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/5f41b71b-aa6e-4399-9388-b7fc9d352fc7%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
