Intelligent feature expansion of online text ads
作者： Hao Zheng , Jian Hu
DOI:
关键词:
摘要: Embodiments employ knowledge from network searches to enrich features useable describe an advertisement. Advertisement content may be segmented generate key phrases that are rank ordered based on a phrase's pointwise mutual information value with Ad keywords and term frequency-inverse document frequency (TF-IDF) scores. These employed plurality of query performed search result snippets. The snippets then analyzed ranked identify expansion having TF-IDF over given threshold. A subset these combined the used rebuild index for When is delivered client device, compared select advertisement provided device.
google.com.mx 参考文章(19)
Yang Jiangming, Feng Jing, Shuo Wang, Lei Zhang, Toward optimized query suggeston: user interfaces and algorithms ,(2007)
Christopher K. Harris, Mauritius A. R. Schmidtler, Effective multi-class support vector machine classification ,(2003)
Shumeet Baluja, Yushi Jing, Ranking of images and image labels ,(2008)
Benyu Zhang, Hua-Jun Zeng, Shuzhen Nong, Zheng Chen, Tarek Najm, Li Li, Ying Li, Advertising keyword cross-selling ,(2006)
Nick Koudas, Nilesh Bansal, Method and system for information discovery and text analysis ,(2008)
Blake Bookstaff, Method and system for automated intelligent electronic advertising ,(2005)
Vanessa Murdock, Vassilis Plachouras, Massimiliano Ciaramita, Method For Matching Electronic Advertisements To Surrounding Context Based On Their Advertisement Content ,(2007)
Mitsuaki Inaba, Yoshio Fukushige, Masako Nomoto, Yuji Kanno, Mitsuhiro Sato, Naohiko Noguchi, Keyword extracting system and text retrieval system using the same ,(1998)
Qianjin Hu, Yonghong Yang, Yuanhua Tang, Full text query and search systems and methods of use ,(2005)
Rosie Jones, Benjamin Rey, Tina Weyand, System and method for determining alternate search queries ,(2005)