International Journal of Science, Engineering and TechnologyAuthors: Assistant Professor Ms. Pooja, Ms. Neeharika Sengar
Abstract: This paper first describes the history of text mining technology, highlights its drawbacks, and then develops a text mining system based on natural language processing technology. The incessant generation of data has presented novel research obstacles because of its intricacy, variety, and magnitude. As a result, big data is gradually being acknowledged as a legitimate scientific discipline. An overview of the current state of big data science research is given in this article, with a focus on the theoretical underpinnings and applications of the field. Natural Language Processing (NLP) is one of the domains where data has a significant impact. The majority of NLP applications, including automatic speech recognition and machine translation, have not performed as well as they could in the past due to the proliferation of data. As such, a lot of NLP applications are regularly shifting from data-driven strategies to knowledge- and rule-based systems. On the other hand, gathered data that are based on vague design specifications or on forms that are not technically appropriate will be meaningless.
