A taxonomy of program visualization systems

A taxonomy of program visualization systems that is based on a model of program visualization that maps programs to graphical representations is presented. The taxonomy is illustrated with three program visualization systems representative of research trends: Zeus, Tango, and Pavane     

A taxonomy of network computing systems

Rapid advances in networking and microprocessor technologies have led to the emergence of Internet-wide distributed computing systems ranging from simple LAN-based clusters to planetary-scale networks. As these network computing systems evolve by combining the best features of existing systems, differences among NCs are blurring. To address this problem, researchers have proposed formal taxonomies of NC systems. We propose a new taxonomy that is both broad enough to encompass all NC systems and simple enough to be widely used.     

A survey on video content rating: taxonomy,challenges and open issues

Multimedia Tools and Applications - Rating a video based on its content is one of the most important solutions to classify videos for audience age groups. In this regard, Film content rating and TV...     

Evaluation of rating systems

Since the publication of the initial consultative proposal of a new Basel capital accord in June 1999 (and latest proposal from summer 2004) the influence of the proposed changes in bank management has been discussed intensively. Especially, the possibility to forecast insolvencies is one of the most relevant questions in many empirical studies. In this paper, we present an evaluation methodology for quantitative rating systems. As an example, we use the well known logistic regression model in order to demonstrate the evaluation methodology proposed and we discuss the results obtained in detail. Any other method (statistical or artificial intelligence methods, e.g. neural networks, fuzzy logic) can be evaluated in the same manner. As a side effect, the approach proposed might lead to improved forecasting results.     

A taxonomy of political processes in systems development

Significant resources invested in information system development (ISD) are wasted due to political manoeuvres. Prior research on ISD politics has contributed mainly through theoretical development and case studies. This has enhanced understanding of relevant concepts, political tactics and conditions facilitating politics. However, there is limited understanding of the different processes through which politics unfold. This paper uses 89 ISD projects to develop a taxonomy of political processes in ISD. The taxonomy includes three distinct processes: Tug of War, wherein multiple parties strive to gain project control; Obstacle Race, which involves efforts to resist and pursue the project; and Empire Building, wherein the project is used as an instrument to enhance political or resource bases. The taxonomy is explained using the non‐proponents' view of the project and the balance of power between system's proponents and non‐proponents. We also discuss the emergent taxonomy's implications for how politics can be managed and studied.     

A taxonomy and current issues in multidatabase systems

A taxonomy of global information-sharing systems is presented, and the way in which multidatabase systems fit into the spectrum of solutions is discussed. The taxonomy is used as a basis for defining multidatabase systems. Issues associated with multidatabase systems are reviewed. Two major design approaches for multidatabases, global schema systems and multidatabase language systems, are described. Existing multidatabase projects and areas for further research are also discussed     

Towards a taxonomy of intrusion-detection systems

Intrusion-detection systems aim at detecting attacks against computer systems and networks, or against information systems in general, as it is difficult to provide provably secure information systems and maintain them in such a secure state for their entire lifetime and for every utilization. Sometimes, legacy or operational constraints do not even allow a fully secure information system to be realized at all. Therefore, the task of intrusion-detection systems is to monitor the usage of such systems and to detect the apparition of insecure states. They detect attempts and active misuse by legitimate users of the information systems or external parties to abuse their privileges or exploit security vulnerabilities. In this paper, we introduce a taxonomy of intrusion-detection systems that highlights the various aspects of this area. This taxonomy defines families of intrusion-detection systems according to their properties. It is illustrated by numerous examples from past and current projects.     

Container-based cluster orchestration systems: A taxonomy and future directions

Containers, enabling lightweight environment and performance isolation, fast and flexible deployment, and fine-grained resource sharing, have gained popularity in better application management and deployment in addition to hardware virtualization. They are being widely used by organizations to deploy their increasingly diverse workloads derived from modern-day applications such as web services, big data, and internet of things in either proprietary clusters or private and public cloud data centers. This has led to the emergence of container orchestration platforms, which are designed to manage the deployment of containerized applications in large-scale clusters. These systems are capable of running hundreds of thousands of jobs across thousands of machines. To do so efficiently, they must address several important challenges including scalability, fault tolerance and availability, efficient resource utilization, and request throughput maximization among others. This paper studies these management systems and proposes a taxonomy that identifies different mechanisms that can be used to meet the aforementioned challenges. The proposed classification is then applied to various state-of-the-art systems leading to the identification of open research challenges and gaps in the literature intended as future directions for researchers.     

A taxonomy of information systems applications: the benefits' evaluation ladder

One of the prime reasons for the deployment of information technology in organizations is the expectation of a positive return on the investment. But the returns from different types of application vary both in terms of the ability to provide straightforward measurement of the costs and benefits, and in the degree of certainty with which estimates of costs and benefits will be realised. This paper provides a framework for classifying applications in the form of an eight-rung ladder, each rung of which represents a class of application. The way in which applications need to be handled and the methods by which their impact can be evaluated changes from rung to rung. Moving up the ladder increases the complexity of evaluation and the degree of risk and uncertainty, but at the same time also increases the potential returns on the investments. The ladder is different from conventional ‘strategic IT’ frameworks: it is a framework for action as well as understanding; it specifically relates to evaluation; and it does not imply any predetermined or time-based sequence of progress.     

A method for taxonomy development and its application in information systems

A fundamental problem in many disciplines is the classification of objects in a domain of interest into a taxonomy. Developing a taxonomy, however, is a complex process that has not been adequately addressed in the information systems (IS) literature. The purpose of this paper is to present a method for taxonomy development that can be used in IS. First, this paper demonstrates through a comprehensive literature survey that taxonomy development in IS has largely been ad hoc. Then the paper defines the problem of taxonomy development. Next, the paper presents a method for taxonomy development that is based on taxonomy development literature in other disciplines and shows that the method has certain desirable qualities. Finally, the paper demonstrates the efficacy of the method by developing a taxonomy in a domain in IS.     

A study of Taiwan's issuer credit rating systems using support vector machines

By providing credit risk information, credit rating systems benefit most participants in financial markets, including issuers, investors, market regulators and intermediaries. In this paper, we propose an automatic classification model for issuer credit ratings, a type of fundamental credit rating information, by applying the support vector machine (SVM) method. This is a novel classification algorithm that is famous for dealing with high dimension classifications. We also use three new variables: stock market information, financial support by the government, and financial support by major shareholders to enhance the effectiveness of the classification. Previous research has seldom considered these variables. The data period of the input variables used in this study covers three years, while most previous research has only considered one year. We compare our SVM model with the back propagation neural network (BP), a well-known credit rating classification method. Our experiment results show that the SVM classification model performs better than the BP model. The accuracy rate (84.62%) is also higher than previous research.     

A survey and taxonomy of name systems in mobile ad hoc networks

Name systems are one of the main components of each network that delivers services such as name registration and name resolution for network users and applications. On the Internet, DNS is used to provide easy communications and automatic name to address translations, but because of special characteristics of mobile ad hoc networks it cannot be used on the MANETs. Therefore, various special purpose solutions have been designed to provide name services in different types of MANETs. In this paper, we present taxonomy of MANET name systems based on their architecture and specify the operations that each category of name systems should support. We discuss about the properties and capabilities of each kind of name systems and compare the overheads of each scheme. This survey clarifies the advantages and disadvantages of each name system and is of high importance to understand the weakness of existing name systems and designing effective and complete name systems. Finally, we conclude with open research issues.     

A generalized taxonomy of explanations styles for traditional and social recommender systems

Recommender systems usually provide explanations of their recommendations to better help users to choose products, activities or even friends. Up until now, the type of an explanation style was considered in accordance to the recommender system that employed it. This relation was one-to-one, meaning that for each different recommender systems category, there was a different explanation style category. However, this kind of one-to-one correspondence can be considered as over-simplistic and non generalizable. In contrast, we consider three fundamental resources that can be used in an explanation: users, items and features and any combination of them. In this survey, we define (i) the Human style of explanation, which provides explanations based on similar users, (ii) the Item style of explanation, which is based on choices made by a user on similar items and (iii) the Feature style of explanation, which explains the recommendation based on item features rated by the user beforehand. By using any combination of the aforementioned styles we can also define the Hybrid style of explanation. We demonstrate how these styles are put into practice, by presenting recommender systems that employ them. Moreover, since there is inadequate research in the impact of social web in contemporary recommender systems and their explanation styles, we study new emerged social recommender systems i.e. Facebook Connect explanations (HuffPo, Netflix, etc.) and geo-social explanations that combine geographical with social data (Gowalla, Facebook Places, etc.). Finally, we summarize the results of three different user studies, to support that Hybrid is the most effective explanation style, since it incorporates all other styles.     

A taxonomy and survey of grid resource management systems for distributed computing

The resource management system is the central component of distributed network computing systems. There have been many projects focused on network computing that have designed and implemented resource management systems with a variety of architectures and services. In this paper, an abstract model and a comprehensive taxonomy for describing resource management architectures is developed. The taxonomy is used to identify approaches followed in the implementation of existing resource management systems for very large‐scale network computing systems known as Grids. The taxonomy and the survey results are used to identify architectural approaches and issues that have not been fully explored in the research. Copyright © 2001 John Wiley & Sons, Ltd.     

A systematic review and taxonomy of explanations in decision support and recommender systems

With the recent advances in the field of artificial intelligence, an increasing number of decision-making tasks are delegated to software systems. A key requirement for the success and adoption of such systems is that users must trust system choices or even fully automated decisions. To achieve this, explanation facilities have been widely investigated as a means of establishing trust in these systems since the early years of expert systems. With today’s increasingly sophisticated machine learning algorithms, new challenges in the context of explanations, accountability, and trust towards such systems constantly arise. In this work, we systematically review the literature on explanations in advice-giving systems. This is a family of systems that includes recommender systems, which is one of the most successful classes of advice-giving software in practice. We investigate the purposes of explanations as well as how they are generated, presented to users, and evaluated. As a result, we derive a novel comprehensive taxonomy of aspects to be considered when designing explanation facilities for current and future decision support systems. The taxonomy includes a variety of different facets, such as explanation objective, responsiveness, content and presentation. Moreover, we identified several challenges that remain unaddressed so far, for example related to fine-grained issues associated with the presentation of explanations and how explanation facilities are evaluated.     

A taxonomy of standards

Objectivity, Inc., markets an engineering database management system that is an OODBMS. We are committed to the idea that standards are beneficial for all players in the industry. We have played active roles in several standardization efforts, including the CAD Framework Initiative (CFI). This proposal discusses the motivation for a standardization effort, suggests a direction for its development, discusses cooperation with other such efforts, and offers some concrete starting suggestions.