Dynamic Selection of Web Services with Recommendation System

Manikrao, U.S.; Prabhakar, T. V.

doi:10.1109/nwesp.2005.32

Cited by 110 publications

(61 citation statements)

References 4 publications

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“…This recommendation engine learns through consumer feedback after using the service. [8], Manikrao [9] and Le-Hung Vu [10] proposed method where consumer will get a selection of web recommendation service in accordance with the previous consumer satisfaction ratings. …”

Section: Dynamic Selection Of Web Services With Recommendation Systemmentioning

confidence: 99%

Untitled

Saadah¹,

Atmagi²

2014

Jurnal Ilmu Komputer dan Informasi

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In service-oriented computing, web services are the basic foundation that aims to facilitate building of business application in a more flexible and interoperable manner for enterprise collaboration. One of the most promising advantages of web service technology is the possibility of creating added-value services by combining existing ones. A key step for composing and executing services lies in the selection of the individual service to use. Much attention has been devoted to appropriate selection of service functionalities, but also the non-functional properties of the services play a key role. A web service selection technique must take as much as possible the important influencing aspects into account to the selection process in order to minimize the selection efforts. This paper evaluates several web service selection techniques published in literature with the focus on their contributions to web service selection. The evaluation results can be used as a basis for improving web service selection techniques and then simplifying the selection tasks. Keywords: Web services, QoS, Service Lifecycle Management, Web Service Broker, UDDI AbstrakDalam komputasi berorientasi layanan, layanan web adalah dasar pembangunan yang bertujuan untuk memfasilitasi pembangunan aplikasi bisnis dengan cara yang lebih fleksibel dan interoperable untuk kolaborasi perusahaan. Salah satu keuntungan yang paling menjanjikan dari teknologi web service adalah kemungkinan untuk menciptakan nilai tambah dengan menggabungkan layanan yang sudah ada. Sebuah langkah kunci untuk menyusun dan melaksanakan layanan terletak pada pemilihan layan-an individual yang akan digunakan. Banyak penelitian berfokus pada pemilihan fungsi pelayanan yang tepat, namun properti non-fungsional dari layanan yang memainkan peran kunci juga tetap diperhatikan. Sebuah teknik dalam menyeleksi layanan web harus mengambil sebanyak mungkin aspek penting yang mempengaruhi perhitungan terhadap proses seleksi dalam meminimalisir upaya seleksi. Penelitian ini mengevaluasi beberapa teknik seleksi layanan web yang dipublikasikan dalam literatur dengan fokus pada kontribusi mereka terhadap pemilihan layanan web. Hasil evaluasi dapat digunakan sebagai dasar untuk meningkatkan teknik pemilihan layanan web yang dapat menyederhanakan proses-proses seleksi.

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Section: Dynamic Selection Of Web Services With Recommendation Systemmentioning

confidence: 99%

Untitled

Saadah¹,

Atmagi²

2014

Jurnal Ilmu Komputer dan Informasi

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“…(Zhang, Liu et al, 2013) proposed a novel approach to modeling the dynamic behavior of interacting context-aware Web services, aiming to process and take advantage of context effectively in realizing the behavior adaptation of Web services. Moreover, for service recommendation, some researchers have used both personal-usage history-oriented contexts and groupusage history-oriented contexts, such as collaborative filters that assess users' ratings of Web services (Resnick, Iakovou et al, 1994;Manikrao & Prabhakar, 2005).…”

Section: Context-aware Web Servicesmentioning

confidence: 99%

Improving Web Service Clustering Through Post Filtering to Bootstrap the Service Discovery

Kumara¹,

Paik²,

Koswatte³

et al. 2014

STSC

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Web service clustering is one of a very efficient approach to discover Web services efficiently. Current approaches use similarity-distance measurement methods such as string-based, corpus-based, knowledge-based and hybrid methods. These approaches have problems that include discovering semantic characteristics, loss of semantic information, shortage of high-quality ontologies and encoding fine-grained information. Thus, the approaches couldn't identify the correct clusters for some services and placed them in wrong clusters. As a result of this, cluster performance is reduced. This paper proposes post-filtering approach to increase the performance of clusters by rearranging services incorrectly clustered. Our approach uses context aware similarity method that learns domain context by machine learning to produce models of context for terms retrieved from the Web in the filtering process to calculate the service similarity. We applied post filtering approach to hybrid term similarity based clustering approach that we proposed in our previous work. Experimental results show that our post-filtering approach works efficiently.

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“…In recent years, recommendation techniques and systems have gained more and more attention, and are researched and applied in a variety of fields [1][2][3][4][5]. Upon that background it has a practical benefit to put the recommendation techniques into workflow execution.…”

Section: Introductionmentioning

confidence: 99%

“…A whole browsing process for a user can be thought of as a workflow instance, and every click operation for that user can be thought of as an activity. In the Service Oriented Computing domain, the nodes (Web services) that are appropriate to the task that are to be fulfilled are first discovered and the best Web service(s) is then identified for execution in the workflow through some service optimization process [3]. In a sense, this resembles to a workflow recommendation problem where the service discovery and optimization help recommend to users the best service that needs to be execute in each step [4].…”

Section: Introductionmentioning

confidence: 99%

A Role-based Adjacent Workflow Recommendation Technique

Chen¹,

Li²

2015

Proceedings of the 2015 International Conference on Computer Science and Intelligent Communication

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Abstract-Recently recommendation techniques and systems have gained more and more attention and are researched in a variety of fields. In this paper we put the recommendation technique into the problem of workflow or Web browsing so that can facilitate the workflow participants to find their next most desired activities or the people in the Business Internet to find their next wanted clicks.The distinguished feature of our automated workflow recommendation technique is that the concept of role-based adjacent workflow instance is incorporated. Our proposed algorithm first calculates the multi-set of rolebased adjacent workflow instances of an incomplete workflow instance, and then utilizes this multi-set to predict the next desired activity for that incomplete workflow instance. The experimental results confirm the promising effectiveness of our role-based adjacent workflow recommendation algorithm.

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Dynamic Selection of Web Services with Recommendation System

Abstract: Abstract

Cited by 110 publications

References 4 publications

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Improving Web Service Clustering Through Post Filtering to Bootstrap the Service Discovery

A Role-based Adjacent Workflow Recommendation Technique

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