TY - GEN
T1 - Automated snippet generation for online advertising
AU - Thomaidou, Stamatina
AU - Lourentzou, Ismini
AU - Katsivelis-Perakis, Panagiotis
AU - Vazirgiannis, Michalis
PY - 2013/12/11
Y1 - 2013/12/11
N2 - 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.
AB - 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.
KW - Automated ad-text generation
KW - Online advertising
KW - Sponsored search
KW - Textual advertising
U2 - 10.1145/2505515.2507876
DO - 10.1145/2505515.2507876
M3 - Conference contribution
AN - SCOPUS:84889604251
SN - 9781450322638
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 1841
EP - 1844
BT - CIKM 2013 - Proceedings of the 22nd ACM International Conference on Information and Knowledge Management
T2 - 22nd ACM International Conference on Information and Knowledge Management, CIKM 2013
Y2 - 27 October 2013 through 1 November 2013
ER -