sentence2vec | BEAT BASELINE FOR SENTENCE EMBEDDINGS | Natural Language Processing library

by peter3125 Python Version: Current License: Non-SPDX

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

kandi X-RAY | sentence2vec Summary

sentence2vec is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch, Tensorflow, Bert applications. sentence2vec has no bugs, it has no vulnerabilities, it has build file available and it has low support. However sentence2vec has a Non-SPDX License. You can download it from GitHub.

Sentence2vec as described in A SIMPLE BUT TOUGH TO BEAT BASELINE FOR SENTENCE EMBEDDINGS by Sanjeev Arora, Yingyu Liang, Tengyu Ma

Support

Quality

Security

License

Reuse

Support

sentence2vec has a low active ecosystem.

It has 301 star(s) with 72 fork(s). There are 17 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 11 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of sentence2vec is current.

Quality

sentence2vec has no bugs reported.

Security

sentence2vec has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

sentence2vec has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

sentence2vec releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

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

Top functions reviewed by kandi - BETA

kandi has reviewed sentence2vec and discovered the below as its top functions. This is intended to give you an instant insight into sentence2vec implemented functionality, and help decide if they suit your requirements.

Convert a list of Sentences to a vector .
Compute the l2 distance between two vectors .
Initialize the text .
String representation of the word
Return the frequency of a word .
Return the representation of the object .
The number of words in the corpus .

Get all kandi verified functions for this library.

sentence2vec Key Features

No Key Features are available at this moment for sentence2vec.

sentence2vec Examples and Code Snippets

No Code Snippets are available at this moment for sentence2vec.

Community Discussions

Trending Discussions on sentence2vec

Sentence2vec and Word2vec involving stop words and Named Entities

QUESTION

Sentence2vec and Word2vec involving stop words and Named Entities

Asked 2018-Feb-28 at 09:53

I'm working on a NLP project, involving sentence2vec. I'm presuming I would be using pre-trained word embeddings for converting tokens into vectors and then proceeding to sentence embedding.

Since my sentence involves : stop words like can't, won't, aren't etc. which NLTK would reduce to {ca, wo, are} + not.
So I can't reduce them, and I don't want to remove them as stop words since sentences like mentioned below, should have different embedding.

My name is Priyank
My name is not Priyank

Another Important doubt is that how to incorporate Named entities such as the name of a person like Mark K. Hogg in my sentence vector.

...

ANSWER

Answered 2018-Feb-28 at 09:53

you can remove the ones you do not want to be as stop words from this list

Source https://stackoverflow.com/questions/49010792

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

Vulnerabilities

No vulnerabilities reported

Install sentence2vec

You can download it from GitHub.
You can use sentence2vec 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 .

Find more information at: