7. An article comprising at least one non-transitory machine-readable storage medium storing instructions to perform multi-phase personalized searching, the instructions upon execution by a computer system causing the computer system to: perform a first search of a corpus of data based on a first query containing a search term, and based on an identifier of a searcher that submitted the first query; rank data items in result data produced by the first search, the ranking according to relevance of the data items to the first search; select a subset of the data items in the result data based on the ranking; select a first subset of terms in data items of the subset of data items; compute correlation weights for corresponding terms in the first subset of terms, where each of the correlation weights is based on correlation of the corresponding term to data items in the subset of data items; select a second subset of the terms in the first subset of terms according to the correlation weights; produce a second query that contains the terms in the second subset of terms; and perform a second search of the corpus of data based on the second query, the second search retrieving data items matching the second subset of terms in the second query from public websites available over an Internet.
7. An article comprising at least one non-transitory machine-readable storage medium storing instructions to perform multi-phase personalized searching, the instructions upon execution by a computer system causing the computer system to: perform a first search of a corpus of data based on a first query containing a search term, and based on an identifier of a searcher that submitted the first query; rank data items in result data produced by the first search, the ranking according to relevance of the data items to the first search; select a subset of the data items in the result data based on the ranking; select a first subset of terms in data items of the subset of data items; compute correlation weights for corresponding terms in the first subset of terms, where each of the correlation weights is based on correlation of the corresponding term to data items in the subset of data items; select a second subset of the terms in the first subset of terms according to the correlation weights; produce a second query that contains the terms in the second subset of terms; and perform a second search of the corpus of data based on the second query, the second search retrieving data items matching the second subset of terms in the second query from public websites available over an Internet. 9. The article of claim 7 , wherein the first query contains the search term entered as a search string by the searcher.