Are there recommendation engines for tourism attractions? For example, if I told the program what kind of tourism attractions I like, and also what kind of price range, and also what I liked or didn't like about certain attractions I'd been to, it'd predict which attractions in a new city I'd be likely to enjoy.

  • There is a host of online resources that try to build community-built databases of local attractions. For example, check this question: travel.stackexchange.com/questions/6872/…
    – MastaBaba
    Commented Aug 23, 2012 at 15:34
  • It seems to me you are on to a good idea. Rate tourist attractions not just on one metric, but on a bunch of metrics, which would make it easy to find similar attractions elsewhere.
    – MastaBaba
    Commented Aug 23, 2012 at 15:35
  • just yesterday I was thinking in that, but for what country do you need this? For USA there are a lot. Commented Aug 23, 2012 at 20:03
  • Heck, I'd use it. I like the idea!
    – Mark Mayo
    Commented Aug 23, 2012 at 21:43
  • TripAdvisor immediately sprang to mind: their site ... their Wikipedia page Commented Aug 24, 2012 at 14:58

1 Answer 1


Apart from forums I tend to google for "What to do in xxxx". This will likely give you results on the first page to websites like tripadvisor (as hippietrail suggested in the comment to your question), lonely planet, timeout and similar.

These websites feature what you are looking for to various degree. In general they feature the ability to select an area of interest and suggest places/attractions based on that, such as shopping, museums, "must visit top list" and so on.

The reason I do not link you directly to tripadvisor or lonely planet is simply because regular search engines has a shot at finding those localized websites. In my experience the large sites are much better and widely used in some areas of the world and less in others, so local might be the way to go.

You should bring your ideas to websites like tripadvisor and make them adapt a more friendly website and up to date search, pattern recognition and match making algorithms.

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