8. A system comprising: one or more processors to: convert a portion of a multimedia stream to text; generate a search query from one or more particular terms in a text segment of the text, when generating the search query, the one or more processors are to: generate a weight for each group of terms of one or more groups of terms, each group of terms, of the one or more groups of terms, including respective one or more terms in the text segment, the weight for each group of terms, of the one or more groups of terms, being generated based on: a weight of each term of the respective one or more terms, and a value that is based on whether the term is a noun, each of the respective one or more terms being associated with a same stem, and select the one or more particular terms from one or more particular groups of terms of the one or more groups of terms, the one or more weights generated for each of the one or more particular groups of terms being highest out of the weights generated for the one or more groups of terms; identify, based on the search query, documents relevant to the multimedia stream; calculate a score for a document, of the documents, based on a similarity between the text segment and the document; rank the document relative to another document of the documents based the score; and provide, for presentation, information regarding the ranked document.
9. The system of claim 8 , where, when calculating the score, the one or more processors are to: generate a similarity vector for the text segment, the similarity vector for the text segment being generated based on a frequency of a term of the one or more particular terms in the text segment; generate a similarity vector for the document, the similarity vector for the document being generated based on a frequency of a term in the document; and calculate the score based on the similarity vector for the text segment and the similarity vector for the document.