A Survey on Mining Frequent Itemsets over Data Streams
نویسندگان
چکیده
منابع مشابه
Mining Frequent Itemsets Over Arbitrary Time Intervals in Data Streams
Mining frequent itemsets over a stream of transactions presents di cult new challenges over traditional mining in static transaction databases. Stream transactions can only be looked at once and streams have a much richer frequent itemset structure due to their inherent temporal nature. We examine a novel data structure, an FP-stream, for maintaining information about itemset frequency historie...
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Frequent pattern mining from data streams is an active research topic in data mining. Existing research efforts often rely on a two-phase framework to discover frequent patterns: (1) using internal data structures to store meta-patterns obtained by scanning the stream data; and (2) re-mining the meta-patterns to finalize and output frequent patterns. The defectiveness of such a two-phase framew...
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The increasing importance of data stream arising in a wide range of advanced applications has led to the extensive study of mining frequent patterns. Mining data streams poses many new challenges amongst which are the one-scan nature, the unbounded memory requirement and the high arrival rate of data streams. In this paper, we propose a new approach for mining itemsets on data stream. Our appro...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2017
ISSN: 0975-8887
DOI: 10.5120/ijca2017916030