Web Service Discovery Based on Past User Experience

Kokash, Natallia; Birukou, Aliaksandr; D’Andrea, Vincenzo

doi:10.1007/978-3-540-72035-5_8

Cited by 46 publications

(32 citation statements)

References 15 publications

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“…Other approaches [1,12] applied the associated rules technique, while [33,34] applied collaborative filtering technique on the service's QoS to deploy a WS recommender system. They, however, did not take into account user's behavior, which is a very important parameter for finding the closest WS operations to users' interests.…”

Section: Problem Statementmentioning

confidence: 99%

A recommender system based on historical usage data for web service discovery

Chân¹,

Gaaloul²,

Tata³

2012

SOCA

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The tremendous growth in the amount of available web services impulses many researchers on proposing recommender systems to help users discover services. Most of the proposed solutions analyzed query strings and web service descriptions to generate recommendations. However, these text-based recommendation approaches depend mainly on user's perspective, languages, and notations, which easily decrease recommendation's efficiency. In this paper, we present an approach in which we take into account historical usage data instead of the text-based analysis. We apply collaborative filtering technique on user's interactions. We propose and implement four algorithms to validate our approach. We also provide evaluation methods based on the precision and recall in order to assert the efficiency of our algorithms.

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Section: Problem Statementmentioning

confidence: 99%

A recommender system based on historical usage data for web service discovery

Chân¹,

Gaaloul²,

Tata³

2012

SOCA

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“…Most related works using quality and context information in serviceoriented computing can be divided into three classes: (i) approaches to enhanced Web service design, such as different ways to add non-functional parameters to Web services in [14]; (ii) techniques to increase the relevance of the result of Web service discovery and selection, such as the discovery of resources based on WS-Policy specifications using an external middleware in [15] and the NFP-based hybrid approach to Web service ranking in [16]; (iii) approaches to improve the relevance of information offered by the services using context information, such as users and their interaction with a service [12], user experiences [17], and context models for personalized Web services [13].…”

Section: Related Workmentioning

confidence: 99%

Context, Quality and Relevance: Dependencies and Impacts on RESTful Web Services Design

Truong

Dustdar

Maurino

et al. 2010

Current Trends in Web Engineering

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Abstract. While several techniques have been introduced for specifying and acquiring context and quality information associated with Web services, they consider such information representing the whole Web services. However, accessing to context and quality of data resources provided by Web services is crucial. This is particularly relevant for data-intensive Web services of which the context and quality of data resources will strongly impact on the service development and composition. In this paper we contribute an analysis of relationships among context, quality, and relevance, as well as their impact on the design and composition of Web services, in particular at the data resource level. Then, we propose several techniques to incorporate context and quality descriptions into REST APIs and RESTful services publishing. By implementing these features, RESTful Web services could allow the consumer to specify and query context and quality information associated with services and data resources, thus fostering the provision of high relevant data resources.

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“…User Experience retrieval [32] assumes that users with similar interests have similar significant action sequences. Data mining processes are used to discover similar patterns from monitored user actions that may refer to the similar services and give recommendations for an action that should be performed like a search request.…”

Section: Surveymentioning

confidence: 99%

Towards Autonomic Service Discovery A Survey and Comparison

Rambold

Kasinger

Lautenbacher

et al. 2009

2009 IEEE International Conference on Services Computing

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Abstract-Service-oriented architecture has become the standard paradigm for software component integration. However, with the permanently increasing amount of available services and dynamic changes, the complexity of such service infrastructures, their maintenance, and consequently the expenditures spent for their operation increase equally. To deal with these effects, an improvement of service composition and discovery becomes necessary, especially a higher degree of automation. Following the idea of Autonomic Computing, which similarly aims at automating processes and workflows to a high degree, service composition and discovery have to proceed autonomously, which will on the one hand side reduce human involvement to a minimum, but on the other side require certain capabilities on the part of these mechanisms. For these purposes, in this paper we define prime criteria that have to be fulfilled for an autonomic service discovery. Based on that we present a comprehensive survey on existing service discovery approaches and evaluate to which extent they already fulfill these criteria. As a result, the paper reveals that there already exist some approaches that support or even fulfill a couple of the proposed criteria, which principally enables autonomic properties, but what is missing is an holistic approach focusing explicitly on providing autonomic properties.

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Web Service Discovery Based on Past User Experience

Cited by 46 publications

References 15 publications

A recommender system based on historical usage data for web service discovery

A recommender system based on historical usage data for web service discovery

Context, Quality and Relevance: Dependencies and Impacts on RESTful Web Services Design

Towards Autonomic Service Discovery A Survey and Comparison

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