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» Contextual Ranking of Keywords Using Click Data
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KDD
2009
ACM
248views Data Mining» more  KDD 2009»
15 years 4 months ago
PSkip: estimating relevance ranking quality from web search clickthrough data
1 In this article, we report our efforts in mining the information encoded as clickthrough data in the server logs to evaluate and monitor the relevance ranking quality of a commer...
Kuansan Wang, Toby Walker, Zijian Zheng
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
16 years 7 days ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
SIGCOMM
2012
ACM
13 years 2 months ago
Measuring and fingerprinting click-spam in ad networks
Advertising plays a vital role in supporting free websites and smartphone apps. Click-spam, i.e., fraudulent or invalid clicks on online ads where the user has no actual interest ...
Vacha Dave, Saikat Guha, Yin Zhang
SIGMOD
2011
ACM
219views Database» more  SIGMOD 2011»
14 years 2 months ago
Context-sensitive ranking for document retrieval
We study the problem of context-sensitive ranking for document retrieval, where a context is defined as a sub-collection of documents, and is specified by queries provided by do...
Liang Jeff Chen, Yannis Papakonstantinou
ICDT
2007
ACM
126views Database» more  ICDT 2007»
15 years 6 months ago
Combining Incompleteness and Ranking in Tree Queries
Abstract. In many cases, users may want to consider incomplete answers to their queries. Often, however, there is an overwhelming number of such answers, even if subsumed answers a...
Benny Kimelfeld, Yehoshua Sagiv