5. A computer readable medium comprising a set of computer instructions implementing a system for determining relevance of an electronic advertisement to a target content, said set of computer instructions for: extracting a set of terms from said electronic advertisement and said target content; calculating a first content match feature using said set of terms, the first content match feature comprising a translation probability feature indicating a probability that one or more terms of the electronic advertisement are related to one or more terms of the target content, wherein the one or more terms of the electronic advertisement do not match the one or more terms of the target content; calculating a second content match feature using said set of terms, said second content match feature comprising a translation proportion feature indicating a proportion of related terms in the electronic advertisement and the target content, the first and second content match features indicating a probability that the electronic advertisement is a translation of the target content; and processing said first content match feature and said second content match feature with a machine learning model to output a relevance score indicating the relevance of the electronic advertisement to the target content, the machine learning model comprising individual weights for the first and second content match features, the machine learning model being trained using said first and second content match features and machine learning techniques.
5. A computer readable medium comprising a set of computer instructions implementing a system for determining relevance of an electronic advertisement to a target content, said set of computer instructions for: extracting a set of terms from said electronic advertisement and said target content; calculating a first content match feature using said set of terms, the first content match feature comprising a translation probability feature indicating a probability that one or more terms of the electronic advertisement are related to one or more terms of the target content, wherein the one or more terms of the electronic advertisement do not match the one or more terms of the target content; calculating a second content match feature using said set of terms, said second content match feature comprising a translation proportion feature indicating a proportion of related terms in the electronic advertisement and the target content, the first and second content match features indicating a probability that the electronic advertisement is a translation of the target content; and processing said first content match feature and said second content match feature with a machine learning model to output a relevance score indicating the relevance of the electronic advertisement to the target content, the machine learning model comprising individual weights for the first and second content match features, the machine learning model being trained using said first and second content match features and machine learning techniques. 6. The computer readable medium of claim 5 , wherein said machine learning model comprises a support vector machine.