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» Swarming to rank for information retrieval
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VLDB
2004
ACM
129views Database» more  VLDB 2004»
14 years 1 months ago
Probabilistic Ranking of Database Query Results
We investigate the problem of ranking answers to a database query when many tuples are returned. We adapt and apply principles of probabilistic models from Information Retrieval f...
Surajit Chaudhuri, Gautam Das, Vagelis Hristidis, ...
SIGIR
2009
ACM
14 years 2 months ago
Reciprocal rank fusion outperforms condorcet and individual rank learning methods
Reciprocal Rank Fusion (RRF), a simple method for combining the document rankings from multiple IR systems, consistently yields better results than any individual system, and bett...
Gordon V. Cormack, Charles L. A. Clarke, Stefan B&...
ECIR
2008
Springer
13 years 9 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...
CORR
2010
Springer
141views Education» more  CORR 2010»
13 years 7 months ago
A database approach to information retrieval: The remarkable relationship between language models and region models
In this report, we unify two quite distinct approaches to information retrieval: region models and language models. Region models were developed for structured document retrieval....
Djoerd Hiemstra, Vojkan Mihajlovic
SIGECOM
2005
ACM
93views ECommerce» more  SIGECOM 2005»
14 years 1 months ago
Ranking systems: the PageRank axioms
This paper initiates research on the foundations of ranking systems, a fundamental ingredient of basic e-commerce and Internet Technologies. In order to understand the essence and...
Alon Altman, Moshe Tennenholtz