Due to the increasing number of available web services, discovering the best service that matches a user requirement is still a challenge. In most cases the discovery system returns a set of very similar services and sometimes it is unable to find results for some complex queries. Therefore, integrating web service discovery and composition, taking into account the diversity of discovered results, in a unified way is still a big issue for web services. In this paper, we propose a novel service ranking algorithm for diversifying web services discovery results in order to minimize the redundancy in the search results. This algorithm chooses a set of selected web services based on relevancy, service diversity and service density. We also propose a new method to generate service dependency network using the Formal Concept Analysis (FCA) framework. The generated graph is used to select the composition of discovered web services set. Experimental results show that our method performs better than others baseline approaches.
In semantic web-based framework, the build of philosophy is utilized to look comes about by relevant that implies of input inquiry or maybe than catchphrase coordinating. From the examination writing, there shows up to be a need for a apparatus which may provide a basic interface for complicate in quiries in dialect that may recover the domain-specific information from the transcendentalism. This examination paper proposes an IRSCSD framework (Data recovery framework for designing science space) as an reply. This method offers progressed questioning and browsing of organized data with look comes about mechanically total and rendered specifically in an exceedingly steady client-interface, in this manner diminishing the manual exertion of clients. So, the most objective of this examination is fashion and advancement of phonetics web-based framework for bunch activity transcendentalism towards domain-specific recovery back. Strategy taken after could be a piecemeal investigation that includes the ensuing stages. First Arrange includes the arranging of system for phonetics web-based framework. Moment organize builds the encapsulation for the system victimization Protégé instrument. Third Arrange bargains with the dialect address transformation into SPARQL look dialect victimization Python-fundamentally based address system.
The number of community detection algorithms is growing continuously adopting a topological based approach to discover optimal subgraphs or communities. In this paper, we propose a new method combining both topology and semantic to evaluate and rank community detection algorithms. To achieve this goal we consider a probabilistic topic based approach to define a new measure called semantic divergence of communities. Combining this measure with others related to prior knowledge, we compute a score for each algorithm to evaluate the effectiveness of its communities and propose a ranking method. We have evaluated our approach considering communities of real web services.
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