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» Mining advertiser-specific user behavior using adfactors
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KDD
2010
ACM
190views Data Mining» more  KDD 2010»
13 years 11 months ago
User browsing models: relevance versus examination
There has been considerable work on user browsing models for search engine results, both organic and sponsored. The click-through rate (CTR) of a result is the product of the prob...
Ramakrishnan Srikant, Sugato Basu, Ni Wang, Daryl ...
CIKM
2009
Springer
14 years 2 months ago
Exploring relevance for clicks
Mining feedback information from user click-through data is an important issue for modern Web retrieval systems in terms of architecture analysis, performance evaluation and algor...
Rongwei Cen, Yiqun Liu, Min Zhang, Bo Zhou, Liyun ...
KDD
2012
ACM
257views Data Mining» more  KDD 2012»
11 years 10 months ago
Aggregating web offers to determine product prices
Historical prices are important information that can help consumers decide whether the time is right to buy a product. They provide both a context to the users, and facilitate the...
Rakesh Agrawal, Samuel Ieong
KDD
2007
ACM
192views Data Mining» more  KDD 2007»
14 years 8 months ago
Active exploration for learning rankings from clickthrough data
We address the task of learning rankings of documents from search engine logs of user behavior. Previous work on this problem has relied on passively collected clickthrough data. ...
Filip Radlinski, Thorsten Joachims
ICDM
2008
IEEE
183views Data Mining» more  ICDM 2008»
14 years 1 months ago
Collaborative Filtering for Implicit Feedback Datasets
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track differe...
Yifan Hu, Yehuda Koren, Chris Volinsky