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WKTD: A Novel Algorithm for Reducing Search Time Using Data Mining Mechanism


Arash Ghorbannia Delavar, Somayeh Zare Harofteh, Majid Feizollahi, Nasim Anisi


Vol. 11  No. 3  pp. 124-129


In this paper we will present an A Novel Algorithm for Reducing Search Time Using Data Mining Mechanism. This method is achieved when we create a threshold detector (TD) by which we may conduct clustering so that in data base accumulation, we may present a new competence function by portioning max and min point which produce specific intervals in the information accumulation. In WKTD algorithm, by evaluating parameters used in data collection in the data base of Iranian Workers Association and Oil Industry Investment Company, the recommended algorithm can be used for searching the abovementioned data bases with a high record of estimated costs which are obtained from data collection. Delays considered in searching banks also have been assessed and sweep time and return time of task search have been calculated using competence function. In order to reduce repetitive data in the data base, we were able to present a new method using the threshold detector which enables us to create repetitive data by clustering. Compared with basic K-Means and WKMSD, the recommended algorithm has a higher performance and dependability and is more reliable than previous algorithms.