GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Finding advertising keywords on web pages
Proceedings of the 15th international conference on World Wide Web
A semantic approach to contextual advertising
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
The effect of title term suggestion on e-commerce sites
Proceedings of the 10th ACM workshop on Web information and data management
Learning document aboutness from implicit user feedback and document structure
Proceedings of the 18th ACM conference on Information and knowledge management
DASA: Dissatisfaction-oriented Advertising based on Sentiment Analysis
Expert Systems with Applications: An International Journal
Pattern based keyword extraction for contextual advertising
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Discovering coverage patterns for banner advertisement placement
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Exploratory class-imbalanced and non-identical data distribution in automatic keyphrase extraction
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
A semantic approach to recommending text advertisements for images
Proceedings of the sixth ACM conference on Recommender systems
Scripts as source of information to contextual video advertising
Proceedings of the 18th Brazilian symposium on Multimedia and the web
SmartAds: bringing contextual ads to mobile apps
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
Multi-label learning with millions of labels: recommending advertiser bid phrases for web pages
Proceedings of the 22nd international conference on World Wide Web
Real-time bidding for online advertising: measurement and analysis
Proceedings of the Seventh International Workshop on Data Mining for Online Advertising
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As the largest online marketplace, eBay strives to promote its inventory throughout the Web via different types of online advertisement. Contextually relevant links to eBay assets on third party sites is one example of such advertisement avenues. Keyword extraction is the task at the core of any contextual advertisement system. In this paper, we explore a machine learning approach to this problem. The proposed solution uses linear and logistic regression models learnt from human labeled data, combined with document, text and eBay specific features. In addition, we propose a solution to identify the prevalent category of eBay items in order to solve the problem of keyword ambiguity.