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...
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...
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...
Background: One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive unde...
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...