1. A system comprising: a memory to store an index comprising a plurality of brand relationships based on an analysis of a collection of user queries, each of the brand relationships comprising a first brand-category pair of a first brand and a first category, a second brand-category pair of a second brand and a second category, and a recommendation score calculated between the first brand-category pair and the second brand-category pair, the recommendation score of each brand relationship determined from user sessions having queries of both the first brand and first category and the second brand and second category; a processor to implement a recommendation module to provide a recommendation based on an identified brand preference from an activity of a user by querying the index in the memory using the first brand and first category of the identified brand preference to identify the second brand-category pair having a highest recommendation score in the index; and an expansion module to expand a seed set of brands corresponding to a category by analyzing the collection of user queries to determine a new brand to add to the seed set, the analyzing including mining a corpus containing a plurality of user queries by evaluating user queries containing a disjunction of brand terms.
1. A system comprising: a memory to store an index comprising a plurality of brand relationships based on an analysis of a collection of user queries, each of the brand relationships comprising a first brand-category pair of a first brand and a first category, a second brand-category pair of a second brand and a second category, and a recommendation score calculated between the first brand-category pair and the second brand-category pair, the recommendation score of each brand relationship determined from user sessions having queries of both the first brand and first category and the second brand and second category; a processor to implement a recommendation module to provide a recommendation based on an identified brand preference from an activity of a user by querying the index in the memory using the first brand and first category of the identified brand preference to identify the second brand-category pair having a highest recommendation score in the index; and an expansion module to expand a seed set of brands corresponding to a category by analyzing the collection of user queries to determine a new brand to add to the seed set, the analyzing including mining a corpus containing a plurality of user queries by evaluating user queries containing a disjunction of brand terms. 15. The system of claim 1 , wherein the recommendation module is to identify the second brand-category pair based on a user activity used to identify the brand preference.