I'm assuming you are referring to this work: Mihalcea, R., & Tarau, P. (2004). Textrank: Bringing order into texts. In Proceedings of EMNLP 2004. Barcelona, Spain.

A Java implementation of the key phrase extraction part (not sentence extraction) is here: https://github.com/ceteri/textrank

See also https://github.com/karchr/icetextsum, which adds sentence extraction to the implementation.

It is some what like page rank algorithm and use the same methodology.  recently many are using graph models to find text rank.

I  think some few of tolls like MatLab and R support.

Hi,

You might want to try DKProKeyphrases: https://code.google.com/p/dkpro-keyphrases/

Here's a link to an example in Java that implements a variant of TextRank: 

https://code.google.com/p/dkpro-keyphrases/source/browse/trunk/de.tudarmstadt.ukp.dkpro.keyphrases.wrappers-gpl/src/main/java/de/tudarmstadt/ukp/dkpro/keyphrases/core/wrapper/tutorial/CooccurrenceGraphExtractorTutorial.java

Unfortunately it is a little bit tricky to get DKPro Keyphrases working. However, once you have it running it provides you with a bunch of powerful computational linguistic algorithms along with DKPro Core and DKPro Similarity.

If you want to try it just send me a message and I can give you detailed installation instructions.

Laura

Hi,

You can also use the Python implementation of text rank algorithm using the link below

https://github.com/davidadamojr/TextRank

However, this work used Levenshtein distance as relation between texts instead of co-occurrence relation used in the original work of Mihalcea et al.

Thushari

I want to ask a thing, how can I use textrank for a turkish text? I tried some exampla, but I didn't take good results by it. is there someone who can help me about  this issue?

you can try using Python libraries like pytldr, sumy or gensim for extractive summarization.

pip install pytldr Code:

https://github.com/pemagrg1/text_summarization/blob/master/various_ways_to_summarize.py

my jgtextrank library is an alternative tool which is a parallelisable and highly customisable implementation.

The opensource library is available via PyPi and can be installed via 'pip install jgtextrank'

If you want detailed view of textrank and how it works in python you can have a look into below link:

https://www.thinkinfi.com/2018/09/automatic-keyword-extraction-using_30.html