When I think of real-time adaptation of indicators, I think of this: http://www.slideshare.net/tdunning/realtime-puppies-and-ponies-evolving-indicator-recommendations-in-realtime
On Fri, Apr 17, 2015 at 6:51 PM, Pat Ferrel <p...@occamsmachete.com> wrote: > I’ve been thinking about Streaming (continuous input) and incremental > coccurrence. > > As interactions stream in from the user it it fairly simple to use > something like Spark streaming to maintain a moving time window for all > input, and an update frequency that recalcs all input currently in the time > window. I’ve done this with the current cooccurrence code but though > streaming, this is not incremental. > > The current data flow goes from interaction input to geometry and user > dictionary reconciliation to A’A, A’B etc. After the multiply the resulting > cooccurrence matrices are LLR weighted/filtered/down-sampled. > > Incremental can mean all sorts of things and may imply different > trade-offs. Did you have anything specific in mind?
