Natural language generation for sponsored-search advertisements
Proceedings of the 9th ACM conference on Electronic commerce
Automatic generation of bid phrases for online advertising
Proceedings of the third ACM international conference on Web search and data mining
Bid generation for advanced match in sponsored search
Proceedings of the fourth ACM international conference on Web search and data mining
Ad retrieval systems in vitro and in vivo: knowledge-based approaches to computational advertising
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Micropinion generation: an unsupervised approach to generating ultra-concise summaries of opinions
Proceedings of the 21st international conference on World Wide Web
Automatic generation of listing ads by reusing promotional texts
Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business
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Products, services or brands can be advertised alongside the search results in major search engines, while recently smaller displays on devices like tablets and smartphones have imposed the need for smaller ad texts. In this paper, we propose a method that produces in an automated manner compact text ads (promotional text snippets), given as input a product description webpage (landing page). The challenge is to produce a small comprehensive ad while maintaining at the same time relevance, clarity, and attractiveness. Our method includes the following phases. Initially, it extracts relevant and important n-grams (keywords) given the landing page. The keywords reserved must have a positive meaning in order to have a call-to-action style, thus we attempt sentiment analysis on them. Next, we build an Advertising Language Model to evaluate phrases in terms of their marketing appeal. We experiment with two variations of our method and we show that they outperform all the baseline approaches.