Faceted search is search where the domain being search is filtered by categories or some taxonomy. Individuals become first class objects in Facebook's new Graph Search and (apparently) search is relative to a node in their social graph that represents the Facebook user, other users they are connected with, and data for connected users.

I don't yet have access to Facebook's new Graph Search but I have no reason to doubt that as it evolves both Facebook users and Facebook's customers (i.e., advertisers and other organizations that make money from user data) should be happy with the service.

Google's Knowledge Graph and their search in general are also personalized per user. Once again this is made possible by collecting data on users and monetizing by providing this information to their customers (i.e., once more, advertisers, etc.)

Pardon a plug for the Evernote service (I am a happy paying customer): Evernote serves as private search. Throw everything relavant to my digital life into Evernote, and I can later search "just my stuff." I don't doubt that Evernote somehow also makes money by aggregating user information.

I assume that any 3rd party web service I use is somehow monetizing on data about me. I decide to use 3rd services more for the value they provide since my cynical self assumes the worse about privacy.

Dealing with faceted search and graph databases at Facebook and Google scale is an engineering art form. Fortunately for the rest of us, frameworks/libraries like Solr (faceted search) and Neo4J (a very easy to use graph database) make it straight forward to experiment with and use the same technologies, but admittedly without the advantage of very large data stores.