Notifying and filtering undesirable messages from online social network (OSN)

V. Kaveri, S. Gopal
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引用次数: 4

Abstract

Nowadays, we have a standard communicating source i.e. On-line Social Networks which are used to share, link and broadcast the substantial quantity of the data of human being's life. Constant and day-to-day communication infers the interchange of numerous kinds of information, comprising image, unrestricted text, video and audial information. A chief portion of social network content is established through the text of short, a notable sample are the mails eternally printed by users of OSN on specific private and public zones, named in common walls. This work recommends the system which imposes the screening process of content-based information and it is considered as a vital provision for OSN. This scheme permits the users of OSN to take a straight supervision on the messages which are mailed on the OSN user's walls. This is attained by the scheme of flexible rule-based, which permits a user to change the screening norms to be practiced to the OSN user's walls, and applied the tool of soft classifier i.e. Machine Learning spontaneously creating membership tags in provision of the process of filtering based on content.
通知和过滤来自在线社交网络的不良消息(OSN)
如今,我们有了一个标准的交流来源,即在线社交网络,它被用来分享、链接和传播人类生活中的大量数据。持续和日常的交流意味着各种信息的交换,包括图像、不受限制的文本、视频和音频信息。社交网络内容的主要部分是通过简短的文本建立起来的,一个值得注意的例子是OSN用户在特定的私人和公共区域永久打印的邮件,命名在公共墙上。本工作推荐了基于内容的信息筛选过程的系统,它被认为是OSN的重要提供。该方案允许OSN用户直接监督发送在OSN用户墙上的消息。这是通过灵活的基于规则的方案来实现的,该方案允许用户将要实践的筛选规范更改到OSN用户的墙上,并在提供基于内容的过滤过程中应用软分类器即机器学习工具自发地创建成员标签。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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