Model advertising slogan selection system using collective wisdom on the web
Model advertising slogan selection system using collective wisdom on the web
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DOI：
10.1109/scis-isis.2014.7044668
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发表时间：
2014-02
期刊：
影响因子：
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通讯作者：
Hiroaki Yamane;M. Hagiwara
中科院分区：
文献类型：
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作者：
Hiroaki Yamane;M. Hagiwara
对网络广告的需求的增加导致了开发针对在线个人的个性化广告的需求的相应增加。我们提出了一个自动化的广告口号选择系统，可以满足这一要求。许多顾客的评论和意见都可以在网上购物网站上公开获得。该系统利用内容挖掘技术从网络中提取有利的报告，并将数据整理成特定的知识表示结构，以提高目标产品的优势。对于一个特定的业务，所提出的系统首先提取元组，由元素表示的知识表示，从每个用户写的评论。然后，使用基于频率的方法和情感语料库来选择这些元组。随后，对于每个元组，使用神经网络从广告口号语料库中选择广告口号。为了验证，我们使用的数据从电子商务网站的酒店，以评估我们的系统的两个方面（即，质量的选择元组和广告口号）。实验结果表明，当给定的数据足够时，该系统可以提取合适的元组。它还可以检索口号，即使它们的含义是错综复杂的。
Increased demand for web advertising has resulted in a corresponding increase in the need to develop personalized advertisements targeted at individuals online. We propose an automated advertising slogan selection system that can satisfy this requirement. Many customer reviews and comments are available publicly on online shopping sites. The proposed system uses content mining to extract favorable reports from the web and arranges the data into a specific knowledge representation structure to improve the advantage of the target product. For a particular business, the proposed system first extracts tuples, composed of elements that express the knowledge representation from each user-written review. Then, these tuples are selected using a frequency-based approach and emotion corpus. Subsequently, for each tuple, advertising slogans are chosen from the advertising slogan corpora using a neural network. For verification, we used data from an electronic commerce website for hotels to evaluate two aspects of our system (namely, quality of selected tuples and advertising slogans). The results of the experiments confirm that the proposed system can extract suitable tuples when the given data are sufficient. It can also retrieve slogans even when their meanings are convoluted.