scholarly journals Web Service Discovery Based on Unified View on Functional and Non-functional Properties

2010 ◽  
Author(s):  
Martin Junghans ◽  
Sudhir Agarwal
Keyword(s):  
Web Service ◽  
Functional Properties ◽  
Service Discovery ◽  
Web Service Discovery ◽  
Unified View

GLUE2: A Web Service Discovery Engine with Non-Functional Properties

2008 ◽  
Author(s):  
Alessio Carenini ◽  
Dario Cerizza ◽  
Marco Comerio ◽  
Emanuele Della Valle ◽  
Flavio De Paoli ◽  
...  
Keyword(s):  
Web Service ◽  
Functional Properties ◽  
Service Discovery ◽  
Web Service Discovery

Study of Web Service Discovery Algorithm Based on Semantic

2014 ◽  
Vol 644-650 ◽  
pp. 2793-2796
Author(s):  
Liang Zhao ◽  
Wei Zhang
Keyword(s):  
Web Service ◽  
Functional Properties ◽  
Process Model ◽  
Service Discovery ◽  
Web Service Discovery ◽  
Input And Output ◽  
Similarity Computation ◽  
Discovery Algorithms

Most of the exiting discovery algorithms focus on the functional properties calculation, and the process model has not been taken into account which leads to the low recall and precision of web service. In the similarity computation of service functional properties, the input and output parameters are divided into pairs by their relationships and process model is transformed into corresponding directed trees, and we can get the similarity between processes by the isomorphism of the directed trees and the similarity computation of tree’s nodes and edges. As experiments state, the cache-based discovery algorithm will significantly improve web service discovery in precision and time consumed.

A Study on Different Web Service Discovery Approaches

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

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.

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