| D15-1038 | completion impute missing facts by | embedding | knowledge graphs in vector spaces |
| H90-1008 | the second only does so if no | embedding | link exists at the current focus |
| J14-2006 | hidden in a cover text using the | embedding | algorithm , resulting in the |
| W06-0603 | marker presence and syntactic | embedding | structure to be strongly associated |
| C92-3137 | re-Evaluation of the attitude in the | embedding | attitude contexts . Thus , ill |
| D14-1167 | Zheng Abstract We examine the | embedding | approach to reason new relational |
| D15-1034 | relationships as translations in the | embedding | space , have shown promising |
| P14-1011 | learns how to transform semantic | embedding | space in one language to the |
| P15-1077 | Gaussian distributions on the | embedding | space . This encourages the model |
| S15-2085 | , word prior polarities , and | embedding | clusters . Using weighted Support |
| D15-1031 | KBs but also to be equal to the | embedding | vector computed from the text |
| D14-1012 | prototype approach , for utilizing the | embedding | features . The presented approaches |
| S14-2011 | provides dense , low-dimensional | embedding | for each fragment which allows |
| C80-1074 | Extract the variables J Is the | embedding | operator applied te the predicate |
| P13-1017 | model , in which bilingual word | embedding | is discriminatively learnt to |
| W03-2200 | directions for improving MT by | embedding | it in an environment of other |
| C92-2072 | thus , we would include multiple | embedding | constructions , poten - ACT , |
| D14-1062 | relevance for the in-domain task . By | embedding | our latent domain phrase model |
| P15-1009 | regularization terms to constrain the | embedding | task . We empirically evaluate |
| W15-2608 | based approach that uses word | embedding | features to recognize drug names |
