Progressive Mining of Sequential Patterns Based on Single Constraint

[...]user needs to analyze data based on specific organizational needs. [...]constraint is used to impose limitation in the mining process. Single constraint checking in PISA utilizes the concept of anti monotonic or monotonic constraint. [...]the number of sequential patterns will decrease, the total execution time of mining process will decrease and as a result, the system scalability will be achieved. Many researches have resulted in scalable algorithms for sequential pattern mining [1-4]. [...]technology on distributed data processing such as MapReduce/Hadoop also contributes in increasing scalability. [...]the mining process could reduce the search space and consider only patterns which are of interest [1]. Progressive mIning of Sequential pAtterns, PISA based on single constraint is the scalable algorithm of our interest, since it is a progressive sequential pattern mininng that searches for sequential patterns which satisfy minimum support and single constraint within certain window length. Since the window length is flexible to be shifted, it makes PISA is flexible in adding or subtracting data in sequence database [1]. Section V contains conclusion of this paper and future research. 2.Related Work Sequential pattern mining is one of the development of frequent itemset mining [14], as well as structured pattern mining, correlation mining, associative classification, and frequent pattern-based clustering. Progressive sequential pattern mining includes incremental sequential pattern mining [2-4]. [...]frequent pattern mining was also developed in distributed systems [18]. Some sequential pattern mining algorithms that conform to user's needs were developed based on existing algorithm such as, (1) SPIRIT (Sequential pattern mining with regular...