Abstract: Techniques for linguistic personalization of messages for targeted campaigns are described. In one or more implementations, dependencies between keywords and modifiers are extracted, from one or more segment-specific texts and a product-specific text, to build language models for the one or more segment specific texts and the product specific text. Modifiers with a desired sentiment are extracted from the product specific text and transformation points are identified in a message skeleton. Then one or more of the extracted modifiers are inserted to modify one or more identified keywords in the message skeleton to create a personalized message for a target segment of the targeted marketing campaign.

Abstract: Techniques for linguistic personalization of messages for targeted campaigns are described. In one or more implementations, dependencies between keywords and modifiers are extracted, from one or more segment-specific texts and a product-specific text, to build language models for the one or more segment specific texts and the product specific text. Modifiers with a desired sentiment are extracted from the product specific text and transformation points are identified in a message skeleton. Then one or more of the extracted modifiers are inserted to modify one or more identified keywords in the message skeleton to create a personalized message for a target segment of the targeted marketing campaign.