Automatic generation of document semantics for the e-science Knowledge Grid

This paper proposes an approach to automatically generate semantics for scientific e-documents, and presents its applications in e-document understanding, question answering and question refinement. The approach uses not only keywords and their relations in e-documents, but also the implied meaning of co-occurred keywords that is hard to be exploited, represented and derived by previous semantic representation approaches. The proposed approach facilitates automatic construction, composition, decomposition and derivation of semantics at different granularity levels, which lay the basis for realizing intelligent services of the e-science Knowledge Grid.