Open AccessDetecting Online Spams through Supervised Learning Techniques
Author(s) -
M. S. Minu,
Kamagiri Mounika,
N. Suhasini,
Bezawada Tejaswi
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a4252.119119
Subject(s) - counterfeit , computer science , affect (linguistics) , subject (documents) , control (management) , index (typography) , data science , artificial intelligence , world wide web , psychology , political science , communication , law
With more customers utilizing on the online review surveys to educate their administration basic leadership, assessment of reviews which economically affect the reality of organizations. Obviously, crafty people or gatherings have endeavored to manhandle or control online review spam to make benefits, etc, and that tricky recognition and counterfeit sentiment surveys is a subject of continuous research intrigue. In this paper, we clarify how supervised learning strategies are utilized to recognize online spam review surveys, preceding showing its utility utilizing an informational index of lodging reviews