Analysing Duplicate Data Detection in Hierarchical Structure with Different Aspects
Sahunthala S1, Udhaya Kumar A2, Latha Parthiban3
1Sahunthala S, Assistant Professor in Department of Information Technology at Anand Institute of Higher Technology, India.
2Dr. Udhaya Kumar A, Professor in Department of Master of Computer Applications at the Hindustan Institute of Technology and Science India.
3Dr. Latha Parthiban, Professor in Department of Computer Science at Pondicherry University India.

Manuscript received on 17 April 2019 | Revised Manuscript received on 22 May 2019 | Manuscript published on 30 May 2019 | PP: 2494-2500 | Volume-8 Issue-1, May 2019 | Retrieval Number: A1439058119/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: In a real world, huge amounts of data are processed on the internet with specific application format. Duplicate data becomes a problem when data is being processed in large volumes; it creates degradation in the performance of processing the query in hierarchical structure. In this paper, we present a survey for analyzing the data duplicate detection in the hierarchical structure with different aspects such as attributes, objects, index of file structure and diversity of the structure based on the number of computation. If the computation is increased the performance is decreased when the query is processed. We also propose a technique Binary Similarity Duplicate Detection (BSDD) to improve the performance for processing the query with detection of duplicate data in a hierarchical structure with reduction of number of computations. It produces good result than the existing techniques.
Index Terms: Attribute Diversity Structure, Duplicate Detection, Index Structure, Objects.
Scope of the Article: Data Analytics