Hello everybody,

in late 2015 I was asking for tech info to document myself for a project about knowledge discovery I was implementing.

I am now happy to have published it and I will be happy to hear for comments to improve utility.

http://nifty.works is a side project I built for brainstorming and help in research of factual knowledge.

I used a data model I co-authored during my first entrepreneurial experience in Italy, and that I also experimented in a mobile app.
Here, I wanted to bring the things forward and make something publicly available over the web!
This project is about experimental interaction to traverse knowledge graphs.

I implemented this functionalities:
- query the context of a topic
- test for suggesting logical paths in between of topics (pathway discovery)
- a gamified version of knowledge networks, as test to engage people in learning (it s still a nerdy prototype I know)
- edit maps (selectively add or remove nodes, available if signed up) 
- sharing maps
- pairing wikipedia articles with entities in the knowledge graph (hyperlinks in article will trigger corresponding topics)

For full-text search, I am now using a very very basic indexing in elasticsearch; you can test a difference with wikipedia indexing by adding test=ab_fts parameter (I don't know which is better).

The nice thing is that I could localise the site for wikipedias not in English, and uncover cultural knowledge strongly related to the language they are written.
I think it may be interesting for there are languages spoken by millions of people but poorly addressed by recommender systems (at my knowledge at least). Thinking about swedish, thai, chinese, dutch, hispanic... to name a few!

I would like to hear from your comments to improve it and help in making a useful service - comments in UX/UI, tech improvements, communication, functionalities as well as opportunities to sustain it (crowd-funding?) are most welcome!

Thank you for time and for your help in answering a lot of questions in the forum!
I hope to give back a bit here.

Cheers,
Luigi