Detecting Automatically Generated Sentences with Grammatical Structure Similarity

Detection of automatically generated papers has been a new field of research. However, all current approaches are working at the document level and are unable to detect a small amount of generated text inside a large body of genuine written text. This paper will present the Grammatical Structure Similarity (GSS) measurement to detect sentences or short fragments from known generators. The proposed approach is tested against common machine learning methods, the ability to detect a modified generator is also tested.