Fuzzy Sequential Pattern Mining over Quantitative Streams
سال انتشار: 1397
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 186
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شناسه ملی سند علمی:
JR_ITRC-11-1_005
تاریخ نمایه سازی: 23 بهمن 1399
چکیده مقاله:
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.
کلیدواژه ها:
نویسندگان
Omid Shakeri
Electrical & Computer Engineering Dept. Kharazmi University, Tehran, Iran
Manoochehr Kelarestaghi
Electrical & Computer Engineering Dept. Kharazmi University, Tehran, Iran
Farshad Eshghi
Electrical & Computer Engineering Dept. Kharazmi University, Tehran, Iran
Ahmad Ganjtabesh
Electrical & Computer Engineering Dept. Kharazmi University, Tehran, Iran