Documentation or Inclusion of other algorithms

[BradKML]

The models and algorithms in https://github.com/boudinfl/pke#implemented-models are similar to Textrank but not sped up by SpaCy, so it might be a good idea to include them in PyTextRank

PS: There are also other non TextRank-esque algorithms to consider when making this assessment:

• RAKE https://github.com/aneesha/RAKE and https://github.com/csurfer/rake-nltk and https://github.com/vgrabovets/multi_rake and https://github.com/chinwuDebug/RAKE_improve
• YAKE https://github.com/LIAAD/yake
• Aho–Corasick algorithm https://github.com/dav009/flash
• RaKUn https://github.com/Parsely/serpextract

[louisguitton]

thanks for bringing our attention to pke !

this issue is similar to #78 for which we have made already great progress with 2 contributions:

• adding PositionRank and BiasedRank
• adding BaseTextRank and BaseTextRankFactory to enable integration of more flavours

Regarding the graph based models of pke, I can see this:

• their TextRank can be achieved with our BaseTextRank(edge_weight=0)
• their SingleRank can be achieved with our BaseTextRank() or BaseTextRank(edge_weight=1.0)
• their PositionRank can be achieved with our PositionRank

the following ones are missing:

• TopicRank paper by (Bougouin et al., 2013)
• TopicalPageRank article by (Sterckx et al., 2015)
• MultipartiteRank article by (Boudin, 2018)

I was not aware of these 3 papers and approaches so thank you.
Do you have experience with them in practice and are they good?
Would you be open to contribute them?

[BradKML]

I am mainly reporting them for notes in Documentation, but if I can I would contribute

Also some extra note: https://github.com/miso-belica/sumy/blob/master/docs/alternatives.md

• Bipartite HITS https://github.com/himanshujindal/Automatic-Text-Summarizer
• LexRank https://github.com/giorgosera/pythia/blob/dev/analysis/summarization/summarization.py https://github.com/kylehg/summarizer
• topic models https://github.com/bobflagg/Topic-Networks
• MEAD http://www.summarization.com/mead/
• Luhn Summ https://github.com/talha1503/Extractive_Text_Summarization/blob/master/luhn_sum.py
• SumBasic https://github.com/talha1503/Extractive_Text_Summarization/blob/master/SumBasic.ipynb

[BradKML]

To reiterate the current algorithms that are not included:

• SumBasic by Nankova et. al. and its Repository in Python
• LexRank by Erkan et. al. and its Repository in Python
• SalianceRank teneva et. al. by and its Reposiroty in Python
• KEA by Witten et. al. and its Repository in Java
• UniKeyPhrase by Wu et. al. and its Repository in Python
• https://github.com/boudinfl/pke#implemented-models
  • TopicRank paper by (Bougouin et al., 2013)
  • TopicalPageRank article by (Sterckx et al., 2015)
  • MultipartiteRank article by (Boudin, 2018)

Looking at

• JAKE https://github.com/xcjackpan/jake
• Crackr https://github.com/anjishnu/Crackr

[ceteri]

Also check the algorithms listed in pke https://github.com/boudinfl/pke which has an excellent range of implementations. FWIW, that library is GPL and not implemented as a spaCy pipeline, so there's some room for algorithm implementations both there (for research) and here (for production deployments).