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KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 7 months 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
WWW
2011
ACM
13 years 2 months ago
Learning to rank with multiple objective functions
We investigate the problem of learning to rank for document retrieval from the perspective of learning with multiple objective functions. We present solutions to two open problems...
Krysta Marie Svore, Maksims Volkovs, Christopher J...
ECAGENTS
2001
Springer
127views ECommerce» more  ECAGENTS 2001»
13 years 12 months ago
User-Centered Agents for Structured Information Location
Abstract. This paper designs an electronic commerce system that integrates conventional electronic commerce services with contemporary WWW advantages, such as comprehensive coverag...
Xindong Wu, Daniel Ngu, Sameer Pradhan
JMLR
2010
141views more  JMLR 2010»
13 years 2 months ago
Pinview: Implicit Feedback in Content-Based Image Retrieval
This paper describes Pinview, a content-based image retrieval system that exploits implicit relevance feedback during a search session. Pinview contains several novel methods that...
Peter Auer, Zakria Hussain, Samuel Kaski, Arto Kla...
SIGIR
2012
ACM
11 years 9 months ago
An exploration of ranking heuristics in mobile local search
Users increasingly rely on their mobile devices to search local entities, typically businesses, while on the go. Even though recent work has recognized that the ranking signals in...
Yuanhua Lv, Dimitrios Lymberopoulos, Qiang Wu