actually i had a similar idea for a keyword-based addressing/search on the web. let's call is keyword naming system, KNS. anyone can define any number of keywords for his website (not neccessarily bound to a dns domain) and these keyword–site-address pairs propagate on the net (like routing protocols, or DHT).
and to prevent spamming the hell out of this system, each user's local KNS client will prefer those sites for a given keyword which are "bookmarked" by the user's peers (more on the closer peers, less on the more distant ones).
this involves some kind of social-netowrking into this system, but don't panic: it is not meant to be a FB, more like a GPG-like web of trust. if your direct "friends" or "peers" or whatever identity which participates in the system (a blog, a yellow pages provider, a local newspaper publisher) visits a site as a result to a keyword and he mark the site appropriative to the keyword (ie. it is not a spam but a legit content for the given keyword according to his opinion), then your KNS client/search engine ranks the site higher. if a friend's friend marks a site this way then your search results still get ranked upper but not that much. and so on: every level more distant the ranking is weighted less.
"bookmarked" is not the best term here, because the users don't save the site to bookmarks or into "Favorites", just marks it appropriative. they might not have incentive to do so, but it can be automated by assuming the user judges a site appropriative for a given keyword by interacting with it, or not going back too soon, etc.
though it is not perfect because one can just stay on a site out of an interest other than the entered keyword. and it raises privacy questions as well: users generally don't want EVERY of their visits to be signaled on the net, however they are often happy to share a fair amount of their keywords/visits with their friend circles. for the remaining set of activities on the web, they may use an other KNS identity (profile/persona) which nobody, or an other set of people follows.