18. A system to provide search results, the system comprising: first means: to receive a search input from a user and a user identification; and to generate a search result comprising a plurality of search result items based on the user input; and second means: to gather a plurality of profile data; to generate a user profile associated with the user identification using the plurality of profile data, wherein the user profile comprises a plurality of weight values with each weight value of the plurality of weight values associated with a corresponding feature category of a plurality of feature categories, wherein the weight value for each of the feature categories is based on an amount of personalization data of the plurality of profile data associated with the corresponding feature category; to identify a plurality of feature scores for each of the plurality of feature categories; for each feature category, to determine the feature score for each of the plurality of search result items; to determine a total score for each of the plurality of search result items based on the feature scores for each of the plurality of search result items and the weight value for each of the plurality of feature scores; to rank the plurality of search result items based on the total score; and to determine a first feature category of the plurality of feature categories comprising a keyword desirability category, wherein each feature score associated with the keyword desirability category is based on a likelihood that a particular search result is a desired item based on the search input and a set of search results obtained from aggregate data from users who made similar queries.
18. A system to provide search results, the system comprising: first means: to receive a search input from a user and a user identification; and to generate a search result comprising a plurality of search result items based on the user input; and second means: to gather a plurality of profile data; to generate a user profile associated with the user identification using the plurality of profile data, wherein the user profile comprises a plurality of weight values with each weight value of the plurality of weight values associated with a corresponding feature category of a plurality of feature categories, wherein the weight value for each of the feature categories is based on an amount of personalization data of the plurality of profile data associated with the corresponding feature category; to identify a plurality of feature scores for each of the plurality of feature categories; for each feature category, to determine the feature score for each of the plurality of search result items; to determine a total score for each of the plurality of search result items based on the feature scores for each of the plurality of search result items and the weight value for each of the plurality of feature scores; to rank the plurality of search result items based on the total score; and to determine a first feature category of the plurality of feature categories comprising a keyword desirability category, wherein each feature score associated with the keyword desirability category is based on a likelihood that a particular search result is a desired item based on the search input and a set of search results obtained from aggregate data from users who made similar queries. 19. The system of claim 18 wherein a second feature category of the plurality of feature categories comprises a user aspect category, wherein each feature score associated with the user aspect category is based on whether the particular search result is associated with a set of characteristics matching preferred user aspect characteristics from the profile data; and a first weight value of the plurality of weight values associated with a fifth feature category is set to 0 based on an absence of personalization data for the fifth feature category in the plurality of profile data.