Meta-learning tries to improve the learning process by using knowledge about already completed learning tasks. Therefore, features of dataset, so-called meta-features, are used to represent datasets. These meta-features are used to create a model of the learning process. In order to make this model more predictive, sufficient training samples and, thereby, sufficient datasets are required. In t...

A benchmark database for character recognition is an essential part for efficient and robust development. Unfortunately, there is no comprehensive handwritten dataset for Urdu language that would be used to compare the state of the art techniques in the field of optical character recognition. In this paper, we present a new and publically available dataset comprising 600 pages of handwritten Ur...

This article describes the techniques employed in production of a synthetic dataset driver telematics emulated from similar real insurance dataset. The generated has 100,000 policies that included observations regarding driver’s claims experience, together with associated classical risk variables and telematics-related variables. work is aimed to produce resource can be used advance models asse...

Turkish migrants and their descendants are the largest migrant group from a single origin country living in Germany. The German Mikrozensus as a large dataset allows us to distinguish between Turkish migrants who migrated as children (1.5 generation) and those who were born to Turkish parents in Germany (second generation migrants). We compare both groups to German non-migrants. Using event-his...

Virtual communities such as Second Life and Entropia Universe are quickly becoming the next frontier of cybercrime. With GDPs of virtual economies of persistent worlds approaching billions of dollars it is necessary to develop tools for protection of virtual environments similar to those utilized to secure real world’s infrastructure, such as biometrics security systems. The first step in the d...

Clinical decision support based on artificial intelligence (AI) methods has increasingly been employed in medical applications to diagnosis. Developing efficient AI methods, however, depends necessarily the availability of sufficiently large amount data provide reliable results. But, medicine, it is not always possible find sufficient real all pathologies, particularly, for rare diseases. This ...

Question answering (QA) models often rely on large-scale training datasets, which necessitates the development of a data generation framework to reduce cost manual annotations. Although several recent studies have aimed generate synthetic questions with single-span answers, no study has been conducted creation list multiple, non-contiguous spans as answers. To address this gap, we propose LIQUI...