With a rapid increase in the volume of textual data on the Internet, extracting useful information through innovative text mining techniques has become crucial. In this context, terminology jargon in the literature related to text-mining creates ambiguity and has made it very difficult for researchers to focus in a specific direction and bring innovation. For example, review mining and opinion mining may have different applications, however, from a technical perspective, they are very similar. In this paper, we propose a classification of the text mining terminologies from the perspectives of technical and text-mining processes. The classification is based on a comprehensive literature survey and analysis. This research study presents a clear classification of text mining terminologies based on technical and text mining processes to resolve the issue of terminology jargon. By utilizing the proposed classification, researchers will be able to easily choose a specific direction instead of diverging amongst similar research problems, thereby, driving innovation. Further, the proposed classification will help advance and improve the overall research progress in all textmining related fields.