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SIGIR
2006
ACM
14 years 1 months ago
Answering complex questions with random walk models
We present a novel framework for answering complex questions that relies on question decomposition. Complex questions are decomposed by a procedure that operates on a Markov chain...
Sanda M. Harabagiu, V. Finley Lacatusu, Andrew Hic...
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 8 months ago
How social structure and institutional order co-evolve beyond instrumental rationality
This study proposes an agent-based model where adaptively learning agents with local vision who are situated in the Prisoner’s Dilemma game change their strategy and location as...
Jae-Woo Kim
BMCBI
2008
139views more  BMCBI 2008»
13 years 7 months ago
Hierarchical structure of cascade of primary and secondary periodicities in Fourier power spectrum of alphoid higher order repea
Background: Identification of approximate tandem repeats is an important task of broad significance and still remains a challenging problem of computational genomics. Often there ...
Vladimir Paar, Nenad Pavin, Ivan Basar, Marija Ros...
BMCBI
2006
105views more  BMCBI 2006»
13 years 7 months ago
CRNPRED: highly accurate prediction of one-dimensional protein structures by large-scale critical random networks
Background: One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive unde...
Akira R. Kinjo, Ken Nishikawa
ICML
2010
IEEE
13 years 8 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos