View source for Collaborative filtering

Collaborative filtering refers to information filtering by the community who uses it.

There are different techniques that information providers use, but they're generally some variation on '''people who liked this also liked this'''.  [[Algorithms]] use this [[big data|data]] to calculate what is most likely to be interesting to a user in a given set of circumstances, which raises all sorts of [[privacy]] issues.

Sometimes different approaches are blended with others and with [[Artificial Intelligence]] to marginally increase precision.  For big companies like search engines, social networks and shopping platforms, tiny improvements in [[Personal Recommendations]] (for example) make a massive difference to profits, so there has been a lot of development in the area.

The effectiveness of these approaches is evident in [[Filter bubbles]], where the process tends to very quickly reduce the diversity of users' [[information diet]].

[[Category:Wiki]][[Category:IT]]
Related Pages
Filter bubbles	Related Pages	Tacit Knowledge
Artificial Intelligence	Personal Recommendations	MediaWiki:Common.css
User:Gav	Information diet	Bottom-up
Knowledge web	Red House Wiki:About	Why I think a wiki would be good for the school