Modeling semantic compositionality of relational patterns

@article{Takase2016ModelingSC,
  title={Modeling semantic compositionality of relational patterns},
  author={Sho Takase and Naoaki Okazaki and Kentaro Inui},
  journal={Eng. Appl. of AI},
  year={2016},
  volume={50},
  pages={256-264}
}
Vector representation is a common approach for expressing the meaning of a relational pattern. Most previous work obtained a vector of a relational pattern based on the distribution of its context words (e.g., arguments of the relational pattern), regarding the pattern as a single ‘word’. However, this approach suffers from the data sparseness problem, because relational patterns are productive, i.e., produced by combinations of words. To address this problem, we propose a novel method for… CONTINUE READING