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» Ranking Retrieval Systems with Partial Relevance Judgements
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GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
16 years 18 days 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
16 years 19 days 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
16 years 6 days 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 7 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
16 years 7 hour 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...