[ian0]

In my mind there are two flavours of queries. The first are those which are "ctrl f" in nature, ie I want to query the entire web to find string x. Which are obviously better suited to indexes. The second are more knowledge based in nature. IE I want to find quality information about a certain topic. These benefit from curation, as anyone who has added "stackoverflow" or "reddit" or "wiki" to a google query will know.

So I would start with a curated and crowdsourced first page results for the top x% of these knowledge based queries. With wikipedia like guidelines and moderation to ensure the quality of the sites mentioned is up to scratch coupled with an inbuilt feedback mechanism from people browsing. I think wikipedia has proven that while difficult, a scheme like this is indeed possible.

I also think you can start very niche and play with the results structure. For example, I like motorcycles and after years of browsing I have discovered the best places for reviews and information. Even just this use case could benefit from a better structure of results page and removal of all the spammy sites. The same goes for other niches like cooking & programming languages.

[ian0]

Another interesting one is illustrating "depth" of knowledge in a results page. For example, I type "Sagittarius A*". It would be nice to have the results grouped into depth. From initial general-audience explainer videos on youtube down to arvix results. With current news seperated from general informational content.

This works for a lot of niches. For example motorcycle reviews run from entertaining comparisons down to detailed analysis. Recipies for omelettes run from the basics, through adding interesting ingredients, right through to the art of perfectly preparing a difficult to make french omelette.