1. A method of ranking an electronic advertisement relative to target content on a web page, said method comprising the steps of: extracting, using a computer, a title and keywords from said electronic advertisement and a landing page associated with said electronic advertisement for creating a first set of elements, and keywords from said target content on said web page for creating a second set of elements, said first and second sets of elements comprising a plurality of multi-word expressions; calculating, using a computer, a first content match feature using said first and second set of elements, the content match feature to evaluate how well said electronic advertisement matches said target content on said web page; calculating, using a computer, a second content match feature using said first and second set of elements, said second content match feature comprising a semantic association feature based on a degree of correlation between pairs of said plurality of words; and processing, using a computer, said first content match feature and said second content match feature with a machine learning model to output a relevance score of said electronic advertisement relative to said target content.
1. A method of ranking an electronic advertisement relative to target content on a web page, said method comprising the steps of: extracting, using a computer, a title and keywords from said electronic advertisement and a landing page associated with said electronic advertisement for creating a first set of elements, and keywords from said target content on said web page for creating a second set of elements, said first and second sets of elements comprising a plurality of multi-word expressions; calculating, using a computer, a first content match feature using said first and second set of elements, the content match feature to evaluate how well said electronic advertisement matches said target content on said web page; calculating, using a computer, a second content match feature using said first and second set of elements, said second content match feature comprising a semantic association feature based on a degree of correlation between pairs of said plurality of words; and processing, using a computer, said first content match feature and said second content match feature with a machine learning model to output a relevance score of said electronic advertisement relative to said target content. 8. The method of ranking an electronic advertisement relative to target content as set forth in claim 1 wherein said second content match feature comprises Pearson's Ï‡2.