If sufficient attention is not paid to the information models on which Learning Platforms are based the ability to deliver rich functionality is hindered. This paper describes the...
Many of the recently proposed algorithms for learning feature-based ranking functions are based on the pairwise preference framework, in which instead of taking documents in isola...
Vitor R. Carvalho, Jonathan L. Elsas, William W. C...
Ubiquitous computing environment requirement needs information sharing of sensors based on sensor network technology, situation-aware and determination functions and other related...
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
Abstract. Emergence--macro-level effects from micro-level causes--is at the heart of the conflict between reductionism and functionalism. How can there be autonomous higher level l...