Sciweavers

12170 search results - page 36 / 2434
» Ranking Information in Networks
Sort
View
ICML
2009
IEEE
16 years 6 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 8 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
IRAL
2003
ACM
15 years 11 months ago
Temporal ranking for fresh information retrieval
In business, the retrieval of up-to-date, or fresh, information is very important. It is difficult for conventional search engines based on a centralized architecture to retrieve ...
Nobuyoshi Sato, Minoru Uehara, Yoshifumi Sakai
NAACL
2010
15 years 3 months ago
Constraint-Driven Rank-Based Learning for Information Extraction
Most learning algorithms for undirected graphical models require complete inference over at least one instance before parameter updates can be made. SampleRank is a rankbased lear...
Sameer Singh, Limin Yao, Sebastian Riedel, Andrew ...
WAOA
2007
Springer
158views Algorithms» more  WAOA 2007»
15 years 12 months ago
Deterministic Algorithms for Rank Aggregation and Other Ranking and Clustering Problems
We consider ranking and clustering problems related to the aggregation of inconsistent information. Ailon, Charikar, and Newman [1] proposed randomized constant factor approximatio...
Anke van Zuylen, David P. Williamson