[lucamartinetti]

Small experiment of visualization of wikipedia articles as a graph using d3.js.

Articles with more traffic are bigger. I computed the semantic similarity using LSI with python (gensim) You have to scroll down/right a bit!

http://similarityapi.appspot.com/graph/?title=blade%20runner

There is also a JSON api: http://similarityapi.appspot.com/api/v1/?limit=100&title...

All feedback is appreciated:

@lucamartinetti [e-mail]

[3pt14159]

I've had much, much better results with LDA than LSI. Give that a shot if you have a chance, you'll be blown away. Stop word ratios are important, and make the max number of tokens 500,000.

[viscanti]

The JSON api should degrade gracefully if results aren't found. I.E. There should be a JSON message explaining that that item doesn't exist.

[lucamartinetti]

Right! It could use some input checking / normalization too. It expects the title parameter to be lower case now.

[rplnt]

Option to select language version could be a good feature (defaulting to en as now).

[Radim]

how much data did you use for the semantic analysis?

[lucamartinetti]

The whole text of all articles from wikipedia english (then filtered those with more the 1k views last month)