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» Magnitude-preserving ranking algorithms
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SEBD
2008
177views Database» more  SEBD 2008»
15 years 7 months ago
Using PageRank in Feature Selection
Abstract. Feature selection is an important task in data mining because it allows to reduce the data dimensionality and eliminates the noisy variables. Traditionally, feature selec...
Dino Ienco, Rosa Meo, Marco Botta
TKDE
1998
184views more  TKDE 1998»
15 years 5 months ago
Supporting Ranked Boolean Similarity Queries in MARS
To address the emerging needs of applications that require access to and retrieval of multimedia objects, we are developing the Multimedia Analysis and Retrieval System (MARS) 29]...
Michael Ortega, Yong Rui, Kaushik Chakrabarti, Kri...
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 6 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
WAW
2004
Springer
150views Algorithms» more  WAW 2004»
15 years 11 months ago
Do Your Worst to Make the Best: Paradoxical Effects in PageRank Incremental Computations
d Abstract) Paolo Boldi† Massimo Santini‡ Sebastiano Vigna∗ Deciding which kind of visit accumulates high-quality pages more quickly is one of the most often debated issue i...
Paolo Boldi, Massimo Santini, Sebastiano Vigna
SAS
2010
Springer
140views Formal Methods» more  SAS 2010»
15 years 4 months ago
Multi-dimensional Rankings, Program Termination, and Complexity Bounds of Flowchart Programs
Abstract. Proving the termination of a flowchart program can be done by exhibiting a ranking function, i.e., a function from the program states to a wellfounded set, which strictl...
Christophe Alias, Alain Darte, Paul Feautrier, Lau...