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» Ranking Information in Networks
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84
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SIGIR
2009
ACM
15 years 8 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&...
115
Voted
SIGIR
2008
ACM
15 years 1 months ago
Efficient top-k querying over social-tagging networks
Online communities have become popular for publishing and searching content, as well as for finding and connecting to other users. User-generated content includes, for example, pe...
Ralf Schenkel, Tom Crecelius, Mouna Kacimi, Sebast...
ECML
2007
Springer
15 years 8 months ago
An Unsupervised Learning Algorithm for Rank Aggregation
Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as op...
Alexandre Klementiev, Dan Roth, Kevin Small
ICMLA
2009
14 years 11 months ago
Discovering Characterization Rules from Rankings
For many ranking applications we would like to understand not only which items are top-ranked, but also why they are top-ranked. However, many of the best ranking algorithms (e.g....
Ansaf Salleb-Aouissi, Bert C. Huang, David L. Walt...
IQIS
2005
ACM
15 years 7 months ago
Data quality inference
In the field of sensor networks, data integration and collaboration, and intelligence gathering efforts, information on the quality of data sources are important but are often not...
Raymond K. Pon, Alfonso F. Cardenas