1. A computer-implemented method for purchasing an advertisement opportunity based on a knowledge representation, the method comprising: obtaining purchaser-context information associated with at least one purchaser; computing, using at least one processor executing stored program instructions, a value, specific to the at least one purchaser, of an advertisement opportunity associated with at least one advertising word or phrase, the computing comprising: identifying, in a knowledge representation encoded as a data structure, a first concept representing at least a portion of the purchaser-context information, identifying, in the knowledge representation, a second concept with which the at least one advertising word or phrase shares at least one label, determining a semantic relevance between the first concept and the second concept based at least in part on the first and second concepts' relative positions in a topology of the knowledge representation, and computing the value of the advertisement opportunity as a function of the determined semantic relevance between the first and second concepts; comparing the computed value to a purchase price of the advertisement opportunity; and purchasing the advertisement opportunity in response to determining that the computed value exceeds the purchase price.
1. A computer-implemented method for purchasing an advertisement opportunity based on a knowledge representation, the method comprising: obtaining purchaser-context information associated with at least one purchaser; computing, using at least one processor executing stored program instructions, a value, specific to the at least one purchaser, of an advertisement opportunity associated with at least one advertising word or phrase, the computing comprising: identifying, in a knowledge representation encoded as a data structure, a first concept representing at least a portion of the purchaser-context information, identifying, in the knowledge representation, a second concept with which the at least one advertising word or phrase shares at least one label, determining a semantic relevance between the first concept and the second concept based at least in part on the first and second concepts' relative positions in a topology of the knowledge representation, and computing the value of the advertisement opportunity as a function of the determined semantic relevance between the first and second concepts; comparing the computed value to a purchase price of the advertisement opportunity; and purchasing the advertisement opportunity in response to determining that the computed value exceeds the purchase price. 3. The computer-implemented method of claim 1 , wherein the knowledge representation comprises a semantic network.