Developing an intelligent web-mining scheme that takes plain text, like a paragraph of a story, to generate multimodal learning materials from the internet could be of great help to both teachers and children with special needs.
Our research aims to develop intelligent solutions that can extract keywords from plain text and co-occurrence distribution between frequent terms and other terms in a sentence to define the relative importance of a term. Extracted keywords are used to search for the multimodal elements (texts, images and video clips) and other similar stories through search engine application programming interfaces (APIs). After the search operation, URL filtering, domain filtering, web content analysis-based filtering and image- and video-filtering methods are used to remove unwanted materials.
The proposed scheme can be used for extraction of learning material at any level, such as business process analysis and prediction model. Our baseline development is already accessible on the Mi-Children website.
Wagley, A., Akhter, P., Bhuiyan, M. and Dahal, K. Web Mining to Generate Multimodal Learning Materials for Children with Special Needs. IEEE Xplore based on 8th International Conference on Software Knowledge, Information, Management and Applications (accepted).