Extracting IEEE LOM 9. 4 using Memetic Algorithm for Textual Learning Objects

Abstract

With the growing number of learning objects & their increasing use for learning, it is required to search the desired learning material in the least time. So it is needed to have the quality learning object. The quality of learning objects means they are tagged with correct & complete metadata. IEEE LOM set up a standard for uniformity of Meta data values. The IEEE LOM has 9 different categories for metadata. These categories are used to describe the learning object when filled with metadata values and in turn they are useful searching and understanding the learning object without actually opens it. IEEE LOM 9 category belongs to the classification and under this category, a important subcategory of IEEE LOM 9.4 lies which actually belongs to keywords of learning objects. This paper uses the memetic algorithm based approach to extract the keywords for each learning objects of different classes. The correct keywords strongly reflect the learning object class and in turn it is very useful for user's point of view to decide whether this is the learning object he is searching for.