Cluster Tree Based Hybrid Document Similarity Measure

Authors

  • Devi MV PG Student, Department of Computer Science and Engineering, V.S.B. Engineering College, Karur

Keywords:

Dimensionality reduction, semantic analysis, cluster tree, hybrid similarity, term association

Abstract

Cluster tree based hybrid similarity measure is established to measure the hybrid similarity. In cluster tree, the hybrid similarity measure can be calculated for the random data even it may not be the co -occurred and generate different views. Different views of tree can be combined and choose the one which is significant in cost. A method is proposed to combine the multiple views. Multiple views are represented by different distance measures into a single cluster. Comparing the cluster tree based hybrid similarity with the traditional statistical methods it gives the better feasibility for intelligent based search. It helps in improving the dimensionality reduction and semantic analysis.

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Published

2024-02-26

How to Cite

Devi, M. V. (2024). Cluster Tree Based Hybrid Document Similarity Measure. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(01), 494–498. Retrieved from https://ijact.in/index.php/j/article/view/88

Issue

Section

Original Research Article

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