Browsing by Author "Chanda, J."

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    An improved web page recommendation system using partitioning and web usage mining
    (Association for Computing Machinery acmhelp@acm.org, 2015) Chanda, J.; Annappa, B.
    There are different types of hypertext documents available on the Internet. Accessing relevant information and serving useful information to the user from the Internet has become a complex and expensive task. To make this process simpler, one of the widely used recommendation systems is item based collaborative filtering recommendation system which predicts web pages based on the browsing activity of the user on the Internet and recommends web pages as per their interests. There are certain challenges in these systems like sparsity and scalability, the proposed approach overcomes these problems. The proposed approach uses weighted kmean clustering instead of simple k-mean clustering and the obtained clusters are partitioned on the basis of similarity which helps in reducing the processing time of recommendation generation. Clustering and partitioning enhances the existing item based collaborative filtering recommendation system. The MovieLens data set is used for demonstrating the proposed approach. The performance of the proposed approach is evaluated using various metrics. The result shows that the proposed approach is 30% efficient in terms of root mean square error and 21% effective in respect of mean absolute error analysis and the accuracy measures factors like precision, recall and F-measure are found to have higher values than the existing item based collaborative filtering recommendation systems. © 2015 ACM.
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    An improved web page recommendation system using partitioning and web usage mining
    (2015) Chanda, J.; Annappa, B.
    There are different types of hypertext documents available on the Internet. Accessing relevant information and serving useful information to the user from the Internet has become a complex and expensive task. To make this process simpler, one of the widely used recommendation systems is item based collaborative filtering recommendation system which predicts web pages based on the browsing activity of the user on the Internet and recommends web pages as per their interests. There are certain challenges in these systems like sparsity and scalability, the proposed approach overcomes these problems. The proposed approach uses weighted kmean clustering instead of simple k-mean clustering and the obtained clusters are partitioned on the basis of similarity which helps in reducing the processing time of recommendation generation. Clustering and partitioning enhances the existing item based collaborative filtering recommendation system. The MovieLens data set is used for demonstrating the proposed approach. The performance of the proposed approach is evaluated using various metrics. The result shows that the proposed approach is 30% efficient in terms of root mean square error and 21% effective in respect of mean absolute error analysis and the accuracy measures factors like precision, recall and F-measure are found to have higher values than the existing item based collaborative filtering recommendation systems. � 2015 ACM.
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    Transformation framework for consistent evolution of uml behavioral elements into BPMN design element
    (Springer New York, 2013) Chanda, J.; Kanjilal, A.; Sengupta, S.; Bhattacharya, S.
    There are many software products that have been developed in the object-oriented paradigm. To incorporate the positive aspects of service-oriented paradigm (SOA) and address the issues related to increasing size and complexity of software products, they need to be evolved to service-oriented domain. There are some proven Object Oriented (OO) Design Tools that can be used for Service Oriented Application design incorporating both the behavioral and structural aspects in a seamless, consistent evolution that can be made from object oriented to service oriented domain. In this chapter, we concentrate on the evolution process of behavioral aspect of design from OO to SOA. Business Process Modeling Notation (BPMN) has become the de-facto standard for modeling business process on a conceptual level. Business processes are an integral part of service-oriented architecture. In service-oriented applications Use cases needs to be ordered along business processes. Business Processes visualize global control-flow across Use cases. Therefore, use of a business process language to visualize the dependencies among different use cases is of high importance. Use case diagram along with activity diagrams represents the behavioral aspect of a system in the analysis phase of an object-oriented system. To enable modeling the relationship among different behavioral aspects and evolve from object oriented domain to service oriented domain, a formal approach would help in establishing the foundation. In order to do that, in this work, we propose a formal framework, FAM (Formalized analysis model), which is a set of grammar based formalized Use case and Activity diagram elements of UML and a framework for verification of the diagrams, which includes syntactic correctness and requirement traceability. Along with that, we also propose FAM2BP (Formalized Analysis Model to Business Process) for transformation of Formalized Analysis Model (FAM) of object-oriented systems into BPMN process for SOA application using a set of rules that will help in generating business processes for SOA application directly from object oriented analysis models. This model would help in a consistent evolution of software development paradigms from Object Oriented to Service Oriented systems. © 2014 Springer Science+Business Media New York. All rights are reserved.