Mindnet
MindNet is the name of several automatically acquired databases of lexico-semantic relations[clarification needed] developed by members of the Natural Language Processing Group at Microsoft Research during the 1990s.[1][2][3] It is considered one of the world's largest lexicons and databases that could make automatic semantic descriptions along with WordNet, FrameNet, HowNet, and Integrated Linguistic Database.[4] It is particularly distinguished from WordNet by the way it was created automatically from a dictionary.[5]
MindNet was designed to be continuously extended. It was first built out of the Longman Dictionary of Contemporary English (LDOCE) and later included American Heritage and the full text of Microsoft Encarta.[6] The system can analyze linguistic representations of arbitrary text.[6] The underlying technology is based on the same parser used in the Microsoft Word grammar checker and was deployed in the natural language query engine in Microsoft's Encarta 99 encyclopedia.[7]
References
- ↑ Montemagni, S.; L. Vanderwende (1992). "Structural Patterns vs. string patterns for extracting semantic information from dictionaries". Proceedings of COLING92: 546–552.
- ↑ Dolan, William B., L. Vanderwende, and S. Richardson. (1993). "Automatically Deriving Structured Knowledge Bases from On-line Dictionaries". Proceedings of the Pacific Association for Computational Linguistics.
- ↑ Dolan, William B., L. Vanderwende, and S. Richardson (1993). "Combining Dictionary-based and Example-based Methods for Natural Language Analysis". Proceedings of the Fifth International Conference on Theoretical and Methodological Issues in Machine Translation: 69–79.
- ↑ Chan, Sin-Wai (2015). Routledge Encyclopedia of Translation Technology. Oxon: Routledge. pp. 430. ISBN 9780415524841.
- ↑ Ågotnes, Thomas (2011). Stairs 2010: Proceedings of the Fifth Starting AI Researchers' Symposium. Amsterdam: IOS Press. pp. 201. ISBN 9781607506751.
- ↑ 6.0 6.1 Allan, Keith (2009). Concise Encyclopedia of Semantics. Oxford: Elsevier Ltd.. pp. 493. ISBN 9780080959689.
- ↑ Buderi, Robert (2000). Engines of Tomorrow. Simon and Schuster. p. 358. ISBN 9780684839004. https://archive.org/details/enginesoftomorro00bude.
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