NARRE | Neural Attentional Regression with Review-level Explanations | Recommender System library

by chenchongthu Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | NARRE Summary

NARRE is a Python library typically used in Artificial Intelligence, Recommender System, Deep Learning, Tensorflow applications. NARRE has no bugs, it has no vulnerabilities and it has low support. However NARRE build file is not available. You can download it from GitHub.

This is our implementation for the paper:. Author: Chong Chen (cstchenc@163.com).

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Quality

Security

License

Reuse

Support

NARRE has a low active ecosystem.

It has 87 star(s) with 42 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 6 open issues and 7 have been closed. On average issues are closed in 78 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of NARRE is current.

Quality

NARRE has 0 bugs and 0 code smells.

Security

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

NARRE code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NARRE 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

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

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

Installation instructions are not available. Examples and code snippets are available.

NARRE saves you 331 person hours of effort in developing the same functionality from scratch.

It has 795 lines of code, 12 functions and 4 files.

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

Top functions reviewed by kandi - BETA

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

Initialize embedding .
Load training data .
Preprocess data .
Pads sentences to the given u_text .
Run dev step .
Train a single training step .
Build the vocabulary .
Add padding to the review id .
Clean a string .
Build input data .

Get all kandi verified functions for this library.

NARRE Key Features

No Key Features are available at this moment for NARRE.

NARRE Examples and Code Snippets

No Code Snippets are available at this moment for NARRE.

Community Discussions

Trending Discussions on NARRE

Is it possible to retrieve the whole sentence in the JSON generated by the spaCy IOB converter?

QUESTION

Is it possible to retrieve the whole sentence in the JSON generated by the spaCy IOB converter?

Asked 2021-May-03 at 17:42

After following the steps to convert data in IOB format to spaCy compatible JSON; the value "raw": string supposed to represent the sentence appears as "null" in my JSON.

Here is an excerpt from my data (test.iob):

...

ANSWER

Answered 2021-May-03 at 17:42

Because the original corpus in this format doesn't contain whitespace information, you can't generate the original/correct raw sentence, so it's left as null. spacy train will take into account whether there's whitespace information or not while training and evaluating, so it's possible to train with or without raw, or from a mixture of docs with and without raw.

If you are training with spacy, you don't want to convert this data to the format with a text string and character offsets. It will cause problems if you have tokens like l', which will be tokenized incorrectly if there's a following space. You should be able to use spacy train from the JSON format with "ner" tags.

Source https://stackoverflow.com/questions/67372491

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

Vulnerabilities

No vulnerabilities reported

Install NARRE

You can download it from GitHub.
You can use NARRE 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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