Sliding window technique to mine regular frequent patterns in data streams using vertical format

Mining interesting patterns from various domains is essential in data mining and knowledge discovery process. Recently, frequent patterns along with regularity have good reputation in data mining research. A frequent pattern is regular frequent pattern if it occurs at less than or equal to user given maximum regularity threshold. So, in this paper we are introducing a new algorithm RFPDS to mine frequent patterns that occur at regular intervals from high speed data streams with sliding window technique using vertical data format, satisfies downward closure property. Our experiment results show the outperformance of our algorithm in discovering recent regular frequent patterns from a high speed data stream.