Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Similarity analysis of service descriptions for efficient Web service discovery(Institute of Electrical and Electronics Engineers Inc., 2014) Kamath S․, S.; Ananthanarayana, V.S.Web services are currently one of the preferred ways for realizing Service Oriented Architectures in business systems. Due to this popularity and also due partly to the failure of the Universal Business Registry initiative, the number of published service descriptions openly available on the Web has increased by a large extent and hence, relevant service discovery as per user specification remains a challenge. In order to achieve more efficient discovery, we propose a crawler based system for gathering service descriptions available on the Web for building a scalable service repository. We apply similarity analysis techniques to the service descriptions after extracting features provided by the service descriptions and automatically generate relevant tags for each service. Using Agglomerative Hierarchical clustering, we cluster the tagged service descriptions and use the same tagging technique to generate tags for each cluster. For generating cluster tags, we take into account how well the tag represents the corresponding service in the cluster and how well the service itself represents the cluster it is in. The search domain for service discovery was significantly reduced by tagging & clustering and and we show that our system achieves good results. © 2014 IEEE.Item A service crawler framework for similarity based web service discovery(Institute of Electrical and Electronics Engineers Inc., 2015) Kamath S․, S.; Ananthanarayana, V.S.Due to the explosive growth in availability of Web services over the open Web and in heterogeneous sources in which they are available, discovering relevant web services for a given task continues to be challenging. In order to deal with these problems, a bottom-up approach based on finding published service descriptions for developing a web service discovery framework was proposed. We discuss in detail the service crawler employed to search and find published WSDL service descriptions on the Web. The service descriptions are semantically analyzed in order to improve efficiency of the discovery process as per user context during keyword search. Since the service crawler will periodically make repeated runs to find new service descriptions or to check the status of already crawled services, the framework is of an inherently dynamic nature. Hence, it is critical to keep track of various entities like visited URLs, already added services and successfully processed service descriptions to avoid rework when the service data set changes, for which an incremental change propagation strategy was incorporated. © 2014 IEEE.Item Change propagation based incremental data handling in a Web service discovery framework(Institute of Electrical and Electronics Engineers Inc., 2015) Kamath S․, S.; Ananthanarayana, V.S.Due to the explosive growth in availability of Web services over the open Web and the heterogeneous sources in which they are available, discovering relevant web services for a given task continues to be challenging. In order to deal with these problems, a bottom-up approach based on finding published service descriptions to automatically build a service repository for developing a web service discovery framework was proposed. This framework employs a Service Crawler to find published service descriptions on the Web. Since the service crawler will periodically make repeated runs to find new service descriptions or to check the continued availability of already crawled services, the framework is of an inherently dynamic nature. Hence, it is critical to keep track of various entities like visited URLs, already added & successfully processed service descriptions to avoid rework when the service data set changes. In order to cope with this problem, we developed a change propagation technique based on an event based state machine to incorporate an incremental processing strategy in this Web scale framework. © 2014 IEEE.