Difference between revisions of "JAIR Analogical Mapping (State of the art)"

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== References ==
 
== References ==
  
Lin, D. (1998). [http://www.cs.ualberta.ca/~lindek/papers/sim.pdf An information-theoretic definition of similarity]. ''Proceedings of the 15th International Conference on Machine Learning (ICML-98)'', Madison, WI, pp. 296-304.
+
Lin, D. (1998). [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.55.1832&rep=rep1&type=pdf An information-theoretic definition of similarity]. ''Proceedings of the 15th International Conference on Machine Learning (ICML-98)'', Madison, WI, pp. 296-304.
  
 
Turney, P.D. (2008), [http://jair.org/papers/paper2693.html The latent relation mapping engine: Algorithm and experiments], ''Journal of Artificial Intelligence Research (JAIR)'', 33, 615-655.
 
Turney, P.D. (2008), [http://jair.org/papers/paper2693.html The latent relation mapping engine: Algorithm and experiments], ''Journal of Artificial Intelligence Research (JAIR)'', 33, 615-655.

Revision as of 15:09, 25 January 2017

  • analogical mapping between two sets of words
  • 20 mapping problems: 10 science analogies, 10 common metaphors
  • typically about 7 words per set
  • available from JAIR
  • task described here

Sample question

Problem: Map {planet, attracts, revolves, sun, gravity, solar system, mass} to {revolves, atom, attracts, electromagnetism, nucleus, charge, electron}

Solution: {solar system -> atom, sun -> nucleus, planet -> electron, mass -> charge, attracts -> attracts, revolves -> revolves, gravity -> electromagnetism}

Table of results

Algorithm Reference for algorithm Reference for experiment Type Correct
LIN+POS Lin (1998) Turney (2008) WordNet-based 76.8%
human human Turney (2008) human 87.6%
LRME Turney (2008) Turney (2008) corpus-based 91.5%

References

Lin, D. (1998). An information-theoretic definition of similarity. Proceedings of the 15th International Conference on Machine Learning (ICML-98), Madison, WI, pp. 296-304.

Turney, P.D. (2008), The latent relation mapping engine: Algorithm and experiments, Journal of Artificial Intelligence Research (JAIR), 33, 615-655.