Alignment of Multi-Cultural Knowledge Repositories

for various use cases such as document retrieval and question answering. However, independently
created repositories are inherently heterogeneous, reflecting their diverse origins. Thus, there is a
need to align concepts and entities across knowledge repositories. A limitation of prior work is the
assumption of high affinity between the repositories at hand, in terms of structure and terminology.
The goal of this dissertation is to develop methods for constructing and curating alignments between
multi-cultural knowledge repositories.
The first contribution is a system, ACROSS, for reducing the terminological gap between repositories.
The second contribution is two alignment methods, LILIANA and SESAME, that cope with structural
diversity. The third contribution, LAIKA, is an approach to compute alignments between dynamic repositories.
Experiments with a suite of Web-scale knowledge repositories show high Quality alignments. In addition,
the application benefits of LILIANA and SESAME are demonstrated by use cases in search and Exploration.