The progression of technology today has led to an increase in the production of digital content for various reasons. Digital content is now readily available in various formats, making it more accessible for different unprofessional users. The amount of this information has grown due to various factors. Extracting the needed content from this vast repository is a special task for users. This extraction is incredibly challenging in media files because they combine text, audio, animations, motion, and other elements. Extracting specific content is a very stimulating assignment for scholars due to the complexity of the data input. This has drawn immediate attention, necessitating a specific procedure to extract content more efficiently. Various procedures are available for extracting and grouping this type of input file, but none of them work well for every type of input; they may only perform effectively for a few sets of inputs. In the projected research a new framework is suggested to mine and group input information. This process is carried out through various stages, with each stage quality-checked against various parameters. Any errors or unwanted factors are identified and removed, and the remaining inputs are considered for the next steps. The final output performs well compared to other existing procedures; the investigational setup confirms this.