Paper: Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases

ACL ID D14-1044
Title Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

Much work in recent years has gone into the construction of large knowledge bases (KBs), such as Freebase, DBPedia, NELL, and YAGO. While these KBs are very large, they are still very incomplete, ne- cessitating the use of inference to fill in gaps. Prior work has shown how to make use of a large text corpus to augment ran- dom walk inference over KBs. We present two improvements to the use of such large corpora to augment KB inference. First, we present a new technique for combin- ing KB relations and surface text into a single graph representation that is much more compact than graphs used in prior work. Second, we describe how to incor- porate vector space similarity into random walk inference over KBs, reducing the fea- ture sparsity inherent in using surface text. This allows us to co...