A semi-automated framework for semantically annotating web content

Today's web is growing very fast and having a strong online presence is becoming critical for businesses. In contrast, websites in search results using traditional Search Engine Optimization (SEO) techniques became less effective in achieving the desired visibility. To overcome the limitations of traditional SEO, some recent trends are adopting the technologies of Semantic Web to annotate web content with Semantic Markup that can be understood by search engines. However, the balance between the accuracy of annotations and the automation level still under investigation. This research proposes a semi-automated framework that provides a high level of accurate annotations with minimum user interaction, based on Schema.org; a well-accepted ontology for ordinary things in life. The proposed framework aims to analyze the contents of web documents and extract the unique keywords and key phrases that best describe that content. Then, annotate those keywords and key phrases with the appropriate Schema.org vocabularies. This will reflect on the understanding level of the search engines to the web contents and accordingly a better visibility in the search results.