Abstract: Systems and methods of generating and modifying a playlist using contextual information are disclosed. For example, a user may provide an input seed such as a song name or artist name. The input seed is compared to database items and a playlist is generated as a result. In some examples, the contextual information is used to enhance the comparison and to select better content objects for a user's playlist. Meanwhile, in some examples the content objects in the playlist may be arranged in an enhanced order using ranking and/or contextual information.

Abstract: Systems and methods of generating and modifying a playlist using contextual information are disclosed. For example, a user may provide an input seed such as a song name or artist name. The input seed is compared to database items and a playlist is generated as a result. In some examples, the contextual information is used to enhance the comparison and to select better content objects for a user's playlist. Meanwhile, in some examples the content objects in the playlist may be arranged in an enhanced order using ranking and/or contextual information.

Abstract: Systems and methods of generating and modifying a playlist using contextual information are disclosed. For example, a user may provide an input seed such as a song name or artist name. The input seed is compared to database items and a playlist is generated as a result. In some examples, the contextual information is used to enhance the comparison and to select better content objects for a user's playlist. Meanwhile, in some examples the content objects in the playlist may be arranged in an enhanced order using ranking and/or contextual information.

Abstract: Systems and methods of generating and modifying a playlist using contextual information are disclosed. For example, a user may provide an input seed such as a song name or artist name. The input seed is compared to database items and a playlist is generated as a result. In some examples, the contextual information is used to enhance the comparison and to select better content objects for a user's playlist. Meanwhile, in some examples the content objects in the playlist may be arranged in an enhanced order using ranking and/or contextual information.

Abstract: Methods of presenting and providing content to a user are disclosed. For example, a user may provide an input seed such as a song name or artist name. The input seed is compared to database items and a playlist is generated as a result. The playlist has an identifier corresponding to one of the database items. A first graphic element associated with the input seed is displayed. A second graphic element associated with the identifier is displayed. As another example, a plurality of database items are compared and a playlist is generated as a result. The playlist has a first identifier corresponding to a first database item. A first graphic element associated with the first identifier is displayed. A first content object corresponding to the first identifier is provided to the user.

Abstract: Methods of generating a playlist for a user are disclosed. For example, an input seed from the user associated with one or more items in a database is received. The input seed may be a song name or artist name. Characteristics that correspond to the input seed are identified. One or more focus traits based on the characteristics are also identified. Based on the identification of the one or more focus traits, a weighting factor is assigned to at least some of the characteristics. The weighted value of the characteristics that correspond to the input seed and characteristics of items in the database are compared. Based on the comparison, items for the playlist are selected.

Abstract: A method of determining at least one match item corresponding to a source item. A database of multiple items such as songs is created. Each song is also represented by an n-dimensional database vector in which each element corresponding to one of n musical characteristics of the song. An n-dimensional source song vector that corresponds to the musical characteristics of a source song is determined. A Distance between the source song vector and each of database song vector is calculated, each distance being a function of the differences between the n musical characteristics of the source song vector and one of source database song vector. The calculation of the distances may include the application of a weighted factor to the musical characteristics of resulting vector. A match song is selected based on the magnitude of the distance between the source song and each database songs after applying any weighted factors.