Automatic Text Summarization Online

In the previous post Automatic Text Summarization with Python I showed how to use different python libraries for text summarization. Recently I added text summarization modules to online site Online Machine Learning Algorithms. So now you can play with text summarization modules online and select best summary generator. This service is the free tool that allows to run some algorithms without coding or installing software modules.

Below are the steps how to use online text summarizer models of Machine Learning Algorithms tool.

How to use online text summarizer algorithms

1. Access the link Online Machine Learning Algorithms : Online Machine Learning Algorithms tool.
Select text summarization algorithm that you want to run. There is one available with gensim and 3 with sumy python modules. We will use Luhn text summarizer algorithm. The algorithms from gensim and sumy python modules are still widely used in automatic text summarization which is part of the field of natural language processing.

Running online text summarization step1
Running online text summarization step1

2. Input the data that you want to run or click on Load Default Values. Note that you need to enter about 10 sentences at least. It will not work if you enter just few words or just one sentence.

Running online text summarization step2

3. Click Run now.

4. Click View Run Results link.

Running online text summarization -  example of output
Running online text summarization – example of output

5. Click Refresh Page button on this new page , you maybe will need click few times untill data output show up. Usually it takes less than 1 min, but it will depend how much data you need to process.
Scroll to the bottom page to see results.

If you try other text summarizers from this online tool you will see that there are some differences in generated text summaries.

End Notes

In this post, we covered how to use online text summarizer models of Machine Learning Algorithms tool available here You can run online algorithms from gensim and sumy python modules.
Feel free to provide comments or suggestions.