Hi Alfredo, My goal is to use the features in ES to create a wordcloud as easy as possible. The termvector or significant terms query seem to be the most useful.
A visualization of the 'significant' words is all I'm after. On Thursday, April 23, 2015 at 10:26:14 AM UTC-5, Alfredo Serafini wrote: > > Hi Jeff > > IMHO a wordcloud visualization is simple to construct over facets, so if > you have aggregations which counts how many documents you have for every > term, this is probably the most simple way to construct it. > If you want to use the term vectors it's important to understand what you > want to describe, in particular. > > What do you want to visualize? What do you expect emerging from data? > > Il giorno giovedì 23 aprile 2015 15:08:36 UTC+2, Jeff Fogarty ha scritto: >> >> >> >> I looking to create a wordcloud in Jupyter (IPython Notebook) using >> either python or javascript. I have a collection of Presidential speeches >> from the millercenter.org loading into ES. I'm able to execute a >> termvector query which returns the below; >> >> term >> term_freq >> ttf >> doc_freq >> >> Is termvector the appropriate query for a wordcloud? If so, which >> numerical value should I use? >> >> Thanks for your help. >> >> Jeff >> > -- You received this message because you are subscribed to the Google Groups "elasticsearch" group. To unsubscribe from this group and stop receiving emails from it, send an email to elasticsearch+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/d2857e82-6d79-41b4-8d19-6e3f25ede0e0%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
