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M.Tech / M.E / PhD Thesis | Computer Science | India | Volume 9 Issue 7, July 2020
Detection of Fake Online Reviews Using Machine Learning Techniques
Abstract: Innovations are evolving quickly. Old advancements are consistently being supplanted by new and complex ones. These new advancements are empowering individuals to have their work done effectively. Such an advancement of innovation is online commercial center. We can shop and reserve spot utilizing on the web sites. Nearly, all of us looks at audits before buying a few items or administrations. Henceforth, online audits have become an extraordinary wellspring of notoriety for the organizations. Likewise, they have huge effect on notice and advancement of items and administrations. With the spread of online commercial center, counterfeit online surveys are getting incredible matter of concern. Individuals can make bogus audits for advancement of their own items that hurts the real clients. Additionally, serious organizations can attempt to harm every others notoriety by giving phony negative audits. Scientists have been reading about numerous methodologies for recognition of these phony online audits. A few methodologies are audit content put together and some are based with respect to conduct of the client who is posting surveys. Content put together investigation centers with respect to what is composed on the audit that is the content of the survey where client conduct put together technique centers with respect to nation, ip-address, number of posts of the commentator and so forth. The greater part of the proposed approaches are directed order models. Scarcely any scientists, additionally have worked with semi-directed models. Semi-administered techniques are being presented for absence of solid naming of the surveys.
Keywords: fake reviews, support vector machine classifier
Edition: Volume 9 Issue 7, July 2020,
Pages: 1796 - 1798