Arabic Text document clustering is an important aspect for providing conjectural navigation
and browsing techniques by organizing massive amounts of data into a small number of …

Text categorization is the task in which documents are classified into one or more of
predefined categories based on their contents. This paper shows that the proposed system …

The use of centroids as prototypes for clustering text documents with the k-means family of
methods is not always the best choice for representing text clusters due to the high …

Image segmentation is a major step in image analysis and processing. Segmentation is
performed through several methods. In this work Niblack's method of segmentation is further …

Document segmentation, the process of dividing a document into coherent and significant
regions, plays a crucial role for diverse applications that require parsing, retrieval, and …

In this paper, we implement a systematic approach to text categorization using latent
semantic indexing (LSI). A novel feature of our approach is that we iteratively refine the LSI …

The TF-IDF term weighting is one of the most successful methods in feature extraction.
Moreover, the highest term frequency (TF) for each document is concerned for feature …

Traditional text document clustering techniques have a threshold value estimation
challenge. In most cases, it is a human decision, and the value should be determined …

This paper describes the methodology adopted to analyze the quality of Membrane filter.
The quality of Membrane filter is estimated by the uniformity of polymer beads which …