

There are 3 security hotspots that need review.

License

KDD2018_MPCN is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

KDD2018_MPCN releases are not available. You will need to build from source code and install.

KDD2018_MPCN has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

KDD2018_MPCN saves you 1578 person hours of effort in developing the same functionality from scratch.

It has 3509 lines of code, 167 functions and 26 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed KDD2018_MPCN and discovered the below as its top functions. This is intended to give you an instant insight into KDD2018_MPCN implemented functionality, and help decide if they suit your requirements.

Build the graph
Compute joint representation
Calculate dual attention
Calculate local attention layer
Build embeddings
Load vectors from a file
Prepare training set for ranking
Compute the pairwise tf - idf features
Train the model
Select test by dev
Prepare a classification evaluation set
Attention layer
Prepare flat data dictionary
Prepare a hierarchical data dictionary
Build a word index from a list of words
Perform intra - attention
Embedding and embeddings
Transformer feedforward layer
Load train and test sets
Print the model stats
Setup tf TensorBoard
Preprocess a dictionary
Convert a sequence of tokens into indices
Write a dictionary to a file
Convert repr of repr to words
Load a set of data

Get all kandi verified functions for this library.

KDD2018_MPCN Key Features

No Key Features are available at this moment for KDD2018_MPCN.

KDD2018_MPCN Examples and Code Snippets

No Code Snippets are available at this moment for KDD2018_MPCN.

Community Discussions

No Community Discussions are available at this moment for KDD2018_MPCN.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install KDD2018_MPCN

Tensorflow 1.7
Python 2.7

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 .

Find more information at: