Finding OERs with Social-Semantic search

Social and semantic web can be complementary approaches searching web resources. This cooperative approach lets enable a semantic search engine to find accurate results and annotate web resources. This work develops the components of a Social-Semantic search architecture proposed by the authors to find open educational resources (OER). By means of metadata enrichment and logic inference, OER consumers get more precise results from general search engines. The Search prototype has been applied to find OER related with computers and engineering in a domain provided by OpenCourseWare materials from two universities, MIT and UTPL. The semantic search answers reasonably well the queta collected.