IndexedFCP - An Index Based Approach to Identify Frequent Contiguous Patterns (FCP) in Big Data

The process of identifying the repeated contiguous patterns existing in a Big data environment, especially in a Sequence Database (SDB) is called Frequent Contiguous Patterns (FCP) mining. The existing FCP algorithms repeatedly scan the SDB to find FCP, which requires high time complexity and large storage space. In this paper, an Index based algorithm has been presented which minimizes the scanning time of SDB, while finding FCP in the SDB. We define IndexedFCP() which uses index based technique to divide the SDB into sub SDBs and helps directly to search the required FCP in its possible sub SDBs. FCP algorithms are used in many SDB applications such as finding Motif, Regulatory Regions and internal repeats in genomic SDB, identifying required items in Inventory SDB and finding trading patterns in stack trading etc.