Mining multimedia data is one of the most important issues in data mining. In this paper, we propose an online one-pass algorithm to mine the set of frequent temporal patterns in online music query streams with a sliding window. An effective bit-sequence representation is used to reduce the processing time and memory needed to slide the windows. Experiments show that the proposed algorithm only needs a half of memory requirement of original music query data, and just scans the data once.
['Hua-Fu Li', 'Chin-Chuan Ho', 'Man-Kwan Shan', 'Suh-Yin Lee']
Online Mining of Recent Music Query Streams