XML With Cluster Feature Extraction for Efficient Search

Provided by: International Journal of Emerging Technology and Advanced Engineering (IJETAE)
Topic: Data Management
Format: PDF
Searching is a very tedious process because, the people all be giving the different keywords to the search engine until they land up with the best results. There is no clustering approach is achieved in the existing. Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of features. The FAST algorithm works in two steps. In the first step, features are divided into clusters by using graph-theoretic clustering methods. In the second step, the most representative feature that is strongly related to target classes is selected from each cluster to form a subset of features. Here XML based cluster formation is achieved in order to have space and language competency.

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