Multi-Level Web Service Clustering to Bootstrap the Web Service Discovery and Selection

2019 ◽  
pp. 44-68
Author(s):  
Banage T. G. S. Kumara ◽  
Incheon Paik ◽  
Koswatte R. C. Koswatte
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Service Discovery ◽  
Value Added ◽  
Search Space ◽  
Clustering Approach ◽  
Multi Level ◽  
Service Clustering ◽  
Service Discovery And Selection

Existing technologies for web services have been extended to give the value-added customized services to users through the service composition. Service composition consists of four major stages: planning, discovery, selection, and execution. However, with the proliferation of web services, service discovery and selection are becoming challenging and time-consuming tasks. Organizing services into similar clusters is a very efficient approach. Existing clustering approaches have problems that include discovering semantic characteristics, loss of semantic information, and a shortage of high-quality ontologies. Thus, the authors proposed hybrid term similarity-based clustering approach in their previous work. Further, the current clustering approaches do not consider the sub-clusters within a cluster. In this chapter, the authors propose a multi-level clustering approach to prune the search space further in discovery process. Empirical study of the prototyping system has proved the effectiveness of the proposed multi-level clustering approach.

Context-Aware Web Service Clustering and Visualization

2020 ◽  
Vol 17 (4) ◽  
pp. 32-54
Author(s):  
Banage T. G. S. Kumara ◽  
Incheon Paik ◽  
Yuichi Yaguchi
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Discovery ◽  
Search Space ◽  
Context Aware ◽  
Specific Context ◽  
Web Service Discovery ◽  
Domain Specific ◽  
Clustering Approach ◽  
Service Clustering

With the large number of web services now available via the internet, web service discovery has become a challenging and time-consuming task. Organizing web services into similar clusters is a very efficient approach to reducing the search space. A principal issue for clustering is computing the semantic similarity between services. Current approaches do not consider the domain-specific context in measuring similarity and this has affected their clustering performance. This paper proposes a context-aware similarity (CAS) method that learns domain context by machine learning to produce models of context for terms retrieved from the web. To analyze visually the effect of domain context on the clustering results, the clustering approach applies a spherical associated-keyword-space algorithm. The CAS method analyzes the hidden semantics of services within a particular domain, and the awareness of service context helps to find cluster tensors that characterize the cluster elements. Experimental results show that the clustering approach works efficiently.

Incorporating LDA With Word Embedding for Web Service Clustering

2018 ◽  
Vol 15 (4) ◽  
pp. 29-44 ◽  
Author(s):  
Yi Zhao ◽  
Chong Wang ◽  
Jian Wang ◽  
Keqing He
Keyword(s):  
Web Service ◽  
Service Discovery ◽  
Word Embedding ◽  
The Internet ◽  
Word Embeddings ◽  
Training Process ◽  
Web Service Discovery ◽  
Processing Data ◽  
Clustering Approach ◽  
Service Clustering

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.

Composition Oriented Semantic Relationships Mining Framework Research

2014 ◽  
Vol 513-517 ◽  
pp. 470-473 ◽  
Author(s):  
Zheng De Zhao ◽  
Yue Hui Cui ◽  
Jian Jun Li
Keyword(s):  
Web Services ◽  
Service Composition ◽  
Service Discovery ◽  
Search Space ◽  
Experimental Results ◽  
Business Logic ◽  
Semantic Relationships ◽  
Functional Clustering ◽  
Two Stages ◽  
Mining Algorithms

In order to improve the efficiency of service discovery and service composition, this paper proposes a Composition oriented Web services semantic relationships mining framework. Firstly, Web services need to be pretreated, which are filtered based on QoS; and then adopt the method of service functional clustering to generate service classes, which largely reduces the services search space and improve the efficiency of service discovery; Secondly, in order to excavate the semantic relationships between service classes that meet the business logic requirement, we need to set the composition rules between service classes; Finally, using two stages of mining algorithms to excavate the semantic relationships between service classes. Experimental results are given to validate the feasibility and validity of our framework.

Towards a High-Availability-Driven Service Composition Framework

2013 ◽  
pp. 221-243 ◽  
Author(s):  
Jonathan Lee ◽  
Shang-Pin Ma ◽  
Shin-Jie Lee ◽  
Chia-Ling Wu ◽  
Chiung-Hon Leon Lee
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Service Discovery ◽  
Service Management ◽  
High Availability ◽  
Main Trend ◽  
Service Oriented ◽  
Composite Services ◽  
Delivery Approach

Service-Oriented Computing (SOC), a main trend in software engineering, promotes the construction of applications based on the notion of services. SOC has recently attracted a great deal of attention from researchers, and has been comprehensively adopted by industry. However, service composition enabling the aggregation of existing services into composite services still imposes a great challenge to service-oriented technology. Web service composition requires component Web services to be available in request, to behave correctly in operation, and to be replaceable flexibly in failure. Although availability of Web services plays a crucial role in building robust SOC-based applications, it has been largely neglected, especially for service composition. In this chapter, we propose a service composition framework that integrates a set of composition-based service discovery mechanisms, a user-oriented service delivery approach, as well as a service management mechanism for composite services.

Towards a High-Availability-Driven Service Composition Framework

2014 ◽  
pp. 1498-1520
Author(s):  
Jonathan Lee ◽  
Shang-Pin Ma ◽  
Shin-Jie Lee ◽  
Chia-Ling Wu ◽  
Chiung-Hon Leon Lee
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Service Discovery ◽  
Service Management ◽  
High Availability ◽  
Main Trend ◽  
Service Oriented ◽  
Composite Services ◽  
Delivery Approach

Service-Oriented Computing (SOC), a main trend in software engineering, promotes the construction of applications based on the notion of services. SOC has recently attracted a great deal of attention from researchers, and has been comprehensively adopted by industry. However, service composition enabling the aggregation of existing services into composite services still imposes a great challenge to service-oriented technology. Web service composition requires component Web services to be available in request, to behave correctly in operation, and to be replaceable flexibly in failure. Although availability of Web services plays a crucial role in building robust SOC-based applications, it has been largely neglected, especially for service composition. In this chapter, we propose a service composition framework that integrates a set of composition-based service discovery mechanisms, a user-oriented service delivery approach, as well as a service management mechanism for composite services.

Web Service Clustering Using Relational Database Approach

2015 ◽  
Vol 25 (08) ◽  
pp. 1365-1393 ◽  
Author(s):  
Jianxiao Liu ◽  
Feng Liu ◽  
Xiaoxia Li ◽  
Keqing He ◽  
Yutao Ma ◽  
...  
Keyword(s):  
Web Services ◽  
Web Service ◽  
Relational Database ◽  
Service Discovery ◽  
The Self ◽  
Input Output ◽  
Computing Services ◽  
Service Information ◽  
Service Oriented ◽  
Service Clustering

In the era of service-oriented software engineering (SOSE), service clustering is used to organize Web services, and it can help to enhance the efficiency and accuracy of service discovery. In order to improve the efficiency and accuracy of service clustering, this paper uses the self-join operation in relational database (RDB) to realize Web service clustering. Based on storing service information, it does the self-join operation towards the Input, Output, Precondition, Effect (IOPE) tables of Web services, which can enhance the efficiency of computing services similarity. The semantic reasoning relationship between concepts and the concept status path are used to do the calculation, which can improve the calculation accuracy. Finally, we use experiments to validate the effectiveness of the proposed methods.

Web Service Clustering and Data Mining in SOA System

2017 ◽  
pp. 157-177
Author(s):  
Sreeparna Mukherjee ◽  
Asoke Nath
Keyword(s):  
Data Mining ◽  
Web Services ◽  
Web Service ◽  
Service Discovery ◽  
Software Components ◽  
Discovery Process ◽  
Data Mining Techniques ◽  
Web Service Discovery ◽  
Service Clustering ◽  
The Web

The success of the web depended on the fact that it was simple and ubiquitous. Over the years, the web has evolved to become not only the repository for accessing information but also for storing software components. This transformation resulted in increased business needs and with the availability of huge volumes of data and the continuous evolution in Web services functions derive the need of application of data mining in the Web service domain. Here we focus on applying various data mining techniques to the cluster web services to improve the Web service discovery process. We end this with the various challenges that are faced in this process of data mining of web services.

The Research of Semantic Web Service Composition Framework Based on Ontology

2014 ◽  
Vol 912-914 ◽  
pp. 1473-1476
Author(s):  
Bo Yang ◽  
Ying Fang Li ◽  
Xiang Yang ◽  
Ying Jiang Li
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Web Service ◽  
Service Composition ◽  
Service Providers ◽  
Value Added ◽  
Web Service Composition ◽  
Semantic Web Service ◽  
Paper Making ◽  
Semantic Web Service Composition

At present, more and more service providers carry on their business as a Web type. However, the function of individual Web services is very limited and the lack of semantic information, only can meet the needs for a single customer. In this paper, making Web services become an entities understood by the computer through introducing the concept of the Ontology. A framework of Semantic Web Service composition also is proposed based on Ontology for assembling basic Web services coming from different service providers and a solution is provided for to achieve value-added services based on a single service.

Web Service Clustering Approach Based on Network and Fused Document-Based and Tag-Based Topics Similarity

2021 ◽  
Vol 18 (3) ◽  
pp. 63-81
Author(s):  
Deng Li Ping ◽  
Guo Bing ◽  
Zheng Wen
Keyword(s):  
Web Services ◽  
Web Service ◽  
Auxiliary Information ◽  
Service Network ◽  
New Approach ◽  
Data Network ◽  
Modal Data ◽  
Clustering Problem ◽  
Clustering Approach ◽  
Service Clustering

To produce a web services clustering with values that satisfy many requirements is a challenging focus. In this article, the authors proposed a new approach with two models, which are helpful to the service clustering problem. Firstly, a document-tag LDA model (DTag-LDA) is proposed that considers the tag information of web services, and the tag can describe the effective information of documents accurately. Based on the first model, this article further proposes an efficient document weight and tag weight-LDA model (DTw-LDA), which fused multi-modal data network. To further improve the clustering accuracy, the model constructs the network for describing text and tag respectively and then merges the two networks to generate web service network clustered. In addition, this article also designs experiments to verify that the used auxiliary information can help to extract more accurate semantics by conducting service classification. And the proposed method has obvious advantages in precision, recall, purity, and other performance.

Web Service Discovery for Cloud-Based Mobile Application Using Multi-Level Clustering and QoS-Based Ranking

2016 ◽  
Vol 26 (07) ◽  
pp. 1077-1097
Author(s):  
R. Kanesaraj Ramasamy ◽  
Fang-Fang Chua ◽  
Su-Cheng Haw ◽  
Chin-Kuan Ho
Keyword(s):  
Web Services ◽  
Web Service ◽  
Mobile Application ◽  
Service Discovery ◽  
Service Providers ◽  
User Preferences ◽  
Web Service Discovery ◽  
Multi Level ◽  
Searching Performance

Since many service providers are providing similar web services, finding an accurate web service based on user preferences is becoming a challenging task. Therefore, enhancing web service discovery (WSD) method will improve the searching performance. In this paper, we firstly discuss and review some existing web service discovery approaches and identify their limitations. Subsequently, we propose a web service discovery method for cloud-based mobile application by using multi-level clustering technique to improve performance by reducing the searching scope. Our web service discovery architecture is able to increase the discoverability of more accurate web services based on user's preferences. Meanwhile, user preference Quality of Services (QoS) attributes are also used for ranking procedure to allow user to decide the quality of the mobile application. The experimental results show that our approach is able to increase the searching performance and provide a reliable list of selection for users.

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