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Semi-supervised clustering has been widely explored in the last years. In this paper, we present HCAC-ML (Hierarchical Confidence-based Active Clustering with Metric Learning), an innovative approach for this task which employs distance metric learning through cluster-level constraints. HCAC-ML is based on the HCAC algorithm, an state-of-the-art algorithm for hierarchical semi-supervised clustering...
Performance assessment of human teaming in complex, real-world contexts is a fundamental challenge for research and training communities alike. We highlight a unique partnership between the cybersecurity training and research communities with the common goal of capturing human team performance. Whether in the context of a training assessment or a research endeavor; both are two sides of the same coin...
A historically important tradition in exegesis, rooted in a number of scriptural passages, considers the Qur'an to be a self-similar text. This claim, while being sharply debated in literature, has never been independently tested. This paper proposes a strategy to measure self-similarity in classical Arabic texts, based on Leven-shtein distance, within the Self-Similar Qur'an (SSQ) project. The significance...
Considering metrics based on finite directed graph, introduced by Etzion and Firer, we characterize the graphs such that every linear code admits a G-canonical decomposition. This decomposition will play an important role in this work, since it will be the main tool to give a sufficient condition for a finite directed graph to satisfy both the MacWilliams Identity and the MacWilliams Extension Property.
The analysis and comparison of open source software can be improved by means of quality models supporting the evaluation of the software systems being compared and the final decision about which of them has to be adopted. Since software quality can mean different things in different scenarios, quality models should be flexible in order to accommodate the needs of different users. Over the years several...
Do case citations reflect the “real” importance of individual judgments for the legal system concerned? This question has long been puzzling empirical legal scholars. Existing research typically studies case citation networks as a whole applying traditional network metrics stemming from graph theory. Those approaches are able to detect globally important cases, but since they do not take time explicitly...
Massive open online courses (MOOCs) have high potential for improving education worldwide, but understanding of student behavior and situations is difficult to achieve in online settings. Network analytics and visualizations can assist instructors with supporting understanding of student behavior as courses unfold. In this work, we perform a visual comparative analysis of two different MOOC courses...
Similarity metric and distance metric are widely used in many research areas and applications. In this paper, for a given similarity metric, we will introduce a family of distance metrics of Minkowski type. We will then show general solutions to construct normalized similarity metric and normalized distance metric from a similarity metric and a distance metric. Applying the general solutions to a...
In this paper, we consider the key dimensions of learning analytics applications in adaptive learning. We then review recent publications on the topic and map them to the dimensions of the reference model. Twenty one peer-reviewed articles are identified and analyzed. The findings of the review suggest that interesting work has been carried out during the last years on the topic. Yet, there is a clear...
Ordinal input variables are common in many supervised and unsupervised machine learning problems. We focus on ordinal classification problems, where the target variable is also categorical and ordinal. In order to represent categorical input variables for measuring distances or applying continuous mapping functions, they have to be transformed to numeric values. This paper evaluates five different...
Network function visualization and software-defined networking allow services consisting of virtual network functions to be designed and implemented with great flexibility by facilitating automatic deployments, migrations, and reconfigurations for services and their components. For extended flexibility, we go beyond seeing services as a fixed chain of functions. We present a YANG model for describing...
In this contribution a process and a way for a standardized documentation are proposed for the creation of gamified and competency-based learning activities. Furthermore the application of the process and its documentation is described by using an exemplary learning activity which was created, implemented and evaluated. The findings indicate, that the use of gamification design elements for learning...
For popular Open Source Software (OSS) projects there are always a large number of worldwide developers who have been glued to making code contributions, while most of these developers play the role of casual contributors due to their very limited code commits (for fixing defects and enhancing features, casually). The frequent turnover of such group of casual developers and the wide variations among...
Trust and reputation are commonly considered critical concepts in open dynamic multi-agent systems, where agents must rely on their peers to achieve their goals. Several computational trust models have been proposed to manage trust in such situation. The diversity of those models makes user confused about which one to choose. Different testbeds were proposed to evaluate trust and reputation systems...
Estimation of data veracity is recognized as one of the grand challenges of big data. Typically, the goal of truth discovery is to determine the veracity of multi-source, conflicting data and return, as outputs, a veracity label and a confidence score for each data value, along with the trustworthiness score of each source claiming it. Although a plethora of methods has been proposed, it is unlikely...
Quality evaluation is a fundamental problem in the field of linguistic description of data. In this work, we analyze the concept of quality and study different approaches to measure quality. Although most of the approaches considered focused on time series data, that are one of the most frequent datasets in real application domains, they can be used for quality assessment of linguistic descriptions...
Computing k-nearest-neighbor graphs constitutes a fundamental operation in a variety of data-mining applications. As a prominent example, user-based collaborative-filtering provides recommendations by identifying the items appreciated by the closest neighbors of a target user. As this kind of applications evolve, they will require KNN algorithms to operate on more and more sensitive data. This has...
In this paper we extend the theory of control of discrete event systems, defined by their trace processes, to their sequential, or steady-state behavior. The control synthesis problem for finite behavior of such processes was first studied by Smedinga. Here we investigate the control synthesis problem for simultaneous control of finite and infinite (sequential) behavior of trace processes. We use...
This paper addresses the issue of detecting violent scenes in Hollywood movies. In this context, we describe the MediaEval 2013 Violent Scene Detection task which proposes a consistent evaluation framework to the research community. 9 participating teams proposed systems for evaluation in 2013, which denotes an increasing interest for the task. In this paper, the 2013 dataset, the annotations process...
We present an analytical framework for modeling a priority-based load balancing scheme in cellular networks based on a new algorithm called direct retry with truncated offloading channel resource pool ($({\rm DR}_{K})$). The model, developed for a baseline case of two cell network, differs in many respects from previous works on load balancing. Foremost, it incorporates the call admission process,...
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