Preattentive processing of web advertising
Preattentive processing of web advertising
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Predicting clicks: estimating the click-through rate for new ads
Proceedings of the 16th international conference on World Wide Web
Online learning from click data for sponsored search
Proceedings of the 17th international conference on World Wide Web
Optimizing relevance and revenue in ad search: a query substitution approach
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
To swing or not to swing: learning when (not) to advertise
Proceedings of the 17th ACM conference on Information and knowledge management
Search advertising using web relevance feedback
Proceedings of the 17th ACM conference on Information and knowledge management
Online expansion of rare queries for sponsored search
Proceedings of the 18th international conference on World wide web
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Web advertising is one of the major sources of income for numerous search engines, news sites and non-commercial publishers. Textual ads, characterized by Sponsored Search (SS) and Content Match (CM), make up a significant portion of Web advertising. In SS, with limited information about ad contents, given a query, the challenge is to place relevant ads alongside organic search results. Organic search results are ranked based on their relevance to search keyword. However, SS results are not necessarily ranked purely based on relevance due to various factors influencing the ads overall ranking such as bid phrase and displayed position. The displayed ads may not relate to a user's information need. In this paper, a study associating ads and users, referred to as personalized advertising is proposed. User profiles are used as external knowledge to establish the relationship between the users and the ads.