Cross-Language Latent Relational Search: Mapping Knowledge across Languages

Latent relational search (LRS) is a novel approach for mapping knowledge across two domains. Given a source domain knowledge concerning the Moon, “The Moon is a satellite of the Earth”, one can form a question {(Moon, Earth), (Ganymede, ?)} to query an LRS engine for new knowledge in the target domain concerning the Ganymede. An LRS engine relies on some supporting sentences such as “Ganymede is a natural satellite of Jupiter.” to retrieve and rank “Jupiter” as the first answer. This paper proposes cross-language latent relational search (CLRS) to extend the knowledge mapping capability of LRS from cross-domain knowledge mapping to cross-domain and cross-language knowledge mapping. In CLRS, the supporting sentences for the source pair might be in a different language with that of the target pair. We represent the relation between two entities in an entity pair by lexical patterns of the context surrounding the two entities. We then propose a novel hybrid lexical pattern c...

• Type: Journal
• Year: 2011
• Where: AAAI
• Authors: Nguyen Tuan Duc, Danushka Bollegala, Mitsuru Ishizuka
• Keywords: AAAI 2011, Intelligent Agents, Satellite Of Jupiter, Semantic Similarity, Target Domain