In recent years, there has been enormous increase in the amount of digital content available online. As a result, the amount of content downloaded by users has increased. This content includes audio and video content. For example, Apple® iTunes® enables users to legally purchase and download music to personal music devices. Video services exist that allow users to access and download video media. Due to the large amount of content available, searching and filtering technologies have emerged as an important enabler to assist users in navigating large amounts of content to produce and manage subsets of available content. These technologies are desired to allow users to filter content according to the user's desires or interests.
Current filtering technologies can be used to generate content results according to user-defined characteristics or criteria. However, these filtering technologies may be inefficient in sufficiently allowing a user to focus the content results to the user's particular interests or goals. For example, a user may select certain genre tags to generate song results meeting the desired genre. If the results are not sufficiently narrowed to the user's desires or interests, the user may have to change or replace the genre tags to produce new results. The user may have to guess which tag changes or replacements should be made to achieve focused results with no guarantee that more focused results will be produced. The user may have to provide several iterations of different filtering settings or characteristics to finally reach a result set that is sufficiently narrowed to the user's interests. As one can imagine, this can be time consuming and possibly frustrating to a user, especially if the iterations do not provide sufficiently focused results.
Further, the user may not be aware of all available filter settings that can be used to filter content to the desired results. Unknown filter settings may be the ones that would successfully produce the desired focused results. For example, in the iTunes® music classification system, there are over 230 different genre and sub-genre music types. Many users are only familiar with the most popular genre types. However, the most popular types often produce the greatest number of search results and thus provide the least focus. Less commonly known genres may be available to produce the desired focused results.
Thus, a need exists for providing a user the ability to more effectively focus content results to the user's particular desires or interests. The user may be unfamiliar with all available filtering characteristics associated with the content at issue. Thus, the user may not be able to efficiently focus content results without additional suggestions or assistance.