A Similarity Function with Pruning Strategy for Tree Structured Data

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Provided by: International Journal of Computer Science & Engineering Technology (IJCSET)
Topic: Data Management
Format: PDF
Although several distance or similarity functions for trees have been introduced, their performance is not always satisfactory in different applications. In the base paper the Extended Sub Tree (EST) function, where a new sub tree mapping is proposed. This similarity function is to compare tree structured data by defining a new set of mapping rules where sub trees are mapped rather than nodes. To reduce the time complexity as well as computational complexity of the system, efficient pruning algorithm is proposed. In the proposed system the unnecessary computation is reduced in the tree structured data by using the lossless pruning strategy.
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