This article summarizes the research on computational methods to detect academic
plagiarism by systematically reviewing 239 research papers published between 2013 and …

The deployment of wireless health wearables is increasing in the framework of mobile
health monitoring. The power and processing efficiencies with data compression are key …

The k-means algorithm is a widely used method that starts with an initial partitioning of the
data and then iteratively converges towards the local solution by reducing the Sum of …

This paper presents an Artificial Bee Colony (ABC) optimization based algorithm for co-
clustering of high-dimensional data. The ABC algorithm is used for optimization problems …

This paper presents a new semantic kernel for classification of high-dimensional data in the
framework of Support Vector Machines (SVM). SVMs have gained widespread application …

Mobile healthcare is an emerging technique for clinical applications. It is usually based on
cloud-connected biomedical implants. In this context, a novel solution is presented for the …

Feature selection is critical in reducing the size of data and improving classifier accuracy by
selecting an optimum subset of the overall features. Traditionally, each feature is given a …

Co-clustering refers to the simultaneous clustering of objects and their features. It is used as
a clustering technique when the data exhibit similarities only in a subset of features instead …

The rapid growth in the digital era initiates the need to inculcate and preserve the academic
originality of translated texts. Cross-lingual semantic similarity is concerned with identifying …

This paper presents a preliminary validation of common textual information retrieval
techniques for mapping unstructured software vulnerability information to distinct software …