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๐Ÿš€๐Ÿš€ Fetch, parse, categorize, summarize user reviews ๐Ÿš€๐Ÿš€

License: MIT License

Python 65.23% HTML 34.61% Shell 0.15%
user-reviews categorization deep-learning machine-learning sentiment-analysis summarization python hacktoberfest fawkes tensorflow

fawkes's People

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fawkes's Issues

requirements.txt does not have fixed versions

requirements.txt should ideally have fixed versions for the packages listed in it to avoid any breakages in future.
Eg.
A installs B (1.5)
C installs B (3.5)
'A' could possibly break in future because it is incompatible with B (3.5)

Add splunk as a datasource

๐Ÿš€ Feature Proposal

A lot of user reviews may go into splunk. Splunk exposes an API which can directly be used to achieve this.

Motivation

To track those user reviews which go into splunk.

Example

Splunk can now become a data source.

Summarisation of user reviews

Going though a lot of user reviews takes time. Having a summary view of all the issues would be a great feature to have.

Auto clustering of user reviews

Currently fawkes only has classification for user reviews, which requires either static weights if we are using text-match or already labelled data to use the LSTM based classification model.

It would be nice to have an automatic clustering of user reviews to get an initial sense of all the topics within the data set.

The important thing is to have a model which can be saved and reused in the future for further clustering when new user reviews are added to the dataset.

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