Recommending multimedia web services in a multi-device environment

Rosaci, Domenico; Sarné, Giuseppe M. L.

doi:10.1016/j.is.2012.08.002

Cited by 43 publications

(19 citation statements)

References 41 publications

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“…Mechanisms for recommending Web services evolving in heterogeneous environments were widely concerned. A new agent-based system was proposed to recommend multimedia Web services based on the effect of the currently exploited device in [5]. Underlying search and ranking algorithms that enable service recommendations was studied in [6], and service recommender system using enhanced syntactical matching was proposed.…”

Section: Introductionmentioning

confidence: 99%

A Clustering Method for Isomorphic Evolution of Web Services

Zhen

2017

Scientific Programming

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Since the basic binding unit of current service request and response schema is an atomic Web service, it needs to costly find a substitute service or reconstruct the service process in the original service space once a fine granular evolution requirement occurs. To reduce the complexity of fine granular service evolution, an isomorphic evolution mechanism based on service clusters is proposed. Searching space can be reduced and responding flexibility will also be improved by adopting service cluster as the unit of service response. Simple evolution and merging evolution were put forward to handle the evolution of atomic Web services. Meanwhile, a formal model and the quality computing method for service processes built by service clusters were presented based on the logic Petri nets. Two types of evolution patterns including dot isomorphic evolution and chain isomorphic evolution were proposed to evolve service processes. The algorithms for different isomorphic evolution patterns of atomic service and service processes were designed in the paper. Simulation experiments were conducted on 10000 Web services with different process patterns. Compared with the traditional service request and response schema, the efficiencies of service discovery and isomorphic evolution are improved greatly in our proposed method.

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Section: Introductionmentioning

confidence: 99%

A Clustering Method for Isomorphic Evolution of Web Services

Zhen

2017

Scientific Programming

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“…Meanwhile, searching for personalized interests and feelings posted to the multi-source information platforms, such as micro-blog systems like Twitter, social network sites including Facebook and LinkedIn, and personal homepages and blogs as well as many others [1] [2], is an interesting yet challenging task. Especially, in the micro-blog system platforms, people repost a lot of short messages about their daily activities and feelings so as to maintain latest interests or friendship.…”

Section: Introductionmentioning

confidence: 99%

Neighborhood-user profiling based on perception relationship in the micro-blog scenario

Zheng

Zhang

Yue

et al. 2015

Journal of Web Semantics

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“…If the quality of experience (QoE) does not reach expectations, users will not trust the service and even reject related services provided by service providers. Therefore, ensuring quality of services (QoS) close to user expectation and discover trustworthy services will be the key factors for promoting cloud computing [1].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the cold start problem will become more serious for potential users in the cloud systems. As a result, the existing methods [1] [3] [4] based on collaborative filtering algorithm cannot provide the high-quality recommendation results.…”

Section: Introductionmentioning

confidence: 99%

“…Meanwhile, considering the cloud services are mainly provided via the uncertain Internet, consumers may experience the different QoS of one service affected by many factors, including client-side location [5], client-side device environment [1], and client-side integrated development environment [6]. It causes that the QoE evaluations from consumers cannot be uniform.…”

Section: Introductionmentioning

confidence: 99%

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Cloud service recommendation based on trust measurement using ternary interval numbers

2014

2014 International Conference on Smart Computing

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Owing to the deficiency of usage experiences and the information overload of QoE (quality of experience) evaluations from consumers, how to discover the trustworthy cloud services is a challenge for potential users. This paper proposed a cloud service recommendation approach based on trust measurement using ternary interval numbers for potential user. The concept of ternary interval number is introduced. The user feature maybe affecting the QoE evaluations are analyzed and the client-side feature similarity between consumers and potential user is calculated. The transform mechanism from trust evaluations to ternary interval number is presented by employing the K-means clustering algorithm. On the basis of multi-attributes trust aggregation based On FAHP (fuzzy analytic hierarchy process) method, a new possibility degree formula is designed for ranking ternary interval numbers and selecting trustworthy service. Finally, the experiments and results show that this approach is effective to improve the accuracy of the trustworthy service recommendation.

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Recommending multimedia web services in a multi-device environment

Cited by 43 publications

References 41 publications

A Clustering Method for Isomorphic Evolution of Web Services

A Clustering Method for Isomorphic Evolution of Web Services

Neighborhood-user profiling based on perception relationship in the micro-blog scenario

Cloud service recommendation based on trust measurement using ternary interval numbers

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