Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/515860
Title: | Ai powered gpu enabled semantic web Service composition |
Researcher: | Swetha, N G |
Guide(s): | Karpagam, G R |
Keywords: | Ai powered gpu Computer Science Computer Science Information Systems Engineering and Technology semantic web Service composition |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | Web services are an essential part of the world wide web which simplifies automation in each business domain. The popularity of web services are increasing day by day with a sudden shift of people into the digital lifestyle. Web Services paves the way into automation of every functionality around us. As the scope for automation increases, the total number of web services developed also increases in an exponential fashion. Every company strives to become a global leader of automation which leads to increased competitiveness across them which in turn leads to an increase in functionally similar web services across the web. The presence of numerous amount of web services increases the challenge involved in the retrieval of web services for a user query. This research work aims in formulating a framework that makes the retrieval of web services efficient. Web services are granular in nature and hence a complex user query in most cases cannot be satisfied by the retrieval of a single atomic service. Hence, it becomes necessary to identify a collection of services which when executed in a particular order satisfy the user query. To facilitate this process of service composition, the framework is divided into three sequential phases namely Web Service Discovery, Web Service Selection, and Plan Generation. This research work aims in contributing towards each phase to ease out the process service composition. Web Service Discovery is the initial step for composing the services where every service has to be functionally detected accurately, such that it can solve an aspect of the user query. The researchers have employed various techniques like Match Making Algorithms, Optimization Techniques, iv newlineClassification methods, and Clustering methods in conjunction with different ontologies to discover relevant services. It is observed from the literature that, the key point in increasing the efficiency of the discovery phase is to efficiently organize the semantics of the web services. This research work employs the utilization of Formal Concept Analysis (FCA) to organize the semantics of the web services by incorporating Lexicon Ontology. Also, Lexicon Ontology driven Concept Lattice (LOCL) framework which incorporates a novel match-making algorithm capable of discovering the web services based on different types of the user query is proposed. Intensive experimentation is performed to analyse the efficiency of the framework in comparison with significant literature works. It is found that the proposed LOCL framework outperforms the significant methods taken for study newline |
Pagination: | XXX,263P. |
URI: | http://hdl.handle.net/10603/515860 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 58.81 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.75 MB | Adobe PDF | View/Open | |
03_content.pdf | 101.28 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 396.46 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 532.42 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 909.22 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 1.47 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 2.03 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.46 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 771.76 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 118.77 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 136.41 kB | Adobe PDF | View/Open |
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