TextRank

As long as you have a tokenizer, i.e. you can split words in a sentence, language doesn't matter for some basic techniques. Two examples that easily come to mind: TF-IDF [1] and TextRank [2,3]. These are good to get started, but if you want to know more about the state of the art, searching on Google Scholar for "keyword extraction $language" is your best bet (and maybe "keyword extraction overview", also in Scholar). [1] http://www.joyofdata.de/blog/tf-idf-statistic-keyword-extrac... [2] http://digital.library.unt.edu/ark%3A/67531/metadc30962/m2/1... [3] https://github.com/davidadamojr/TextRank

I don't find any information on what version of Python this works with, any pointers? 2.X 3? How is this different from all the other textrank implementation? Is this more complete? https://github.com/summanlp/textrank https://github.com/davidadamojr/TextRank https://github.com/galsang/PyTextRank rant: I hate how complex the python ecosystem is, there are different versions for language, different packaging systems (this project uses both conda and pip), sometimes you need to install stuff even with OS package manager or install packages from the source. Something really needs to be done for this mess.