8. A computer-implemented method that facilitates providing specialized content to a user, comprising: operating a processor with a coupled memory; identifying at least one term in a user query as being related to at least one specialized content topic, the specialized content topic is determined based upon a lexical analysis of a plurality of previous queries in which a portion of the specialized content topic is categorized into at least one reference language model; extracting a portion of specialized content from a search result from at least one reference language model, the portion of specialized content is a portion of a previous query result having a pre-defined word frequency in connection with the user query wherein specialized content is content, other than Web pages, that is derived from specialized data feeds; generating a query language model upon receipt of returned search results for a user query, the query language model is generated based upon at least one of a lexical property of the user query or a property of at least one search result; generating the at least one reference language model for each of a plurality of query topics wherein generating the at least one reference language model comprises: analyzing returned results for a plurality of topic-specific queries where topic-specific queries are queries related to a specific topic; analyzing returned results for a plurality of general queries where general queries are queries not related to the specific topic; and weighting words that occur with a higher frequency in the topic-specific queries than in the general queries; comparing the query language model to the at least one reference language model corresponding to the specialized content topic related to a portion of terms in the user query; determining whether a similarity between the query language model and the at least one reference language model is equal to or above a relevance threshold value; and automatically displaying the portion of specialized content from the at least one reference language model with a search result for the user query if the determined similarity is equal to or above the relevance threshold value.
8. A computer-implemented method that facilitates providing specialized content to a user, comprising: operating a processor with a coupled memory; identifying at least one term in a user query as being related to at least one specialized content topic, the specialized content topic is determined based upon a lexical analysis of a plurality of previous queries in which a portion of the specialized content topic is categorized into at least one reference language model; extracting a portion of specialized content from a search result from at least one reference language model, the portion of specialized content is a portion of a previous query result having a pre-defined word frequency in connection with the user query wherein specialized content is content, other than Web pages, that is derived from specialized data feeds; generating a query language model upon receipt of returned search results for a user query, the query language model is generated based upon at least one of a lexical property of the user query or a property of at least one search result; generating the at least one reference language model for each of a plurality of query topics wherein generating the at least one reference language model comprises: analyzing returned results for a plurality of topic-specific queries where topic-specific queries are queries related to a specific topic; analyzing returned results for a plurality of general queries where general queries are queries not related to the specific topic; and weighting words that occur with a higher frequency in the topic-specific queries than in the general queries; comparing the query language model to the at least one reference language model corresponding to the specialized content topic related to a portion of terms in the user query; determining whether a similarity between the query language model and the at least one reference language model is equal to or above a relevance threshold value; and automatically displaying the portion of specialized content from the at least one reference language model with a search result for the user query if the determined similarity is equal to or above the relevance threshold value. 12. The method of claim 8 , further comprising implicitly adjusting the relevance threshold value for a given query topic based at least in part on user query history.