Mining Top-K Rank Frequent Patterns in Data Streams A Tree Based Approach with Ternary Function and Ternary Feature Vector

Authors:
M. S. B. PhridviRaj;C. V. Guru Rao
Affiliations:
Senior Assistant Professor Department of Computer Science & Engineering kakatiya Institute of Technology & Science, Warangal, INDIA;Professor & Head Department of Computer Science & Engineering S.R.Engineering College Hasanparthy, Warangal, INDIA
Venue:
Proceedings of the Second International Conference on Innovative Computing and Cloud Computing
Year:
2013

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Abstract

Data is the primary concern in data mining. Data Stream Mining is gaining a lot of practical significance with the huge online data generated from Sensors, Internet Relay Chats, Twitter, Facebook, Online Bank or ATM Transactions. The primary constraint in finding the frequent patterns in data streams is to perform only one time scan of the data with limited memory and requires less processing time. The concept of dynamically changing data is becoming a key challenge, what we call as data streams. In our present work, the algorithm is based on finding frequent patterns in the data streams using a tree based approach.