基于社交数据集的虚假个人资料检测用于电影推广

Parul Parihar, Devanand, N. Kumar
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引用次数: 2

摘要

在当今竞争激烈的环境中,产品促销对于增加产品的销量至关重要。在这方面,在线推广媒介是至关重要的。产品推广,尤其是电影领域的产品推广存在虚假推广问题。电影被实体通过虚假评级来推广。这项工作主要集中在虚假配置文件的检测上。为了实现这种协同过滤,采用了预处理机制。工作演示将通过电影镜头数据集完成。所建议的方法是模块化的;这意味着整个工作将分为几个阶段。数据采集在第一阶段进行。收集数据集后,采用标称转换的预处理机制。将协同过滤与聚类相结合,确定电影镜头数据集中的假推广。还需要标称转换,因为推荐系统可能无法处理字符串值。通过分类精度,我们可以表明所提出的工作的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fake Profile Detection from the Social Dataset for Movie Promotion
Product promotion for increasing the sale of the product is critical in today’s competitive environment. Online medium of promotion is vital in this regard. Product promotion especially in the field of movies goes through fake promotion issues. Movies are promoted by the entities through fake rating. This work primary focuses on the detection of fake profiles. To accomplish this collaborative filtering with the pre-processing mechanism is used. Demonstration of work will be done through movie lense dataset. The nature of proposed approach is modular; this means entire work will be divided into phase. Data acquisition is performed in the first phase. After collecting the dataset, pre-processing mechanism is applied by using nominal conversion. Collaborative filtering is applied along with clustering to determine the fake promotion of within movie lense dataset. Nominal conversion is also required since recommender system may not able to handle string values. By the classification accuracy we can show the result of the proposed work.
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