Data Mining - Concepts and Techniques.

International Journal of Computer and Applications

Two decades was systematically reviewed on fuzzy MCDM techniques from 1994 to 2014.The database for review was 403 papers from more than 150 high-ranking journals.403 scholarly papers were grouped in four different main fields.Papers were classified based on utilizing, developing and proposing research papers. MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several fuzzy FMCDM tools have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the fuzzy multi decision-making (FMCDM) techniques. This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals (extracted from online databases such as ScienceDirect, Springer, Emerald, Wiley, ProQuest, and Taylor & Francis). According to experts' opinions, these papers were grouped into four main fields: engineering, management and business, science, and technology. Furthermore, these papers were categorized based on authors, publication date, country of origin, methods, tools, and type of research (FMCDM utilizing research, FMCDM developing research, and FMCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, hybrid fuzzy MCDM in the integrated method and fuzzy AHP in the individual section were ranked as the first and second methods in use. Additionally, Taiwan was ranked as the first country that contributed to this survey, and engineering was ranked as the first field that has applied fuzzy DM tools and techniques.

Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014

Multiple criteria decision-making (MCDM) is considered as a complex decision-making (DM) tool involving both quantitative and qualitative factors. In recent years, several MCDM techniques and approaches have been suggested to choosing the optimal probable options. The purpose of this article is to systematically review the applications and methodologies of the MCDM techniques and approaches. This study reviewed a total of 393 articles published from 2000 to 2014 in more than 120 peer reviewed journals (extracted from Web of Science). According to experts’ opinion, these articles were grouped into 15 fields. Furthermore, these articles were categorised based on authors, publication date, name of journals, methods, tools, and type of research (MCDM utilising research, MCDM developing research, and MCDM proposing research). The results of this study indicated that in 2013 scholars have published articles more than in other years. In addition, the analytic hierarchy process (AHP) method in the individual tool...

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Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014

Microsoft has promoted ASP.NET’s new web services more than almost any other part of the.NET Framework. But despite their efforts, confusion is still widespread about what a web service is and, more importantly, what it’s meant to accomplish. This chapter introduces web services and explains their role in Microsoft’s vision of the programmable web. Along the way, you’ll learn about the open standards plumbing that allows web services to work and removes some of the confusion surrounding technical terms like WSDL (Web Service Description Language), SOAP, and UDDI (universal description, discovery, and integration).

Web Services Architecture

Web Service selection is a key component in service-oriented computing. Service-oriented Architectures follow the find-bindexecute paradigm in which service providers register their services in public or private registries, which clients use to locate web services. The QoS based web service selection mechanisms plays an essential role in service-oriented architectures, because most of the applications want to use services that accurately meet their requirements. Currently, the UDDI catalogue supports only primitive matching mechanisms and provides no control over the quality of registered services. We propose a QoS broker based architecture for dynamic web service selection which facilitates the clients to specify the non-functional requirements like QoS along with functional requirements. The paper presents an efficient mechanism for finding the most suitable web service according to the consumer’s requirements.

/pdf/an-efficient-ws-qos-broker-based-architecture-for-web-1g8ztcn138.pdf

An Efficient WS-QoS Broker Based Architecture for Web Services Selection

This paper develops a knowledge based decision support system (KBDSS) that acquires and quantifies the work-related risks on musculoskeletal disorder specifically, shoulder and neck pain (SNP) that is a prevalent pain complaint within the working environment. Quantifying SNP subjective risk factors helps the physician in decision making. The objective involves knowledge acquisition performed through literature analysis, traditional and concept mapping interviews with neurology, orthopedic, psychology and physiotherapy experts to identify risk factors that include mechanical, physical and psychosocial categories. The determination of ranking the relative factor importance has accomplished using analytic hierarchy processing (AHP) analysis. Capturing domain expert (DE) knowledge and quantifying risk factors produce KBDSS.

Knowledge based decision support system to assist work-related risk analysis in musculoskeletal disorder

Web service is a new paradigm of using the Web. One of the fundamental supports of the web service vision is a brokerage system that enables services to be published to a searchable repository and later retrieved by potential users. Automated Web service discovery is a key challenge in Service Oriented Architecture (SOA) research. There exist many web services which exhibit similar functional characteristics. It is imperative to provide service consumers with facilities for discovering required web services according to their nonfunctional aspects like QoS. An important issue arising from Web Service applications is how to conveniently, accurately and efficiently retrieve services from large-scale and expanding service repositories. The QoS based web service discovery play an essential role in SOA because most of the applications want to use services that accurately meet their requirements. We propose the agent-based architecture for dynamic Web service discovery which facilitates the requester to specify his/her QoS requirements along with functional requirements. In this paper, we propose a novel approach for designing and developing an agent-based architecture and its QoS-based matching, ranking and selection algorithm for evaluating web services. The paper presents an optimal approach for finding the most suitable web service according to the consumer's requirements.

An optimal agent-based architecture for dynamic Web service discovery with QoS

In Internet applications, due to the growth of big data with more features, intrusion detection has become a difficult process in terms of computational complexity, storage efficiency and getting optimized solutions of classification through existing sequential computing environment. Using a parallel computing model and a nature inspired feature selection technique, a Hadoop Based Parallel Binary Bat Algorithm method is proposed for efficient feature selection and classification in order to obtain optimized detection rate. The MapReduce programming model of Hadoop improves computational complexity, the Parallel Binary Bat algorithm optimizes the prominent features selection and parallel Naive Bayes provide cost-effective classification. The experimental results show that the proposed methodologies perform competently better than sequential computing approaches on massive data and the computational complexity is significantly reduced for feature selection as well as classification in big data applications.

Hadoop Based Parallel Binary Bat Algorithm for Network Intrusion Detection

Web service technology has gained more important role in developing distributed applications and systems on the Internet. Rapid growth of published Web services makes their discovery more and more difficult. There exist many web services which exhibit similar functional characteristics. It is imperative to provide service consumers with facilities for selecting required web services according to their non-functional characteristics or QoS. The QoS-based web service discovery mechanisms will play an essential role in SOA, as e-Business applications want to use services that most accurately meet their requirements. However, representing and storing the values of QoS attributes are problematic, as the current UDDI was not designed to accommodate these emerging requirements. To solve the problems of storing QoS in UDDI and aggregating QoS values using the tModel approach. The aim is to study these approaches and other existing QoS tModel representation for their efficiency and consistency in service discovery. This paper discusses a broad range of research issues such as web service discovery or web service selection based on QoS in the E-Business domain.

P. Balasubramanie

Papers

An Efficient WS-QoS Broker Based Architecture for Web Services Selection

Knowledge based decision support system to assist work-related risk analysis in musculoskeletal disorder

An optimal agent-based architecture for dynamic Web service discovery with QoS

Hadoop Based Parallel Binary Bat Algorithm for Network Intrusion Detection

Analysis on the Study of QoS-Aware Web Services Discovery