Benchmark Algorithms and Models of Frequent Itemset Mining over Data Streams: Contemporary Affirmation of State of Art

1
V.Sidda Reddy
V.Sidda Reddy
2
Dr.T.V.Rao
Dr.T.V.Rao
3
Dr.A.Govardhan
Dr.A.Govardhan
1 Jawaharlal Nehru Technological University Hyderabad

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Data mining and knowledge discovery is an active research work and getting popular by the day because it can be applied in different type of data like web click streams, sensor networks, stock exchange data and time-series data and so on. Data streams are not devoid of research problems. This is attributed to non-stop data arrival in numerous, swift, varying with time, erratic and unrestricted data field. It is highly important to find the regular prototype in single pass data stream or minor number of passes when making use of limited space of memory. In this survey the review on the final progress in the study of regular model mining in data streams. Mining algorithms are talked about at length and further research directions have been suggested.

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No external funding was declared for this work.

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The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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V.Sidda Reddy. 1970. \u201cBenchmark Algorithms and Models of Frequent Itemset Mining over Data Streams: Contemporary Affirmation of State of Art\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C5): .

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Data mining and knowledge discovery is an active research work and getting popular by the day because it can be applied in different type of data like web click streams, sensor networks, stock exchange data and time-series data and so on. Data streams are not devoid of research problems. This is attributed to non-stop data arrival in numerous, swift, varying with time, erratic and unrestricted data field. It is highly important to find the regular prototype in single pass data stream or minor number of passes when making use of limited space of memory. In this survey the review on the final progress in the study of regular model mining in data streams. Mining algorithms are talked about at length and further research directions have been suggested.

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Benchmark Algorithms and Models of Frequent Itemset Mining over Data Streams: Contemporary Affirmation of State of Art

V.Sidda Reddy
V.Sidda Reddy Jawaharlal Nehru Technological University Hyderabad
Dr.T.V.Rao
Dr.T.V.Rao
Dr.A.Govardhan
Dr.A.Govardhan

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