As key players in innovation and entrepreneurial ecosystems, Higher Education Institutions (HEI) assume a position as catalysts creating disseminating knowledge with repercussions the societal, economic, political environments. In this scenario, HEI are facing need to balance performance of their traditional missions—teaching research—with pursuit performance. This brings awareness pay particul...

Protein structure analysis from DNA sequences is an important and fast growing area in both computeT science and biochemistry. Although interesting approaches have been studied, it is very dificult to capture the characteristics of protein, since even a simple protein are made of more than 100 amino acids, which makes biochemical experiments very dificult to detect functional components. For th...

In this report, we provide a comparative analysis of different techniques for user intent classification towards the task of app recommendation. We analyse the performance of different models and architectures for multi-label classification over a dataset with a relative large number of classes and only a handful examples of each class. We focus, in particular, on memory network architectures, ...

We present the first experiment-based study that explicitly contrasts the three major semantic role labeling frameworks. As a prerequisite, we create a dataset labeled with parallel FrameNet-, PropBank-, and VerbNet-style labels for German. We train a state-of-the-art SRL tool for German for the different annotation styles and provide a comparative analysis across frameworks. We further explore...

Opinion surveys are widely admitted as a valuable source of information which becomes complementary to the information extracted from data by machine learning techniques. This paper focuses on a challenging and still open problem which is related to how to handle properly the inherent uncertainty of human perceptions. Namely, we propose new ways to interpret and analyze fuzzy data coming out fr...

An important limitation of regression-based analysis stems from the assumption of symmetric relationships between variables, which is often violated. To overcome this limitation within IS research, we propose the use of the fuzzy-set qualitative comparative analysis (FsQCA) method. The paper elaborates on the rationale for applying this approach to IS behavioural research and how to tailor FsQC...

During the past two decades, a set of systematic comparative case analysis techniques has been developing at a steady pace. During the last few years especially, the main initial technique, qualitative comparative analysis (QCA), has been complemented by other related methods and techniques. The purpose of this article is to critically assess some main recent developments in this field. QCA and...

This work builds on complexity theory in order to identify different types of learners that use video-based learning (VBL). VBL has great value as an educational tool which has already been identified in various contexts. This study combines learners’ demographics with learners’ experience in a conceptual model to explain the adoption of VBL technologies. We test and validate the proposed model...

A new rough-fuzzy model for pattern classification based on granular computing is described in the present article. In this model, we propose the formulation of class-dependent granules in fuzzy environment. Fuzzy membership functions are used to represent the feature-wise belonging to different classes, thereby producing fuzzy granulation of the feature space. The fuzzy granules thus generated...