A content optimization system includes a content generation module, a content evaluation module, and a rule management module. The content generation module is adapted to generate a content configuration, wherein the content configuration comprises a plurality of content elements and one or more relationships among the plurality of content elements, wherein the one or more relationships are in accordance with a set of rules on content generation. The content evaluation module is adapted to evaluate content performance of a piece of content assembled from the content configuration. The rule management module is adapted to amend the set of rules based on the evaluated content performance.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for optimizing content, comprising: generating, by a processor, two content configurations, each content configuration comprising a plurality of content elements and one or more relationships among the plurality of content elements, the one or more relationships in accordance with a set of rules defining permissible relationships; assembling, by a processing unit, the two content configurations to two pieces of content; conducting an experiment to obtain effectiveness data of the two pieces of content on reaching an optimization objective; and determining relative effectiveness of the two content configurations based on the effectiveness data. 2. The method of claim 1, further comprising: associating the relative higher effectiveness of one content configuration to a relationship that is different in the two content configurations; and generating a rule on the relationship based upon the one content configuration having relative higher effectiveness. 3. The method of claim 1, further comprising: associating the relative higher effectiveness of one content configuration to a relationship that is different in the two content configurations; selecting a rule from the set of rules, the rule related to the relationship; and modifying the rule based upon the one content configuration having relative higher effectiveness. 4. The method of claim 1, further comprising: associating the relative higher effectiveness of one content configuration to a content element that is different in the two content configurations; and generating a rule on the content element based upon the one configuration of the plurality of content elements having relative higher effectiveness. 5. The method of claim 1, further comprising: associating the relative higher effectiveness of one content configuration to a content element that is different in the two content configurations; selecting a rule from the set of rules, the rule related to the content element; modifying the rule based upon the one configuration of content elements having relative higher effectiveness. 6. The method of claim 1, further comprising: generating a rule on visual perception based on the optimization objective; applying a VAM, by a processing unit, to at least one of the two pieces of content to generate a VAM output; and determining if the at least one of the two pieces of content satisfies the rule on visual perception based on the VAM output. 7. The method of claim 1, further comprising: generating a rule based upon at least one of factors comprising inventory data, point-of-sale data, locality, day-part, and trigger data. 8. A content optimization system, comprising: a content generation module content generation module adapted to generate a content configuration, the content configuration comprising a plurality of content elements and one or more relationships among the plurality of content elements, the one or more relationships in accordance with a set of rules on content generation, the content configuration designed with a particular optimization objective; a content evaluation module adapted to evaluate content performance on reaching the particular optimization objective based on data acquired when a piece of content assembled from the content configuration is displayed; and a rule management module adapted to amend the set of rules based on the evaluated content performance. 9. The content optimization system of claim 8, wherein the rule management module is adapted to amend the set of rules by at least one of the steps of adding a rule on a relationship and modifying a rule on a relationship. 10. The content optimization system of claim 8, wherein the set of rules comprises at least one of rules on relationships, rules on content elements, rules on metric adjustments, and rules on visual perception. 11. The content optimization system of claim 8, wherein the rule management module is adapted to amend the set of rules by at least one of the steps of adding a rule on content elements and modifying a rule on content elements. 12. The content optimization system of claim 8, wherein the content configuration further comprises a metric adjustment of a content element, wherein the rule management module is adapted to amend the set of rules by at least one of the steps of adding a rule regarding a metric adjustment of the content element and modifying a rule regarding a metric adjustment of the content element. 13. The content optimization system of claim 8, wherein the evaluated content performance comprises at least one of data indicative of activities at a location where the piece of content is displayed, data indicative of view behavior, and result from a visual attention model. 14. The content optimization system of claim 8, wherein the rule management module is adapted to amend the set of rules by at least one of the steps of adding a rule on visual perception based on the particular optimization objective and modifying a rule on visual perception based on the particular optimization objective. 15. The content optimization system of claim 8, further comprising: a visual attention model (VAM) evaluator adapted to apply a VAM on the assembled piece of content to generate a VAM output and determine if the assembled piece of content satisfies the set of rules based on the VAM output.