Hi! 1. There was a bug in UI, I've checked raw recommendations. "water heating device" has low score. So first 30 recommended items really fits iPhone, next are not so good. Anyway result is good, thank you very much. 2. I've inspected "sessions" of users, really there are people who viewed iphone and heating device. 10 people for last month. 3. I will calculate relative measurment, I didn't calc what is % of these people comparing to others and how they fluence on score result.
*You wrote:* Then once you have that working you can add more actions but only with cross-cooccurrence, adding by weighting* will not work with this type of recommender*, which recommender can work with weights for actions? *About building recommendations using sales.* Sales are less than 1% from item views. You will recommend only stuff people buy. If you recommend what people see you significantly widen range of possible buy actions. People always buy case "XXX" with iphone. You would never recommened them to buy case "YYY". If people watch "XXX" and "YYY" it's reasonable to recommened "YYY". Maybe "YYY" it's more expensive that is why people prefer cheaper "XXX". What's wrong with this assumption? *About our obsessive desire to add weights for actions.* We would like to self-tune our recommendations. If user clicks our recommendation it's a signal for us that items are related. So next time this link should have higher score. What are the approaches to do it? 2014-08-20 7:18 GMT+04:00 Ted Dunning <[email protected]>: > On Tue, Aug 19, 2014 at 12:53 AM, Serega Sheypak <[email protected] > > > wrote: > > > What could be a reason for recommending "Water heat device " to iPhone? > > iPhone is one of the most popular item. There should be a lot of people > > viewing iPhone with "Water heat device "? > > > > What are the numbers? > > How many people got each item? How many people total? How many people got > both? > > What about the same for the iPhone related items? >
