Abstract: A method for suggesting related queries to a user query using semantic relationships that are present in informational content stored in public domains. Semantic relationships between named entities are discovered and the named entities are extracted. The entities are indexed according to the relationships. When a user query is received that includes one of the entities, query suggestions are returned to the user based on indexed relationships corresponding to the entity named in the user query.

Abstract: An algorithm for selecting audio content including an audio database, a user preference learning routine, and an audio selection routine. The user preference learning routine is capable of explicitly learning by a manual entry made by the user concerning his/her favorite audio selections. The user preference learning routine is capable of implicitly learning by recording the selections made by the user through a preference input. The preference input queries the user whether he/she liked or disliked a particular audio selection. Initially, random selections are provided to the user. If the user does not like the audio selection it is skipped. If the user liked the selection it is recorded. As the user listens or doesn't listen to audio selections, a profile is developed that identifies the user's preferences. The audio selection routine chooses the next audio selection to be played for the user. There are at least two methods of making the audio selection.