Scientific publications has been increasing enormously, with this increase classification of
scientific publications is becoming challenging task. The core objective of this research is to …

Few of the existing document clustering methods can detect or describe document topics
properly, which makes it difficult to conduct clustering based on topics. In this paper, we …

Currently, the dynamic website has increased with more than thousands of documents
associated to a category topic available. Most of the website documents are unstructured …

1.1 Background With the growth of the amount of text information on Internet web pages and
modern applications, in general, interest in the text analysis area has increased to facilitate …

The manipulation of large-scale document data sets often involves the processing of a
wealth of features that correspond with the available terms in the document space. The …

Automatic text categorization has always been an important application and research topic
since the inception of digital documents. Today, text categorization is a necessity due to the …

We propose a document classifier based on principal component analysis (PCA) and one-
class support vector machine (OCSVM), where PCA helps achieve dimensionality reduction …

In this paper, we present a new feature selection method based on document frequencies
and statistical values. We also present a new similarity measure to calculate the degree of …

Document clustering is automatic organization of documents into clusters so that documents
within a cluster have high similarity in comparison to documents in other clusters. It has been …