Faculty of Computing
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Publication Embargo eGaz: Enhanced Search Engine for Gazette Publications(IEEE, 2022-07-18) Mendis, M. C. P; Perera, M. S. M; Karunaratne, J. M. P. D; Silva, K. K. S; Haddela, P. S; Gunarathne, D. AA government gazette is a periodical distribution that has been approved to distribute public or legitimate takes note. Presently, governments gazettes are published in the official website with the facility of downloading the individual files in portable document format. Even though these gazettes are categorized into a few types, individual gazettes contain diverse amount of material from various sectors of the government making it stiffer to the reader to search for their preferred apprises without reading the complete file. To address this problem as a possible convenient solution, Enhanced Search Engine for Gazette Publications was developed. The system is able to scrape gazette files from the official website, which is followed by a progression of text extraction, summarizing and clustering the extracted data and hoard them in a distributed system. With the use of the Content Search Engine, user could loop through any material issued over gazettes which would bring up filtered results from the extracted data. Similarly, users can read summarized reports of advertisements on job vacancies, examination details and results of examinations and could even filter them by relevant departments.Publication Embargo MOOCRec 2 for Humanities-Learning Style Based MOOC Recommender and Search Engine(IEEE, 2019-12-05) Fazuludeen, F; Vijayakumaran, G; Mahroof, Z. A; Kodagoda, N; Suriyawansa, KIntroduction of Massive Open Online Courses (MOOC) has a great impact on the e-learning sector. Further, MOOC platforms like Coursera, EdX, and Future Learn have made learning accessible to millions of people for free. Also, availability of such platforms has become a blessing and a burden to people since users cannot find the right courses that suits them due to the availability of similar topic of courses in different platforms. Moreover, MOOCRec Humanities is a curated search platform for these courses. Further, MOOCRec tries to address this problem by considering the learning style of user and matching them with the right courses. Additionally, the courses are mapped using VARK learning model. For the mapping purpose, course video styles and course practical content such as quizzes and reading materials are considered. In addition, users can search individual topics that can be covered in a course.Publication Embargo MoocRec: Learning styles-oriented MOOC recommender and search engine(IEEE, 2019-04-08) Aryal, S; Porawagama, A. S; Hasith, M. G. S; Thoradeniya, S. C; Kodagoda, N; Suriyawansa, KMassive Open Online Courses (MOOCs) are the new revolution in the field of e-learning, providing a large number of courses in different domains to a wide range of learners. Due to the availability of several MOOC providers (including edX, Coursera, Udacity, FutureLearn), a specific domain has multiple courses spread across these platforms that confuses a learner on selecting the most suitable course for him. It is a tedious manual task for the learner to browse through various courses before he finds the best course that meets his learning requirements and objectives. MoocRec is a unique learning styles-oriented system that recommends the most suitable courses to a learner from different MOOC platforms based on their learning styles and individual needs. The courses are recommended based on the mapping of Felder and Silverman learning styles with the standard video styles used in MOOC videos (including talking head, slide, tutorial/demonstration). MoocRec also allows the learners to search for courses using specific topics to provide an enhanced personalized learning environment. Results show that MoocRec is strongly reliable and can be used for personalized learning.