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» Contextual Ranking of Keywords Using Click Data
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WWW
2010
ACM
15 years 4 months ago
Tracking the random surfer: empirically measured teleportation parameters in PageRank
PageRank computes the importance of each node in a directed graph under a random surfer model governed by a teleportation parameter. Commonly denoted alpha, this parameter models ...
David F. Gleich, Paul G. Constantine, Abraham D. F...
86
Voted
WSDM
2010
ACM
236views Data Mining» more  WSDM 2010»
15 years 7 months ago
Personalized Click Prediction in Sponsored Search
Sponsored search is a multi-billion dollar business that generates most of the revenue for search engines. Predicting the probability that users click on ads is crucial to sponsor...
Erick Cantú-Paz, Haibin Cheng
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
15 years 7 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
WWW
2008
ACM
15 years 10 months ago
Online learning from click data for sponsored search
Sponsored search is one of the enabling technologies for today's Web search engines. It corresponds to matching and showing ads related to the user query on the search engine...
Massimiliano Ciaramita, Vanessa Murdock, Vassilis ...
77
Voted
CIKM
2010
Springer
14 years 8 months ago
Online learning for recency search ranking using real-time user feedback
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohu...