Data mining : past present and future - a typical survey on data streams

2016/05/04 by M.S.B. PhridviRaja, PhridviRaja, M. S. B., C. V. Guru Rao +1
Computer Science · #Anomaly Detection Techniques and Applications #Data Stream Mining Techniques #Databases (cs.DB) #FOS: Computer and information sciences #Time Series Analysis and Forecasting

paper · pdf · doi:10.48550/arxiv.1605.01429

openalex publication_date 2016/05/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Data Stream Mining is one of the area gaining lot of practical significance and is progressing at a brisk pace with new methods, methodologies and findings in various applications related to medicine, computer science, bioinformatics and stock market prediction, weather forecast, text, audio and video processing to name a few. Data happens to be the key concern in data mining. With the huge online data generated from several sensors, Internet Relay Chats, Twitter, Face book, Online Bank or ATM Transactions, the concept of dynamically changing data is becoming a key challenge, what we call as data streams. In this paper, we give the algorithm for finding frequent patterns from data streams with a case study and identify the research issues in handling data streams.

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