… text classification performance is in full swing in that domain. In this paper, a cosine
similarity-based … The proposed methodology combines cosine similarity (between a test document …

… Text document classification and clustering is an important … process high dimensional text
documents. Word distribution in … A fuzzy similarity-based approach for multi-label document …

… The scope of this work concentrates on promoting the performance of text clustering and
classification through a new measure along with a detailed comparative analysis for the …

… Inspired by the success of distance-based meta-feature representations in text classification,
in this paper we propose a novel set of new meta-features that tackle some limitations or …

… and subdivision of the classification system. The contribution of this … similarity based on
string is simple and easy to implement. Apart from this, it can also have good results for some text …

… Therefore, the question of how to represent text using a graph is crucial to the graph kernel
approach to similarity-based text classification. Two main challenges in this approach are (1) …

… is to perform product recommendation using textual similarity based Learning model. In this
research … Classification of the text document and finding similar items using text description is …

… [4] proposed a two-channel CNN model to calculate semantic similarity based on lexical …
similarity techniques that are used to measure similarity of the pair of texts and classification …

… LC is utilized to calculate the similarity based on the shortest path connecting the meanings
of the two words and the maximum depth considering the taxonomy in which their meanings …

… algorithms, but also for any similarity-based clustering and classification algorithms. Hence,
they can be used for clustering and classification of all types of text document datasets. …