7 citations · 23 across the 4 of their papers we have counts for
4 papers
Probabilistic Belief Embedding for Knowledge Base Completion
Miao Fan, Qiang Zhou, Andrew Abel +2
This paper contributes a novel embedding model which measures the probability of each belief in a large-scale knowledge repository via simultaneously learn…
Large Margin Nearest Neighbor Embedding for Knowledge Representation
Miao Fan, Qiang Zhou, Thomas Fang Zheng +1
Traditional way of storing facts in triplets ({\it head\_entity, relation, tail\_entity}), abbreviated as ({\it h, r, t}), makes the knowledge intuitively displayed and easily acqu…
Jointly Embedding Relations and Mentions for Knowledge Population
Miao Fan, Kai Cao, Yifan He +1
This paper contributes a joint embedding model for predicting relations between a pair of entities in the scenario of relation inference. It differs from most stand-alone approache…
Learning Embedding Representations for Knowledge Inference on Imperfect and Incomplete Repositories
Miao Fan, Qiang Zhou, Thomas Fang Zheng
This paper considers the problem of knowledge inference on large-scale imperfect repositories with incomplete coverage by means of embedding entities and relations at the first att…