1. A computer implemented system that facilitates providing specialized content to a user in response to a user query, comprising: a computing device with a processor and a memory, the computing device including: a reference language model pre-generated and created by evaluating two or more previous queries to accumulate: 1) a sample data set that includes a topic, and 2) a respective portion of specialized content extracted from content related to a search result from at least one previous query, the sample data set and the respective portion of specialized content are generated based on a frequency of at least one of a key word or a topic within the lexical property evaluation of the previous queries; an interface component by which a user enters a query and receives returned data associated with at least one search result from a search engine based on the query; a component that creates a query language model that is a set of data generated by evaluating a lexical property of the query received by a computer implemented system or a lexical property of a web search result for the query received by a computer implemented system wherein the query language model is created based upon information gleaned from results from the search engine in response to the user query, the information including at least one of a universal resource locator (URL) associated with a returned web page, a web page title, a portion of web page content, or a result snippet; and an arbitration component that automatically and directly returns the portion of specialized content to the user based upon a determination that a correlation above a threshold of relevance exists between the query language model and the pre-generated reference language model wherein specialized content is content, other than Web pages, that is derived from specialized data feeds and wherein the arbitration component uses a query processing component that identifies whether the query contains two or more terms relevant to at least one of a plurality of specialized content topics associated with the reference language model, such relevancy is utilized for identifying the correlation; the portion of specialized content is inferred from a portion of a previous query that has a pre-defined word frequency in comparison to the received query, the portion of specialized content is identified from the pre-generated reference model; and the portion of specialized content is populated into at least one search result associated with the user's query based upon the correlation being above the threshold.
2. The system of claim 1 , in which the arbitration component comprises: a language model generator that builds the query language model based on a set of search results returned from a search engine in response to the user query, wherein the set of search results is evaluated to identify a topic a majority of the search results relate; at least one reference language model for each sample data set, the sample data set is generated based upon at least one of a previous topical query, a previous non-topical query, or a previous general query; the reference language model is generated based upon aggregating at least one of a lexical property of such previous queries or a word frequency within such previous queries; and a comparison component that identifies and evaluates a similarity between at least one reference language model and the query language model, the similarity is measured by at least one of a cosine similarity or a KL-divergence.