8. A computer-implemented system comprising one or more processors configured to: identify a computer-implemented content object to serve as a contextual reference; access a first plurality of values, wherein each of the first plurality of values is based on an inference of a first user's interest level with respect to a topic, wherein each of the interest level inferences is derived from a plurality of behaviors; access a second plurality of values, wherein each of the second plurality of values is based on an inferred degree of relevance to a topic of one or more phrases that are contained in the content object; and generate a recommendation comprising one or more objects for delivery to the first user, wherein the recommendation is generated in accordance with the first plurality of values and the second plurality of values.
8. A computer-implemented system comprising one or more processors configured to: identify a computer-implemented content object to serve as a contextual reference; access a first plurality of values, wherein each of the first plurality of values is based on an inference of a first user's interest level with respect to a topic, wherein each of the interest level inferences is derived from a plurality of behaviors; access a second plurality of values, wherein each of the second plurality of values is based on an inferred degree of relevance to a topic of one or more phrases that are contained in the content object; and generate a recommendation comprising one or more objects for delivery to the first user, wherein the recommendation is generated in accordance with the first plurality of values and the second plurality of values. 16. The system of claim 8 , further comprising a processor configured to: generate the recommendation, wherein the recommendation is generated in accordance with a serendipity tuning level set by the first user.