Understanding Google's algorithm and changing your queries to match it rather than what makes sense for a human. Google uses PageRank and some form of latent semantic indexing (LSI) to create centrality for search results. You can return items found by a search, extract the meaningful terms with term frequency inverse document frequency (TF-IDF), create a term/document matrix and remove irrelevant terms or documents. The resulting top terms will return dramatically more pertinent results.

While the above can be automated in software, its not necessary to achieve better results, you just need to start looking for the uncommon but important terms in your return documents instead of a grammatically correct sentence.

E.g. Looking for an instance of arrest records for your new babysitter, Jane Smith... instead of typing "Has Jane Smith been arrested?" You end up with a query like " 'Jane Smith' 'texas' arrest police vehicle report ".

There are more tricks using required, optional, and query fields to help disambiguation of results as well.

Additionally Google allows you to select either target domain (such as only .COM) or schema.org schema to narrow your search further if for example you are looking for education links .EDU only or schema tagged paged might narrow your results tremendously.