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:

Data Stream ، Fuzzy Sequential Pattern Mining ، Gap Constraint ، Sliding Window.

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