Association for Computing Machinery
In this paper the authors propose Fria, a fast and robust instance alignment framework across two independently built Knowledge Bases (KBs). Their objective is two-fold: to design an effective instance similarity measure and to build a fast and robust alignment framework. Specifically, Fria consists of two-phases. Fria first achieves high-precision alignment for seed matches which have strong evidence for aligning. To obtain high-recall alignment, Fria then divides non-matched instances according to the types identified from seeds, and gives additional chances to the same-typed instances to be matched.