The exponential growth of documents in the web makes it very hard for researchers to be aware relevant work being done within scientific community. task efficiently retrieving information has therefore become an important research topic. objective this study is test how efficiency text classification changes if different weights are previously assigned sections that compose documents. proposal ...

Vector-space and distributional methods for text document clustering are discussed. Discriminative clustering, a recently proposed method, uses external data to find taskrelevant characteristics of the documents, yet the clustering is defined even with no external data. We introduce a distributional version of discriminative clustering that represents text documents as probability distributions...

Text line extraction from a text document image and segmenting it into isolate words these individual characters are considered as one of the most critical processes in OCR systems development turning searchable electronic representation, this paper presents new approach to analyze Arabic documents, proposed contains four steps, preprocessing, segmentation, word character segmentation. The hori...

Measuring inter-document similarity is one of the most essential steps in text document clustering. Traditional methods rely on representing text documents using the simple Bag-of-Words (BOW) model. A document is an organized structure consisting of various text segments or passages. Such single term analysis of the text treats whole document as a single semantic unit and thus, ignores other se...