Predicting ConceptNet Path Quality Using Crowdsourced Assessments of Naturalness

@article{Zhou2019PredictingCP,
  title={Predicting ConceptNet Path Quality Using Crowdsourced Assessments of Naturalness},
  author={Yilun Zhou and S. Schockaert and J. Shah},
  journal={The World Wide Web Conference},
  year={2019}
}
In many applications, it is important to characterize the way in which two concepts are semantically related. Knowledge graphs such as ConceptNet provide a rich source of information for such characterizations by encoding relations between concepts as edges in a graph. When two concepts are not directly connected by an edge, their relationship can still be described in terms of the paths that connect them. Unfortunately, many of these paths are uninformative and noisy, which means that the… Expand
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References

SHOWING 1-7 OF 7 REFERENCES
Modeling Relation Paths for Representation Learning of Knowledge Bases
The Three Sides of CrowdTruth
Solving and Explaining Analogy Questions Using Semantic Networks
Glove: Global Vectors for Word Representation
Freebase: a collaboratively created graph database for structuring human knowledge
Introduction to WordNet: An On-line Lexical Database