An Optimal Agent Based (Oab) Architecture for Web Service Discovery

2016 ◽  
Vol 9 (3) ◽  
pp. 37-46
Author(s):  
Suganya D ◽  
Revathy A ◽  
R.G. Suresh Kumar ◽  
N. Moganarangan ◽  
D Madhavan
Author(s):  
Aliaksandr Birukou ◽  
Enrico Blanzieri ◽  
Paolo Giorgini

People belong to different communities: business communities, Web 2.0 communities, just to name a few. In this chapter the authors show that experience acquired by people in communities constitute community culture. The authors introduce the problem of culture transfer between or within communities and propose a domain-independent approach for transferring community culture. First, the authors formalize the notion of culture, which includes behavior, knowledge, artifacts, best practices, etc. Second, using this formalism, the authors propose the Implicit Culture Framework, which is an agent-based framework for transferring behavior between community members or between communities. Finally, the authors present and evaluate a system for web service discovery developed using the Implicit Culture Framework.


2012 ◽  
Vol 8 (1) ◽  
pp. 76-97
Author(s):  
Nandini S. Sidnal ◽  
Sunilkumar S. Manvi

Internet enabled auctions are one of the popular application which basically require a web service discovery mechanism that is efficient in all perspectives. This paper focuses on auction service discovery and building repository of services for the use of E-customers. The auction service directory (repository) is developed based on the customer’s desires. Agent based Belief Desire Intention (BDI) architecture is used in this model, not only to support the service discovery process in spotty or no connectivity network environment but also to automate the process so that it enables the mobile users to complete the discovery process successfully without continuous on-line presence. The simulation results depict that the performance parameters like customer satisfaction, availability of requested services and stability in fetching the services are better in the proposed service discovery model as compared to auction based advertisement facilitated service discovery mechanism.


2018 ◽  
Vol 6 (9) ◽  
pp. 311-314
Author(s):  
Rahul P. Mirajkar ◽  
Nikhil D. Karande ◽  
Surendra Yadav

2018 ◽  
Vol 15 (4) ◽  
pp. 29-44 ◽  
Author(s):  
Yi Zhao ◽  
Chong Wang ◽  
Jian Wang ◽  
Keqing He

With the rapid growth of web services on the internet, web service discovery has become a hot topic in services computing. Faced with the heterogeneous and unstructured service descriptions, many service clustering approaches have been proposed to promote web service discovery, and many other approaches leveraged auxiliary features to enhance the classical LDA model to achieve better clustering performance. However, these extended LDA approaches still have limitations in processing data sparsity and noise words. This article proposes a novel web service clustering approach by incorporating LDA with word embedding, which leverages relevant words obtained based on word embedding to improve the performance of web service clustering. Especially, the semantically relevant words of service keywords by Word2vec were used to train the word embeddings and then incorporated into the LDA training process. Finally, experiments conducted on a real-world dataset published on ProgrammableWeb show that the authors' proposed approach can achieve better clustering performance than several classical approaches.


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