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» Ranking Retrieval Systems with Partial Relevance Judgements
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GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
15 years 7 months ago
Swarming to rank for information retrieval
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...
CIKM
2009
Springer
15 years 7 months ago
Enabling multi-level relevance feedback on pubmed by integrating rank learning into DBMS
Background: Finding relevant articles from PubMed is challenging because it is hard to express the user’s specific intention in the given query interface, and a keyword query ty...
Hwanjo Yu, Taehoon Kim, Jinoh Oh, Ilhwan Ko, Sungc...
INEX
2007
Springer
15 years 7 months ago
Structured Document Retrieval, Multimedia Retrieval, and Entity Ranking Using PF/Tijah
CWI and University of Twente used PF/Tijah, a flexible XML retrieval system, to evaluate structured document retrieval, multimedia retrieval, and entity ranking tasks in the conte...
Theodora Tsikrika, Pavel Serdyukov, Henning Rode, ...
ECIR
2008
Springer
15 years 2 months ago
An Evaluation Measure for Distributed Information Retrieval Systems
This paper is concerned with the evaluation of distributed and peer-to-peer information retrieval systems. A new measure is introduced that compares results of a distributed retrie...
Hans Friedrich Witschel, Florian Holz, Gregor Hein...
SIGIR
2006
ACM
15 years 7 months ago
Adapting ranking SVM to document retrieval
The paper is concerned with applying learning to rank to document retrieval. Ranking SVM is a typical method of learning to rank. We point out that there are two factors one must ...
Yunbo Cao, Jun Xu, Tie-Yan Liu, Hang Li, Yalou Hua...