Mining frequent closed structures in stremying melody sequences

Abstract

In this paper, we study the problem of mining frequent closed structures in a continuous, infinite-sized, and fast changing music melody stream. By modeling a music melody as a sequence of chord-sets, we propose an efficient algorithm FCS-stream (Frequent Closed Structures of streaming melody sequences) for incremental mining of frequent closed structures in one scan of the continuous stream of chord-set sequences. An extended prefix-tree structure called TCS-tree (Temporal Closed Structure tree) is developed for storing compact, essential information about the frequent closed structures of the stream. Results from our theoretical analysis and experimental studies with synthetic data show that algorithm FCS-strearn satisfies the main performance requirements, namely, single-pass, bounded memory, and real-time, for data stream mining.