API Assisted Semantic Matching for Subjective Online Examination System
Correspondence Oluwatoyin Ayokunle Enikuomehin, Department of Computer Science, Faculty of Science, Lagos State University, Nigeria. Email:toyinenikuomehin@gmail.com Abstract: Introduction: Online examination systems exist as an attempt to expand the frontiers of learning and testing. This development has been limited by the strictness of the examination format vis a vis keyword match which are boundary defined. This constraint has led to poor adoption of online testing systems which are essential in handling the problem associated with large enrolment. Existing systems do not allow examiners to test for knowledge in ways that they seem due; similar to the conventional classroom testing system. Aim: To develop an Application Programming Interface (API) assisted semantic matching for subjective online examination system. The proposed system will take advantages of web resources to reduce time, cost and other constraints associated with location defined examination. Materials and Methods:We leveraged on the advances in Natural Language Processing and the success emerging from same and therefore remodelled the examination system against some known concepts in text summarization, term dependencies, semantic tagging and corporal buildup using a standalone global API for semantic interpretation of answers. Results: We improve the Levenshtein distance between two strings a, b using the triangular inequality to identify the relationship of two terms as applicable between questions and answers. The metric was coded in php with a MySQL supporting backend. The Levenshtein distance was denoted in php with the int levenshtein string $str1 string $str2 .The complexity of the algorithm is O(m*n) where n and m are the length of str1 and str2. Conclusion: The output of the research is a subjective examination system that allows the self grading of essay type question using a web based semantic API.