Cross-language latent relational search: Mapping knowledge across languages

Nguyen Tuan Duc, Danushka Bollegala, Mitsuru Ishizuka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

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 clustering algorithm to capture the semantic similarity between paraphrased lexical patterns across languages. Experiments on Japanese-English datasets show that the proposed method achieves an MRR of 0.579 for CLRS task, which is comparable to the MRR of an existing monolingual LRS engine.

Original languageEnglish
Title of host publicationProceedings of the National Conference on Artificial Intelligence
Pages1237-1242
Number of pages6
Volume2
Publication statusPublished - 2011
Externally publishedYes
Event25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11 - San Francisco, CA
Duration: 2011 Aug 72011 Aug 11

Other

Other25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11
CitySan Francisco, CA
Period11/8/711/8/11

Fingerprint

Moon
Search engines
Earth (planet)
Satellites
Clustering algorithms
Semantics
Experiments

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Duc, N. T., Bollegala, D., & Ishizuka, M. (2011). Cross-language latent relational search: Mapping knowledge across languages. In Proceedings of the National Conference on Artificial Intelligence (Vol. 2, pp. 1237-1242)

Cross-language latent relational search : Mapping knowledge across languages. / Duc, Nguyen Tuan; Bollegala, Danushka; Ishizuka, Mitsuru.

Proceedings of the National Conference on Artificial Intelligence. Vol. 2 2011. p. 1237-1242.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Duc, NT, Bollegala, D & Ishizuka, M 2011, Cross-language latent relational search: Mapping knowledge across languages. in Proceedings of the National Conference on Artificial Intelligence. vol. 2, pp. 1237-1242, 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11, San Francisco, CA, 11/8/7.
Duc NT, Bollegala D, Ishizuka M. Cross-language latent relational search: Mapping knowledge across languages. In Proceedings of the National Conference on Artificial Intelligence. Vol. 2. 2011. p. 1237-1242
Duc, Nguyen Tuan ; Bollegala, Danushka ; Ishizuka, Mitsuru. / Cross-language latent relational search : Mapping knowledge across languages. Proceedings of the National Conference on Artificial Intelligence. Vol. 2 2011. pp. 1237-1242
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