Empirical Studies in Decision Rule-Based Flexibility Analysis for Complex Systems Design and Management

The technology behind personalization or Web page recommendation has undergone tremendous changes, and several Web-based personalization systems have been proposed in recent years. The main goal of Web personalization is to dynamically recommend Web pages based on online behavior of users. Although personalization can be accomplished in numerous ways, most Web personalization techniques fall into four major categories: decision rule-based filtering, content-based filtering, and collaborative filtering and Web usage mining. Decision rule-based filtering reviews users to obtain user demographics or static profiles, and then lets Web sites manually specify rules based on them. It delivers the appropriate content to a particular user based on the rules. However, it is not particularly useful because it depends on users knowing in advance the content that interests them. Content-based filtering relies on items being similar to what a user has liked previously. Collaborative filtering, also called social or group filtering, is the most successful personalization technology to date. Most successful recommender systems on the Web typically use explicit user ratings of products or preferences to sort user profile information into peer groups. It then tells users what products they might want to buy by combining their personal preferences with those of like-minded individuals. However, collaborative filtering has limited use for a new product that no one has seen or rated, and content-based filtering to obtain user profiles might miss novel or surprising information. Additionally, traditional Web personalization techniques, including collaborative or content-based filtering, have other problems, such as reliance on subject user ratings and static profiles or the inability to capture richer semantic relationships among Web objects. To overcome these shortcomings, the new Web personalization tool, nonintrusive personalization, attempts to increasingly incorporate Web usage mining techniques. Web usage mining can help improve the scalability, accuracy, and flexibility of recommender systems. Thus, Web usage mining can reduce the need for obtaining subjective user ratings or registration-based personal preferences. This chapter provides a survey of Web usage mining approaches.

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Supporting the Complexity of Inquiring Organizations

Inquiring Organizations ◽

10.4018/978-1-59140-309-8.ch006 ◽

2011 ◽

pp. 109-132

Author(s):

Dianne J. Hall ◽

Yi Guo

Keyword(s):

Complex Systems ◽

Multiagent System ◽

Support Systems ◽

Systems Design ◽

Agent Technology ◽

Technological Support ◽

Organization Support

This chapter examines the issue of technological support for inquiring organizations and suggests that the complexity of these organizations is best supported by a technology of equal complexity—that is, by agent technology. Agents and the complex systems in which they are active are ideal for supporting not only the activity of Churchman’s inquirers but also those components necessary to ensure an effective environment. Accordingly, a multiagent system to support inquiring organizations is introduced. By explaining agent technology in simple terms and by defining inquirers and other components as agents working within a multiagent system, this chapter demystifies agent technology, enables researchers to grasp the complexity of inquiring organization support systems, and provides the foundation for inquiring organization support systems design.

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Biometric image enhancement using decision rule based image fusion techniques

10.1117/12.855858 ◽

2010 ◽

Author(s):

G. Mary Amirtha Sagayee ◽

S. Arumugam

Keyword(s):

Image Fusion ◽

Image Enhancement ◽

Decision Rule ◽

Rule Based

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Online decision rule-based method for localization of PD sources in multi sheath grounded single core cables

IEEE Transactions on Dielectrics and Electrical Insulation ◽

10.1109/tdei.2014.004169 ◽

2014 ◽

Vol 21 (5) ◽

pp. 2225-2236 ◽

Cited By ~ 1

Author(s):

Abbas Babaee ◽

S. Mohammad Shahrtash

Keyword(s):

Decision Rule ◽

Rule Based

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Enhancing ‘Fit' of Health Information Systems Design Through Practice Support

Human, Social, and Organizational Aspects of Health Information Systems ◽

10.4018/978-1-59904-792-8.ch003 ◽

2010 ◽

pp. 50-66 ◽

Cited By ~ 2

Author(s):

Craig E. Kuziemsky

Keyword(s):

Information Systems ◽

Severe Pain ◽

Empirical Studies ◽

Systems Design ◽

Healthcare Setting ◽

Design And Implementation ◽

Empirical Level ◽

Computer Based ◽

Information Practice

The design and implementation of healthcare information systems (HIS) is problematic as many HIS projects do not achieve the desired outcomes. There exist a number of theories to enhance our ability to successfully develop HIS. Examples of such theories include ‘fit’ and the sociotechnical approach. However, there are few empirical studies that illustrate how to understand and operationalize such theories at the empirical level needed for HIS design. This chapter introduces a practice support framework that bridges the gap between the theoretical and empirical aspects of HIS design by identifying specific process and information practice supports that need to be considered to actively produce fit of an HIS within a healthcare setting. The chapter also provides an empirical case study of how practice support was used to develop a computer based tool in the domain area of palliative care severe pain management.

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Heuristic algorithm for optimal redundancy allocation in complex systems

Journal of Quality in Maintenance Engineering ◽

10.1108/jqme-01-2018-0003 ◽

2019 ◽

Vol 25 (1) ◽

pp. 54-64 ◽

Cited By ~ 1

Author(s):

Sudhanshu Aggarwal

Keyword(s):

Complex Systems ◽

Heuristic Algorithm ◽

Communication Systems ◽

Heuristic Algorithms ◽

Real Life ◽

Optimal Solution ◽

Systems Design ◽

Computational Time ◽

Coherent System ◽

Content Type

PurposeThe purpose of this paper is to present an efficient heuristic algorithm based on the 3-neighborhood approach. In this paper, search is made from sides of both feasible and infeasible regions to find near-optimal solutions.Design/methodology/approachThe algorithm performs a series of selection and exchange operations in 3-neighborhood to see whether this exchange yields still an improved feasible solution or converges to a near-optimal solution in which case the algorithm stops.FindingsThe proposed algorithm has been tested on complex system structures which have been widely used. The results show that this 3-neighborhood approach not only can obtain various known solutions but also is computationally efficient for various complex systems.Research limitations/implicationsIn general, the proposed heuristic is applicable to any coherent system with no restrictions on constraint functions; however, to enforce convergence, inferior solutions might be included only when they are not being too far from the optimum.Practical implicationsIt is observed that the proposed heuristic is reasonably proficient in terms of various measures of performance and computational time.Social implicationsReliability optimization is very important in real life systems such as computer and communication systems, telecommunications, automobile, nuclear, defense systems, etc. It is an important issue prior to real life systems design.Originality/valueThe utilization of 3-neighborhood strategy seems to be encouraging as it efficiently enforces the convergence to a near-optimal solution; indeed, it attains quality solutions in less computational time in comparison to other existing heuristic algorithms.

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