RETRACTED ARTICLE: A swarm-optimized tree-based association rule approach for classifying semi-structured data using soft computing approach
Abstract
The semantic and XML in document classification are used to develop XML data based on tree-based document classification method. The document classification plays the main role in the information management and its retrieval of data, which is a learning problem. In a development context, document classification has a major role in many applications, especially in classifying, organizing, searching and representing concisely large information volumes. A swarm-optimized tree-based association rule approach is presented for the classification of semi-structured data with the use of soft computing. To improve document classification, a tree pruning technique to prune weak and infrequent rules and a binary particle swarm optimization (BPSO) method to optimize tree construction are proposed. An optimized tree-based association rule was proposed to improve XML documents classification based on BPSO, and tree pruning technique to prune weak/infrequent rules is presented. The method was evaluated by Reuters dataset. The Reuters dataset is applied for this method. Results show that the new method performs well for precision and recall compared with current methods.
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Publication History
Published: 01 October 2021
Accepted: 02 April 2021
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