KeyPhrase-Extraction | Source codes of our EMNLP2016 paper Keyphrase Extraction

by fudannlp16 Python Version: Current License: No License

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kandi X-RAY | KeyPhrase-Extraction Summary

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

Source codes of our EMNLP2016 paper Keyphrase Extraction Using Deep Recurrent Neural Networks on Twitter.

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Support

KeyPhrase-Extraction has a low active ecosystem.

It has 40 star(s) with 15 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 1 have been closed. On average issues are closed in 126 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of KeyPhrase-Extraction is current.

Quality

KeyPhrase-Extraction has 0 bugs and 0 code smells.

Security

KeyPhrase-Extraction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

KeyPhrase-Extraction code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

KeyPhrase-Extraction 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

KeyPhrase-Extraction releases are not available. You will need to build from source code and install.

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

KeyPhrase-Extraction saves you 260 person hours of effort in developing the same functionality from scratch.

It has 630 lines of code, 24 functions and 9 files.

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

Top functions reviewed by kandi - BETA

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

Compute the LLEval score
Get keyphrase list
Return a list of contexts for a given window
Return a list with a given window

Get all kandi verified functions for this library.

KeyPhrase-Extraction Key Features

No Key Features are available at this moment for KeyPhrase-Extraction.

KeyPhrase-Extraction Examples and Code Snippets

No Code Snippets are available at this moment for KeyPhrase-Extraction.

Community Discussions

Trending Discussions on KeyPhrase-Extraction

Access server running on docker container

QUESTION

Access server running on docker container

Asked 2020-Oct-07 at 08:08

I am running the StanfordCoreNLP server through my docker container. Now I want to access it through my python script.

Github repo I'm trying to run: https://github.com/swisscom/ai-research-keyphrase-extraction

I ran the command which gave me the following output:

...

ANSWER

Answered 2020-Oct-07 at 08:08

As seen in the log, your service is listening to port 9000 inside the container. However, from outside you need further information to be able to access it. Two pieces of information that you need:

The IP address of the container
The external port that docker exports this 9000 to the outside (by default docker does not export locally open ports).

To get the IP address you need to use docker inspect, for example via

Source https://stackoverflow.com/questions/64238613

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

Vulnerabilities

No vulnerabilities reported

Install KeyPhrase-Extraction

You can download it from GitHub.
You can use KeyPhrase-Extraction 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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