Authorship analysis is an important task for different text applications, for example in the field of digital forensic text analysis. Hence, we propose an authorship analysis method that compares the average similarity of a text of unknown authorship with all the text of an author. Using this idea, a text that was not written by an author, would not exceed the average of similarity with known t...

In the present article, we considered two-dimensional steady incompressible Oldroyd-B nanofluid flow past a stretching sheet. Using appropriate similarity variables, the partial differential equations are transformed to ordinary (similarity) equations, which are then solved numerically. The effects of various parameters, namely, Deborah numbers [Formula: see text] and [Formula: see text], Prand...

Clustering is a useful technique that organizes a large quantity of unordered text documents into a small number of meaningful and coherent clusters, thereby providing a basis for intuitive and informative navigation and browsing mechanisms. Text-clustering is to divide a collection of textdocuments into different categories so that documents in the same category describe the same topic such as...

In text mining area, popular methods use the bagof-words models, which represent a document as a vector. These methods ignored the word sequence information, and the good clustering result limited to some special domains. This paper proposes a new similarity measure based on suffix tree model of text documents. It analyzes the word sequence information, and then computes the similarity between ...

In this paper, we propose a new text recognition model based on measuring the visual similarity of text and predicting the content of the unlabeled texts. First a Siamese network is trained with deep supervision on a labeled training dataset. This network projects texts into a similarity manifold. The Deeply Supervised Siamese network learns visual similarity of texts. Then a K-nearest neighbor...