For associations and people with a profound social, political, or monetary Sinterest in keeping up and fortifying their clout and notoriety, Twitter has become a goldmine. Sentiment analysis is the way toward characterizing and classifying the considerations and sentiments communicated in a source record. By performing this assessment investigation in a meticulous space, it is feasible to decide the force of area data on notion order. For feeling examination order, the proposed system utilizes the calculations Support Vector Regression (SVR), Decision Trees (DTs), and Random Forest (RF). The real execution of this structure depends on a twitter dataset unveiled by the NLTK corpora devices. The proposed approach will precisely identify ordinal relapse utilizing AI procedures.
Plagiarism is a problem that is becoming more prevalent as technology advances and the use of computer systems grows in comparison to previous generations. Plagiarism is the unauthorized use of another person’s work. Since manual plagiarism detection is difficult, this method should be automated. Plagiarism detection can be done using a variety of methods. Some of the research focuses on intrinsic plagiarism, while others focus on extrinsic plagiarism. Data mining is an area that can assist in both detecting plagiarism and improving the reliability of the operation. Plagiarism can be detected using a variety of data mining techniques. Text mining, clustering, bi-grams, tri-grams, and n-grams are some of the techniques that can assist with this. In this paper we will use the data mining techniques to increase the efficiency of detection of plagiarism.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.