%0 Journal Article %A Shakeri, Omid %A Kelarestaghi, Manoochehr %A Eshghi, Farshad %A Ganjtabesh, Ahmad %T Fuzzy Sequential Pattern Mining over Quantitative Streams %J International Journal of Information and Communication Technology Research %V 11 %N 1 %U http://ijict.itrc.ac.ir/article-1-435-en.html %R %D 2019 %K Data Stream, Fuzzy Sequential Pattern Mining, Gap Constraint, Sliding Window, %X Sequential pattern mining is an interesting data mining problem with many real-world applications. Though new applications introduce a new form of data called data stream, no study has been reported on mining sequential patterns from the quantitative data stream. This paper presents a novel algorithm, for mining quantitative streams. The proposed algorithm can mine exact set of fuzzy sequential patterns in sliding window and gap constraints entailing the most recent transactions in a data stream. In addition, the proposed algorithm can also mine non-quantitative or transaction-based sequential patterns over a data stream. Numerical results show the running time and the memory usage of the proposed algorithm in the case of quantitative and customer-transaction-based sequence counting are proportional to the size of the sliding window and gap constraints %> http://ijict.itrc.ac.ir/article-1-435-en.pdf %P 36-44 %& 36 %! %9 Applicable %L A-10-383-1 %+ Electrical & Computer Engineering Dept. Kharazmi University %G eng %@ 2251-6107 %[ 2019