InteSearch: An intelligent linked data information access framework

Abstract

Information access over linked data requires to determine subgraph(s), in linked data’s underlying graph, that correspond to the required information need. Usually, an information access framework is able to retrieve richer information by checking of a large number of possible subgraphs. However, on the fly checking of a large number of possible subgraphs increases information access complexity. This makes an information access frameworks less effective. A large number of contemporary linked data information access frameworks reduce the complexity by introducing different heuristics but they suffer on retrieving richer information. Or, some frameworks do not care about the complexity. However, a practically usable framework should retrieve richer information with lower complexity. In linked data information access, we hypothesize that pre-processed data statistics of linked data can be used to efficiently check a large number of possible subgraphs. This will help to retrieve comparatively richer information with lower data access complexity. Preliminary evaluation of our proposed hypothesis shows promising performance.