6. A system for evaluating a plurality of content segments for relevancy to a plurality of different categories, the system comprising: a set of processing units; and a machine readable medium storing: a crawler which when executed by at least one of the processing units searches a network for new content segments on a regular basis and downloads the new content segments; a content segment evaluator which when executed by at least one of the processing units determines whether the new content segments are relevant to each of the plurality of different categories by using content relevance models for the plurality of different categories, wherein at least one of the content relevance models for a particular category is a context-based model comprising (i) a set of groups of word sets, each group of word sets comprising a key word set and a second word set, (ii) scores for the groups of word sets, and (iii) a definition of context that specifies when a second word set is in the context of a key word set, wherein the context-based model determines whether a new content segment is relevant by: identifying each key word set from the context-based model that is in the new content segment; for each identified key word set, associating the key word set and each word set within the context of the key word set in the content segment as a different group of word sets; and aggregating scores for each of the associated groups of word sets to calculate a relevancy score for the new content segment; and a content segment tagger which when executed by at least one of the processing units tags a particular content segment with a particular category and the relevancy score for the category when the content segment is relevant to the category.
6. A system for evaluating a plurality of content segments for relevancy to a plurality of different categories, the system comprising: a set of processing units; and a machine readable medium storing: a crawler which when executed by at least one of the processing units searches a network for new content segments on a regular basis and downloads the new content segments; a content segment evaluator which when executed by at least one of the processing units determines whether the new content segments are relevant to each of the plurality of different categories by using content relevance models for the plurality of different categories, wherein at least one of the content relevance models for a particular category is a context-based model comprising (i) a set of groups of word sets, each group of word sets comprising a key word set and a second word set, (ii) scores for the groups of word sets, and (iii) a definition of context that specifies when a second word set is in the context of a key word set, wherein the context-based model determines whether a new content segment is relevant by: identifying each key word set from the context-based model that is in the new content segment; for each identified key word set, associating the key word set and each word set within the context of the key word set in the content segment as a different group of word sets; and aggregating scores for each of the associated groups of word sets to calculate a relevancy score for the new content segment; and a content segment tagger which when executed by at least one of the processing units tags a particular content segment with a particular category and the relevancy score for the category when the content segment is relevant to the category. 12. The system of claim 6 , wherein the machine readable medium is further for storing a model development application which when executed by at least one of the processing units defines the content relevance models.