Aspect-Based-Sentiment-Analysis | 💭 Aspect-Based-Sentiment-Analysis : Transformer | Machine Learning library

by ScalaConsultants Python Version: 2.0.3 License: Apache-2.0

X-Ray Key Features Code Snippets(6)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Aspect-Based-Sentiment-Analysis Summary

Aspect-Based-Sentiment-Analysis is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Bert applications. Aspect-Based-Sentiment-Analysis has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install Aspect-Based-Sentiment-Analysis' or download it from GitHub, PyPI.

The task is to classify the sentiment of potentially long texts for several aspects. The key idea is to build a modern NLP package which supports explanations of model predictions. The approximated decision explanations help you to infer how reliable predictions are. The package is standalone, scalable, and can be freely extended to your needs. We sum up thoughts in the article:. There are over 100 repositories on GitHub around sentiment analysis 1 2 3 4 5 6 7 8 9 . All of them are hard to commercialize and reuse open-source research projects. We clean up this excellent research. Please give a star if you like the project. This is important to keep this project alive.

Support

Quality

Security

License

Reuse

Support

Aspect-Based-Sentiment-Analysis has a low active ecosystem.

It has 433 star(s) with 82 fork(s). There are 13 watchers for this library.

It had no major release in the last 12 months.

There are 33 open issues and 30 have been closed. On average issues are closed in 35 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Aspect-Based-Sentiment-Analysis is 2.0.3

Quality

Aspect-Based-Sentiment-Analysis has 0 bugs and 0 code smells.

Security

Aspect-Based-Sentiment-Analysis has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Aspect-Based-Sentiment-Analysis code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Aspect-Based-Sentiment-Analysis is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Aspect-Based-Sentiment-Analysis releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

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

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Train a Keras classifier
Trains training
Wrap a given step into a strategy
Compute the softmax loss
Run test loop
Run training loop
Display a review
Highlight a token
Highlight a Pattern
Highlight tokens
Display a list of patterns
Escape text
Creates an objective function
Train the classifier

Get all kandi verified functions for this library.

Aspect-Based-Sentiment-Analysis Key Features

No Key Features are available at this moment for Aspect-Based-Sentiment-Analysis.

Aspect-Based-Sentiment-Analysis Examples and Code Snippets

Add punctuation at the end of sentence after regular expression processing: Python

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

txt=re.sub('goo+d+(?=[^a-z])','good',txt) #"goooodddd" to "good"

Spacy Dependency Parsing with Pandas dataframe

Python

Lines of Code : 31

License : Strong Copyleft (CC BY-SA 4.0)

Copy

def find_sentiment(text):
    doc = nlp(text)
    ner_heads = {ent.root.idx: ent for ent in doc.ents}
    rule3_pairs = []
    for token in doc:
        children = token.children
        A = "999999"
        M = "999999"
        add_neg_pf

How can I specify the exact folder IN STREAMLIT for the uploaded file to be saved to?

Python

Lines of Code : 3

License : Strong Copyleft (CC BY-SA 4.0)

Copy

with open(filename, "wb") as f:
    f.write(buf.getbuffer())

How to do sentiment analysis of different topics/aspects from the same text sample

Python

Lines of Code : 26

License : Strong Copyleft (CC BY-SA 4.0)

Copy

>>> from nltk.tokenize import sent_tokenize

>>> sentences = sent_tokenize(review_text)
>>> sentences
[“Nice central hotel.”,
 “Room was great but the staff were rude.”,
 “Very easy to reach from the central stat

Unable to load Sentihood dataset Json file in Python

Python

Lines of Code : 5

License : Strong Copyleft (CC BY-SA 4.0)

Copy

import json
with open("test.json",mode='r') as f:
    d = json.loads(f.read())  # changed this line
    print(d)

Aspect Based Sentiment Analysis using python

Python

Lines of Code : 27

License : Strong Copyleft (CC BY-SA 4.0)

Copy

word_list = [phrase for phrase in a if phrase.count(' ') == 1]

startTime = time.time()

for i in range(1000000):
    word_list = []
    for phrase in comments.noun_phrases:
        if phrase.count(' ') == 1:

Community Discussions

Trending Discussions on Aspect-Based-Sentiment-Analysis

Create a string on the output. The output is a NoneType object

QUESTION

Create a string on the output. The output is a NoneType object

Asked 2021-May-22 at 16:25

I am running Aspect-Based-Sentiment-Analysis. And I get the output. I want to get this output as a string. I spent several hours in googling how to refer to the output and not only to see the output when I run a code. Maybe I don't comprehend something in Python basics and need huge support on that.

The code I am talking about is as follows:

...

ANSWER

Answered 2021-May-22 at 16:23

Looks like the command is just printing the output to stdout instead of acutally returning an object containing the information you are looking for. You may want to try and capture stdout while running the function. The answer to this question should be helpful.

Source https://stackoverflow.com/questions/67651699

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

Vulnerabilities

No vulnerabilities reported

Install Aspect-Based-Sentiment-Analysis

The aim is to classify the sentiments of a text concerning given aspects. We have made several assumptions to make the service more helpful. Namely, the text being processed might be a full-length document, the aspects could contain several words (so may be defined more precisely), and most importantly, the service should provide an approximate explanation of any decision made, therefore, a user will be able to immediately infer the reliability of a prediction. Above is an example of how quickly you can start to benefit from our open-source package. All you need to do is to call the load function which sets up the ready-to-use pipeline nlp. You can explicitly pass the model name you wish to use (a list of available models is below), or a path to your model. In spite of the simplicity of using fine-tune models, we encourage you to build a custom model which reflects your data. The predictions will be more accurate and stable.
You can use the pip:.

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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