Efficient Methods for Rare Sequential Pattern Mining
Lei Y · Jisuanji kexue yu tansuo · 2015
Sequential pattern mining is an important subject of data mining with a wide application range. Previous studies in this field are mostly dedicated to mining frequent sequential patterns. On the contrary, the infrequent sequential patterns, say, rare sequential patterns(RSP), may reveal the uncommon regularities, so the rare sequences may be of higher interests to analysts. This paper defines the problem of mining rare sequential patterns, and proposes two level- wise algorithms for mining the complete set of all rare sequential patterns. Moreover, in order to overcome the problem of combinatorial explosion when mining the full set of rare sequential patterns, this paper proposes a binary search based algorithm to mine only the set of minimal rare sequential patterns(MRSP), which contains the information of all rare sequential patterns. The experimental results show that the proposed algorithms serve as effective solutions to the problem of mining rare sequential patterns.