Abstract
We present an approach to diversify entity search by utilizing semantics present and inferred from the initial entity search results. Our approach makes use of ontologies and independent component analysis of the entity descriptions to reveal direct and latent semantic connections between the entities present in the initial search results. The semantic connections are then used to sample a set of diverse entities. We empirically demonstrate the performance of our approach through retrieval experiments that use a real-world dataset composed from four entity databases. The results indicate that our approach significantly improves both diversity and effectiveness of entity search.
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