Abstract. We establish a generic theoretical tool to construct probabilistic bounds for algorithms where the output is a subset of objects from an initial pool of candidates (or mo...
Abstract. In this paper we propose an algorithm for personalized learning based on a user’s query and a repository of lecture subparts —i.e., learning objects— both are descr...
Learning Object Metadata (LOM) intends to facilitate the retrieval and reuse of learning material. However, the fastidious task of authoring them limits their use. Motivated by thi...
We study the problem of answering spatial queries in databases where objects exist with some uncertainty and they are associated with an existential probability. The goal of a thre...
Xiangyuan Dai, Man Lung Yiu, Nikos Mamoulis, Yufei...
This paper gives the SNAP and SPAN ontologies relating to recognizing variable vista spatial environments, namely, SNAPVis and SPANVis. It proposes that recognizing spatial environ...