Combining social network and collaborative filtering for personalised manufacturing service recommendation

Zhang, W.Y.; Zhang, S.; Chen, Yuangao; Pan, Xiao

doi:10.1080/00207543.2013.832839

Cited by 44 publications

(32 citation statements)

References 27 publications

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“…However, the previous social network-based recommender methods [8,17,23,25,29], have not considered reputation propagation between consumer enterprises, which makes the result of manufacturing service recommendation ineffective. Therefore, this study employed SALSA, which is an effective link analysis method to compute global and accurate reputation value of enterprises in a social network.…”

Section: Social Network-based Recommender Methodsmentioning

confidence: 99%

“…Additionally, Sun et al [25] proposed a dynamic competitive approach to overcome the problem of environmental change for social network service recommendation. A previous work [29]-also done by the present writers-presented Quality of Service (QoS)-aware service recommendation by combining social network and CF technology to predict the missing QoS values for manufacturing service recommendation.…”

Section: Social Network-based Recommender Methodsmentioning

confidence: 99%

“…In this section, PCC is also leveraged to calculate the rating similarity of consumer enterprises according to their historical ratings to services, and the equation is presented as follows [29]:…”

Section: Selection Of Top K2 Enterprises With Similar Ratingsmentioning

confidence: 99%

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A Hybrid Social Network-based Collaborative Filtering Method for Personalized Manufacturing Service Recommendation

Zhang

Yang

et al. 2017

INT J COMPUT COMMUN

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Nowadays, social network-based collaborative filtering (CF) methods are widely applied to recommend suitable products to consumers by combining trust relationships and similarities in the preference ratings among past users. However, these types of methods are rarely used for recommending manufacturing services. Hence, this study has developed a hybrid social network-based CF method for recommending personalized manufacturing services. The trustworthy enterprises and three types of similar enterprises with different features were considered as the four influential components for calculating predicted ratings of candidate services. The stochastic approach for link structure analysis (SALSA) was adopted to select top K trustworthy enterprises while also considering their reputation propagation on enterprise social network. The predicted ratings of candidate services were computed by using an extended user-based CF method where the particle swarm optimization (PSO) algorithm was leveraged to optimize the weights of the four components, thus making service recommendation more objective. Finally, an evaluation experiment illustrated that the proposed method is more accurate than the traditional user-based CF method.

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Section: Social Network-based Recommender Methodsmentioning

confidence: 99%

Section: Social Network-based Recommender Methodsmentioning

confidence: 99%

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A Hybrid Social Network-based Collaborative Filtering Method for Personalized Manufacturing Service Recommendation

Zhang

Yang

et al. 2017

INT J COMPUT COMMUN

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“…As a matter of fact, there are many algorithms but the one adopted in this research is the use of Pearson Correlation Coefficient, which is a commonly employed statistical test for this purpose (e.g. Ahlgren et al, 2003;Cheung and Li, 2012;Zhang et al, 2013;Bouguettaya et al, 2015). Table 3 lists the coefficients and the corresponding pair of items (i.e.…”

Section: Figure 2 Dendrogram Of the Cluster Analysismentioning

confidence: 99%

The role of social media data in operations and production management

Chan

Lacka

Yee

et al. 2015

International Journal of Production Research

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Social media data contain rich information in posts or comments written by customers. If those data can be extracted and analysed properly, companies can fully utilise this rich source of information. They can then convert the data to useful information or knowledge which can help to formulate their business strategy. This can not only facilitate marketing research in view of customer behaviour, but can also aid other management disciplines. Operations management research and practice with the objective to make decisions on product and process design is a fine example. Nevertheless, this line of thought is underresearched. In this connection, this paper explores the role of social media data in operations management research. A structured approach is proposed which involves the analysis of social media comments and a statistical cluster analysis to identify the interrelationships among important factors. A real-life example is employed to demonstrate the concept.

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“… Inventory Management -The overseeing and controlling of the ordering, storage and use of components that a company will use in the production of the items it will sell as well as the overseeing and controlling of quantities of finished products for sale. (Columbus, 2013;Gould, 2012) (Coyle et al, 2013);Gould, 2012;Zhang, Zhang, Chen & Pan, 2014) Mashups "Aggregating content from different online sources to create a new application or service" (Kenney, 2007, p. 39 (Churches, 2009;Harris, 2008;Lackie & Terrio, 2007;Meditskos & Bassililades, 2011) Mobile Mobile Marketing "includes messaging, Wireless Application Protocol (WAP), and the mobile Internet, streaming media, and downloadable content". (Castronovo & Huang, 2012, p. 121).…”

Section: Dashboardsmentioning

confidence: 99%

Non-Technical Skills for IT Professionals in the landscape of Social Media

Johnson

2015

AJBM

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This paper provides a comprehensive literature review on the non-technical skills needed by IT professionals to work successfully in social media. Previous research has examined nontechnical and found that soft skills such as communication, knowledge management, leadership, personal accountability, time management and an understanding of business functions are important for IT professionals to possess. No study has examined the specific soft skills that are needed in the landscape of social media such as for bogging, content sharing, customer relationship management, pod-casting and project management. This paper will provide a comprehensive list of soft skills and will ascertain which skills are required for specific social media applications. Finally a review of the literature has indicated that an understanding of one's personal brand will impact career success. The issues relevant to personal branding for IT students and professionals will be discussed. Implications for curriculum development in academia and for practitioners will be examined.

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Combining social network and collaborative filtering for personalised manufacturing service recommendation

Cited by 44 publications

References 27 publications

A Hybrid Social Network-based Collaborative Filtering Method for Personalized Manufacturing Service Recommendation

A Hybrid Social Network-based Collaborative Filtering Method for Personalized Manufacturing Service Recommendation

The role of social media data in operations and production management

Non-Technical Skills for IT Professionals in the landscape of Social Media

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