Opinion mining and Sentiment Analysis for contextual online-advertisement

A. Adamov, E. Adali
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引用次数: 10

Abstract

With rapid expansion of the Internet and increasing amount of time users spend online, the Internet evolves from entertainment environment towards highly dynamic and flexible business medium. Online advertisement has become one of the most successful business model for Internet environment. There are two major types of online advertisement: sponsored search and contextual display advertisement. This paper dedicated on contextual display advertisement. Generally, contextual advertisement implementations based on topical or keyword-based relevance approach. This study addresses the mechanism of advanced contextual advertisement based on opinion about specific topic within content of webpage. Use of Natural Language Processing and Sentiment Analysis aims to determine the writer's attitude towards particular topic as: positive, negative, or neutral. This approach helps to develop an advertisement system that is more content-sensitive and consequently has higher ROI of marketing.
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基于上下文的网络广告意见挖掘与情感分析
随着互联网的快速发展和用户上网时间的增加,互联网从娱乐环境演变为高度动态和灵活的商业媒介。网络广告已经成为互联网环境下最成功的商业模式之一。在线广告主要有两种类型:赞助搜索和上下文显示广告。本文主要研究上下文显示广告。通常,上下文广告的实现基于主题或基于关键字的相关性方法。本研究探讨网页内容中基于特定主题意见的高级情境广告机制。使用自然语言处理和情感分析的目的是确定作者对特定话题的态度:积极,消极或中立。这种方法有助于开发更具内容敏感性的广告系统,从而获得更高的营销ROI。
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