Context recognition is an important component of the common sense knowledge problem, which is one of the key research areas in the field of Artificial Intelligence. The paper develops a model of context recognition using the Internet as a knowledge base. The use of the Internet as a database for context recognition gives a context recognition model immediate access to a nearly infinite amount of data in a multiplicity of fields. Context is represented here as any textual description that is most commonly selected by a set of subjects to describe a given situation. The model input is based on any aspect of the situation that can be translated into text (such as: voice recognition, image recognition, facial expression interpretation, and smell identification). The research model is based on the streaming in text format of information that represents situations-Internet chats, e-mails, Shakespeare plays, or article abstracts. The comparison of the results of the algorithm with the results of human subjects yielded a very high agreement and correlation. The results showed there was no significant difference in the determination of context between the algorithm and the human subjects.