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Article
Publication date: 19 June 2017

Khai Tan Huynh, Tho Thanh Quan and Thang Hoai Bui

Service-oriented architecture is an emerging software architecture, in which web service (WS) plays a crucial role. In this architecture, the task of WS composition and…

Abstract

Purpose

Service-oriented architecture is an emerging software architecture, in which web service (WS) plays a crucial role. In this architecture, the task of WS composition and verification is required when handling complex requirement of services from users. When the number of WS becomes very huge in practice, the complexity of the composition and verification is also correspondingly high. In this paper, the authors aim to propose a logic-based clustering approach to solve this problem by separating the original repository of WS into clusters. Moreover, they also propose a so-called quality-controlled clustering approach to ensure the quality of generated clusters in a reasonable execution time.

Design/methodology/approach

The approach represents WSs as logical formulas on which the authors conduct the clustering task. They also combine two most popular clustering approaches of hierarchical agglomerative clustering (HAC) and k-means to ensure the quality of generated clusters.

Findings

This logic-based clustering approach really helps to increase the performance of the WS composition and verification significantly. Furthermore, the logic-based approach helps us to maintain the soundness and completeness of the composition solution. Eventually, the quality-controlled strategy can ensure the quality of generated clusters in low complexity time.

Research limitations/implications

The work discussed in this paper is just implemented as a research tool known as WSCOVER. More work is needed to make it a practical and usable system for real life applications.

Originality/value

In this paper, the authors propose a logic-based paradigm to represent and cluster WSs. Moreover, they also propose an approach of quality-controlled clustering which combines and takes advantages of two most popular clustering approaches of HAC and k-means.

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Article
Publication date: 27 November 2018

Luca Mazzola, Patrick Kapahnke and Matthias Klusch

The need to flexibly react to changing demands and to cost-efficiently manage customized production even for lot size of one requires a dynamic and holistic integration of…

Abstract

Purpose

The need to flexibly react to changing demands and to cost-efficiently manage customized production even for lot size of one requires a dynamic and holistic integration of service-based processes within and across enterprises of the value chain. In this context, this paper aims at presenting ODERU, the authors’ novel pragmatic approach for automatically implementing service-based manufacturing processes at design and runtime within a cloud-based elastic manufacturing platform.

Design/methodology/approach

ODERU relies on a set of semantic annotations of business process models encoded into an extension of the business process model and notation (BPMN) 2.0 standard. Leveraging the paradigms of semantic SOA and XaaS, ODERU integrates pattern-based semantic composition of process service plans with QoS-based optimization based on multi-objective constraint optimization problem solving.

Findings

The successful validation of ODERU in two industrial use cases for maintenance process optimization and automotive production in the European project CREMA revealed its usefulness for service-based process optimization in general and for significant cost reductions in maintenance in particular.

Originality/value

ODERU provides a pragmatic and flexible solution to optimal service composition with the following three main advantages: full integration of semantic service selection and composition with QoS-based optimization; executability of the generated optimal process service plans by an execution environment as they include service assignments, data flow (variable bindings) and optimal variable assignments; and support of fast replanning in a single model and plan.

Details

International Journal of Web Information Systems, vol. 14 no. 4
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 27 July 2020

Tal Samuel-Azran and Moran Yarchi

This study examines the impact of gender on Facebook campaign strategies and the reception of these strategies during the 2018 Israeli municipal elections.

Abstract

Purpose

This study examines the impact of gender on Facebook campaign strategies and the reception of these strategies during the 2018 Israeli municipal elections.

Design/methodology/approach

The authors analyzed all the messages posted on 48 politicians' official Facebook pages during the week leading up to the elections. They analyzed messages posted by 152 candidates running for the position of head of a municipality, 68 of whom were women (48 had an active Facebook account), examining the amount of engagement they had created. The authors also analyzed the candidates' use of rhetoric and use of negative campaigning and the engagement it created.

Findings

Analysis of the overall engagement of Facebook users in respect to men versus women politicians showed that men politicians' posts were significantly more engaging in terms of the number of likes and shares they generated, although the multilevel analysis found no significant differences between engagement in the posts of men and women politicians. The Aristotelian rhetoric analysis revealed no significant differences between women and men contenders; however, in line with the role incongruity theory, the engagement analysis found that male candidates' logic-based posts attracted significantly more shares. The negative campaigning analysis found that, contrary to the study’s hypothesis, female candidates posted twice as many messages, attacking their opponents as their men counterparts. However, in line with the hypothesis based on the role incongruity theory, these posts gained significantly less engagement than those of their men counterparts.

Originality/value

The study highlights that female candidates do not conform to their perceived gender role as soft, emotional, and gentle in their social media campaigning. However, in line with role incongruity theory, they were not rewarded for this “unwomanly” behavior because they gained significantly less engagement with their logic-based posts and their attacks against other candidates than their men counterparts. Despite the fact that prior studies have indicated the potential of social networks service (SNS) to empower women leaders, the findings of the study highlight the continued gender discrimination and the validity of role incongruity theory during social media campaigning, particularly at the municipal elections level.

Details

Online Information Review, vol. 44 no. 6
Type: Research Article
ISSN: 1468-4527

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Article
Publication date: 23 July 2019

Meriem Aziez, Saber Benharzallah and Hammadi Bennoui

The purpose of this paper is to address the Internet of Things (IoT) service discovery problem and investigate the existing solutions to tackle this problem in many aspects.

Abstract

Purpose

The purpose of this paper is to address the Internet of Things (IoT) service discovery problem and investigate the existing solutions to tackle this problem in many aspects.

Design/methodology/approach

This paper presents an overview of IoT services aiming at providing a clear understanding about their features because this term is still ambiguous for the IoT service discovery approaches. Besides, a full comparison study of the most representative service discovery approaches in the literature is presented over four perspectives: the IoT information model, the mechanism of IoT service discovery, the adopted architecture and the context awareness. These perspectives allow classifying, comparing and giving a deeper understanding of the existing IoT service discovery solutions.

Findings

This paper presents a new definition and a new classification of IoT services and citation of their features comparing with the traditional Web services. This paper discusses the existing solutions, as well as the main challenges, that face the service discovery issue in the IoT domain. Besides, two classifications of the approaches are adopted on the basis of their service description model and their mechanism of discovery, and a set of requirements that need to be considered when defining an IoT service are proposed.

Originality/value

There are few number works that survey the service discovery approaches in the IoT domain, but none of these surveys discuss the service description models in the IoT or the impact of the context awareness aspect in the service discovery solution. There are also few works that give a comprehensive overview of IoT services to understand their nature to facilitate their description and discovery. This paper fills this gap by performing a full comparison study of multi-category and recent approaches for service discovery in the IoT over many aspects and also by performing a comprehensive study of the IoT service features.

Details

International Journal of Pervasive Computing and Communications, vol. 15 no. 1
Type: Research Article
ISSN: 1742-7371

Keywords

Content available
Article
Publication date: 4 August 2020

Kanak Meena, Devendra K. Tayal, Oscar Castillo and Amita Jain

The scalability of similarity joins is threatened by the unexpected data characteristic of data skewness. This is a pervasive problem in scientific data. Due to skewness…

Abstract

The scalability of similarity joins is threatened by the unexpected data characteristic of data skewness. This is a pervasive problem in scientific data. Due to skewness, the uneven distribution of attributes occurs, and it can cause a severe load imbalance problem. When database join operations are applied to these datasets, skewness occurs exponentially. All the algorithms developed to date for the implementation of database joins are highly skew sensitive. This paper presents a new approach for handling data-skewness in a character- based string similarity join using the MapReduce framework. In the literature, no such work exists to handle data skewness in character-based string similarity join, although work for set based string similarity joins exists. Proposed work has been divided into three stages, and every stage is further divided into mapper and reducer phases, which are dedicated to a specific task. The first stage is dedicated to finding the length of strings from a dataset. For valid candidate pair generation, MR-Pass Join framework has been suggested in the second stage. MRFA concepts are incorporated for string similarity join, which is named as “MRFA-SSJ” (MapReduce Frequency Adaptive – String Similarity Join) in the third stage which is further divided into four MapReduce phases. Hence, MRFA-SSJ has been proposed to handle skewness in the string similarity join. The experiments have been implemented on three different datasets namely: DBLP, Query log and a real dataset of IP addresses & Cookies by deploying Hadoop framework. The proposed algorithm has been compared with three known algorithms and it has been noticed that all these algorithms fail when data is highly skewed, whereas our proposed method handles highly skewed data without any problem. A set-up of the 15-node cluster has been used in this experiment, and we are following the Zipf distribution law for the analysis of skewness factor. Also, a comparison among existing and proposed techniques has been shown. Existing techniques survived till Zipf factor 0.5 whereas the proposed algorithm survives up to Zipf factor 1. Hence the proposed algorithm is skew insensitive and ensures scalability with a reasonable query processing time for string similarity database join. It also ensures the even distribution of attributes.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

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Book part
Publication date: 25 June 2012

Andrea Ordanini and A. Parasuraman

Purpose – The paper develops a conceptual framework for assessing value-creating service ecosystems that contains four core dimensions: medium, meaning, usage, and…

Abstract

Purpose – The paper develops a conceptual framework for assessing value-creating service ecosystems that contains four core dimensions: medium, meaning, usage, and network. Its purpose is to identify and discuss the implications of the changes that occur in these dimensions when exchanges within the ecosystem that have long been mediated by physical products become direct instead.

Methodology/approach – The analysis employs the historical method and is based on a systematic investigation of the evolution of the recorded-music market during the past 150 years.

Findings – The analysis shows that the key dimensions of the recorded-music-service ecosystem evolved only gradually and incrementally during the era of physical formats that were dominant until the mid-1990s. With the advent of “liquid” music, the elements of the service ecosystem changed dramatically, leading to instability and redefining roles and exchange mechanisms in the ecosystem.

Research limitations/implications – The investigation focuses on a single ecosystem (music), and conclusions stemming from it are subject to the assumptions inherent in the historical method. Nevertheless, the paper contributes to knowledge in the Service-Dominant Logic (S-D logic) domain by offering a robust framework and a set of core dimensions that are useful for systematically analyzing the nature and consequences of changes that occur in rapidly evolving service ecosystems.

Practical implications – Apart from direct implications for the music market, the proposed framework can help managers working in other ecosystems to adopt a macro perspective in addressing value-creation issues and to pay particular attention to the underlying dynamics that influence value creation in those ecosystems.

Originality/value of paper – The development of a conceptual framework that adopts a macro-level, market-wide perspective for understanding value creation in service ecosystems is a distinct contribution of the paper, as is the application of the historical method in analyzing such an ecosystem.

Details

Special Issue – Toward a Better Understanding of the Role of Value in Markets and Marketing
Type: Book
ISBN: 978-1-78052-913-4

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Article
Publication date: 6 April 2012

Mohammad Kamal Uddin, Juha Puttonen, Sebastian Scholze, Aleksandra Dvoryanchikova and Jose Luis Martinez Lastra

The purpose of this paper is to present an ontology‐based approach of context‐sensitive computing for the optimization of flexible manufacturing systems (FMS).

Abstract

Purpose

The purpose of this paper is to present an ontology‐based approach of context‐sensitive computing for the optimization of flexible manufacturing systems (FMS).

Design/methodology/approach

A context‐sensitive computing approach is presented, integrated on top of FMS control platform. The approach addresses how to extract manufacturing contexts at source, how to process contextual entities by developing an ontology‐based context model and how to utilize this approach for real time decision making to optimize the key performance indicators (KPIs). A framework for such an optimization support system is proposed. A practical FMS use case within SOA‐based control architecture is considered as an illustrative example and the implementation of the core functionalities to the use case is reported.

Findings

Continuous improvement of the factory can be enhanced utilizing context‐sensitive support applications, which provides an intelligent interface for knowledge acquisition and elicitation. This can be used for improved data analysis and diagnostics, real time feedback control and support for optimization.

Research limitations/implications

The performance of context‐sensitive computing increases with the extraction, modeling and reasoning of as much contexts as possible. However, more computational resources and processing times are associated to this. Hence, the trade‐off should be in between the extent of context processing and the required outcome of the support applications.

Practical implications

This paper includes the practical implications of context‐sensitive applications development in manufacturing, especially in the dynamic operating environment of FMS.

Originality/value

Reported results provide a modular approach of context‐sensitive computing and a practical use case implementation to achieve context awareness in FMS. The results are seen extendable to other manufacturing domains.

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Article
Publication date: 1 June 2005

Nigel Ford

The purpose of this paper is to review recent developments in educational informatics relating to the provision by information systems of pedagogical support to web‐based…

Abstract

Purpose

The purpose of this paper is to review recent developments in educational informatics relating to the provision by information systems of pedagogical support to web‐based learners, and to propose further investigation of the feasibility and potential value of web‐based “conversational” information systems to complement adaptive hypermedia and information retrieval systems.

Design/methodology/approach

The potential of Pask's conversation theory is considered as a potentially useful framework for the development of information systems capable of providing pedagogical support for web‐based learners, complementary to that provided by existing computer‐assisted learning and adaptive hypermedia systems. The potential role and application of entailment meshes are reviewed in relation to other forms of knowledge representation including classifications, semantic networks, ontologies and representations based on knowledge space theory.

Findings

Concludes that conversation theory could be a useful framework to support the development of web‐based “conversational” information that would complement aspects of computer‐assisted learning, adaptive hypermedia and information retrieval systems. The entailment mesh knowledge representation associated with conversation theory provides the potential for providing particularly rich pedagogical support by virtue of its properties of cyclicity, consistency and connectivity, designed to support deep and enduring levels of understanding.

Research limitations/implications

Although based on a considerable body of theoretical and empirical work relating to conversation theory, the paper remains speculative in that the gap is still great between, on the one hand, what has so far been achieved and, on the other, the practical realisation of its potential to enhance web‐based learning. Much work remains to be done in terms of exploring the extent to which procedures developed and benefits found in relatively small‐scale experimental contexts can effectively be scaled to yield enhanced support for “real world” learning‐related information behaviour.

Originality/value

The ideas of Pask, discussed in this paper, are capable of guiding the structuring of information according to parameters designed to facilitate deep and enduring understanding via interactive “conversational” engagement between the conceptual structures of information source authors and learners. If one can scale Pask's work to “real world” learning‐related information behaviour, one can increase the range of web‐based information systems and services capable of providing pedagogical support to web‐based learners.

Details

Journal of Documentation, vol. 61 no. 3
Type: Research Article
ISSN: 0022-0418

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Article
Publication date: 30 January 2019

Efendi Nasibov, Murat Demir and Alper Vahaplar

Beside the development of technology and accessibility, ease of use, ability to reach various products and compare many products at the same time make online shopping even…

Abstract

Purpose

Beside the development of technology and accessibility, ease of use, ability to reach various products and compare many products at the same time make online shopping even more popular. Despite the great advantages provided by online shopping for either consumers or retailers, there are certain issues that must be solved to improve online shopping advantages. Finding right size is one of the biggest barriers against apparel online retailing. Since the use of apparels is directly related with fitting, choosing right size is becoming more critical for retailers and consumers. The purpose of this paper is to contribute to the solution of the problem.

Design/methodology/approach

For the study, the specific size measurements of male shirts (collar, shoulder, chest, waist, arm length in cm) from four different sizes (small, medium, large, x-large) and from eight different brands were collected and stored in a database. Totally, weight, height and body measurements (collar, shoulder, chest, waist and arm length in cm) of 80 male candidates, between the ages of 18 and 35, were measured individually. These data were then used for experiments.

Findings

Any product with known measurements can be compared with users’ body measurement based on fuzzy logic rule and the best-fitted size can be selected for users. Similarly, using the proposed web design, users are able to see desired products on users with similar body type.

Originality/value

In this study, a new mathematical method based on fuzzy relations for apparel size finder is proposed. Beside, this method can group users based on body measurements in order to find people with similar size.

Details

International Journal of Clothing Science and Technology, vol. 31 no. 2
Type: Research Article
ISSN: 0955-6222

Keywords

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Article
Publication date: 10 December 2018

Bruno C.N. Oliveira, Alexis Huf, Ivan Luiz Salvadori and Frank Siqueira

This paper describes a software architecture that automatically adds semantic capabilities to data services. The proposed architecture, called OntoGenesis, is able to…

Abstract

Purpose

This paper describes a software architecture that automatically adds semantic capabilities to data services. The proposed architecture, called OntoGenesis, is able to semantically enrich data services, so that they can dynamically provide both semantic descriptions and data representations.

Design/methodology/approach

The enrichment approach is designed to intercept the requests from data services. Therefore, a domain ontology is constructed and evolved in accordance with the syntactic representations provided by such services in order to define the data concepts. In addition, a property matching mechanism is proposed to exploit the potential data intersection observed in data service representations and external data sources so as to enhance the domain ontology with new equivalences triples. Finally, the enrichment approach is capable of deriving on demand a semantic description and data representations that link to the domain ontology concepts.

Findings

Experiments were performed using real-world datasets, such as DBpedia, GeoNames as well as open government data. The obtained results show the applicability of the proposed architecture and that it can boost the development of semantic data services. Moreover, the matching approach achieved better performance when compared with other existing approaches found in the literature.

Research limitations/implications

This work only considers services designed as data providers, i.e., services that provide an interface for accessing data sources. In addition, our approach assumes that both data services and external sources – used to enhance the domain ontology – have some potential of data intersection. Such assumption only requires that services and external sources share particular property values.

Originality/value

Unlike most of the approaches found in the literature, the architecture proposed in this paper is meant to semantically enrich data services in such way that human intervention is minimal. Furthermore, an automata-based index is also presented as a novel method that significantly improves the performance of the property matching mechanism.

Details

International Journal of Web Information Systems, vol. 15 no. 1
Type: Research Article
ISSN: 1744-0084

Keywords

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