Content-Based Filtering for Music Recommendation Based on Ubiquitous Computing
Jong‐Hun Kim, Un-Gu Kang, Jung-Hyun Lee · 2007
In music search and recommendation methods used in the present time, a general filtering method that obtains a result by inquiring music information and recommends a music list using users’ profiles is used. However, this filtering method presents a certain difficulty to obtain users’ information according to their circumstances because it only considers users’ static information, such as personal information. In order to solve this problem, this paper defines a type of context information used in music recommendations and develops a new filtering method based on statistics by applying it to a content-based filtering method. In addition, a recommendation system using a content-based filtering method that was implemented by a ubiquitous computing technology was used to support service mobility and distribution processes. Based on the results of the performance evaluation of the system used in this study, it significantly increases not only the satisfaction for the music selection, but also the quality of services.