Document clustering is a significant research issue in information retrieval and text mining. Traditionally, most clustering methods were based on the vector space model which has a few limitations such as high dimensionality and weakness in handling synonymous and polysemous problems. Latent...

The primary goal of an information retrieval system is to retrieve all the documents that are relevant to the user query. Disparities between the vocabulary of the system's authors and that of their users pose difficulties when information is processed without human intervention. Preprocessing...

A new, efficient clustering method for solving the cellular manufacturing problem is presented in this paper. The method uses the part-machine incidence matrix of the manufacturing system to form machine cells, each of which processes a family of parts. By doing so, the system is decomposed into...

Dynamical low-rank approximation is a differential-equation-based approach to efficiently compute low-rank approximations to time-dependent large data matrices or to solutions of large matrix differential equations. We illustrate its use in the following application areas: as an updating...

Latent Semantic Indexing (LSI) is a famous Information Retrieval (IR) technique that tries to overcome the problems of lexical matching using conceptual indexing. LSI is a variant of vector space model and proved to be 30% more effective. Many studies have reported that good retrieval...

This study investigates the state, development and drivers of banking market integration in the member countries of the Southern African Development Community (SADC). A Principal Component Analysis (PCA) of national retail interest rates indicates increasing integration in loan and deposit...