Objective type of Examination evaluation is easy in Computer world, but the descriptive type of question evaluation is more complex and there is no significant research has been taken place. So many descriptive type examinations like University Exams, GRE etc., have been conducting from long time which is being evaluated manually by sending these types of questions and answers to the experts. This kind of exams needs automatic evaluation instead of manual correction to bring accuracy and reduce the evaluation time. In this paper, authors propose CosInfo algorithm a new solution to the above problem which can evaluate the papers automatically. This algorithm implemented the feature clustering for evaluation purpose that calculate the similarity between two documents and cluster the relevant documents in to different groups. Proposed algorithm uses the expected information function and parts of speech in English grammar as parameters to cluster the data, and also builds a model to classify the testing documents using SVM classification to assess the degree of similarity which will help to award the marks automatically. Experimental results show that the proposed method obtains better and accurate results to allocate marks compared with manual evaluation.
The article that you are looking for is unavailable to public domain. The article is subjected to compliance with 2014-2015 IJCA scientific data guidelines. You might want to navigate the journal via the menu options provided in the left side of the screen. However, feel free to contact us anytime regarding any article which you are unable to find.
The article that you are looking for is unavailable to public domain. The article is subjected to compliance with 2014-2015 IJCA scientific data guidelines. You might want to navigate the journal via the menu options provided in the left side of the screen. However, feel free to contact us anytime regarding any article which you are unable to find.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.