Efficient and Effective Duplicate Detection in Hierarchical Data

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Efficient and Effective Duplicate Detection in Hierarchical Data

IEEE Projects 2013 | Final year projects | BE Projects | Abstract: Although there is a long line of work on identifying duplicates in relational data, only a few solutions focus on duplicate detection in more complex hierarchical structures, like XML data. In this paper, we present a novel method for XML duplicate detection, called XMLDup. XMLDup uses a Bayesian network to determine the probability of two XML elements being duplicates, considering not only the information within the elements, but also the way that information is structured. In addition, to improve the efficiency of the network evaluation, a novel pruning strategy, capable of significant gains over the unoptimized version of the algorithm, is presented. Through experiments, we show that our algorithm is able to achieve high precision and recall scores in several data sets. XMLDup is also able to outperform another state-of-the-art duplicate detection solution, both in terms of efficiency and of effectiveness.

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As a part of project you will get below mentioned documentation along with SOURCE CODE,

1). BIBLIOGRAPHY
2). CONCLUSION
3). HARDWARE SOFTWARE SPECIFICATION
4). IMPLEMENTATION
5). INPUT DESIGN &OUTPUT DESIGN
6). INTRODUCTION
7). LITERATURE SURVEY
8). SCREENSHOT
9). SOFTWARE ENVIRONMENT
10). SYSTEM ANALYSIS
11). SYSTEM DESIGN
12). SYSTEM STUDY
13). SYSTEM TESTING

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Efficient and Effective Duplicate Detection in Hierarchical Data

Efficient and Effective Duplicate Detection in Hierarchical Data

Efficient and Effective Duplicate Detection in Hierarchical Data

Technology: DOT NET and DOT NET IEEE PROJECTS.Project Tags: Cloud Computing, Final Year Projects, IEEE 2013 Projects, and KNOWLEDGE AND DATA ENGINEERING-DATA MINING.

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