2026-06-27T08:01:11Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/3101 2021-12-13T05:46:24Z 1582963413512:1596119372420 user-ytu

Efficient Document Clustering System Basedon Probability Distribution ofK-Means(PD K-Means) Model Tin Thu Zar Win Nang Aye Aye Htwe Moe Moe Aye <p>In document clustering system, some documents with the same similarity scores may fall into different clusters instead of same cluster due to calculate similarity distance between pairs of documents based on geometric measurements.&nbsp; To tackle this point, probability distribution of KMeans (PD K-Means) algorithm is proposed. In this system, documents are clustered based on proposed probability distribution equation instead of similarity measure between objects. It can also solve initial centroids problems of K-Means by using Systematic Selection of Initial Centroid (SSIC) approach. So, it not only can generate compact and stable results but also eliminates initial cluster problem of K-Means. According to the experiment, F-measure values increase about 0.28 in 20NewsGroup dataset, 0.26 in R8 and 0.14 in R52 from Reuter21578 datasets. The evaluations demonstrate that the proposed solution outperforms than original method and can be applied for various standard and unsupervised datasets.</p> 2017-10-06 http://hdl.handle.net/20.500.12678/0000003101 https://meral.edu.mm/records/3101