Contextual web searches in Facebook using learning materials and discussion messages

The web is nowadays one of the main information sources, and information search is an important area in which many advances have been registered. One approach to improve web search results is to consider contextual information. Usually, information about context has been provided through user logs on previous searches or the monitoring of clicks on first results, but different approaches can be used in specific environments. In a web based learning environment, existing documents and exchanged messages could provide contextual information. So, the main goal of this work is to provide a contextual web search engine based on shared documents and messages posted in a social network used for collaborative learning. Contextual search is provided through query expansion using learning documents (material provided by the teacher) and discussion messages (posts, links and comments that result from the participants’ interactions). A prototype was implemented and used in a learning scenario to acquire the context in a learning community. The proposed approach makes the context acquisition faster and more dynamic as it considers an automatic approach over text processing of documents and discussions. In addition, the results of the query engine with and without the contextual information were compared and the proposed approach using contextual information showed improvements in the precision of the results.