1. A method comprising: receiving a collection of text-based terms associated with a document; performing a statistical analysis on the text-based terms to identify a distribution and relative frequency of the text-based terms in the document; receiving a listing of multiple themes associated with the document, the listing of multiple themes being derived as a result of performing a semantic analysis of the document; and utilizing the distribution and relative frequency information derived from the statistical analysis to rank the multiple themes.
1. A method comprising: receiving a collection of text-based terms associated with a document; performing a statistical analysis on the text-based terms to identify a distribution and relative frequency of the text-based terms in the document; receiving a listing of multiple themes associated with the document, the listing of multiple themes being derived as a result of performing a semantic analysis of the document; and utilizing the distribution and relative frequency information derived from the statistical analysis to rank the multiple themes. 12. The method as in claim 1 further comprising: utilizing the statistical information to identify a corresponding set of at least one most representative text-based term for each page of multiple pages in the document; and for each of the multiple pages, utilizing the corresponding set of at least one most representative text-based terms to identify a theme associated with a respective page that enables matching of a highly relevant advertisement with the respective page.