2 research outputs found
Predicting Relevance Scores for Triples from Type-Like Relations using Neural Embedding - The Cabbage Triple Scorer at WSDM Cup 2017
The WSDM Cup 2017 Triple scoring challenge is aimed at calculating and
assigning relevance scores for triples from type-like relations. Such scores
are a fundamental ingredient for ranking results in entity search. In this
paper, we propose a method that uses neural embedding techniques to accurately
calculate an entity score for a triple based on its nearest neighbor. We strive
to develop a new latent semantic model with a deep structure that captures the
semantic and syntactic relations between words. Our method has been ranked
among the top performers with accuracy - 0.74, average score difference - 1.74,
and average Kendall's Tau - 0.35.Comment: Triple Scorer at WSDM Cup 2017, see arXiv:1712.0808
Overview of the Triple Scoring Task at the WSDM Cup 2017
This paper provides an overview of the triple scoring task at the WSDM Cup
2017, including a description of the task and the dataset, an overview of the
participating teams and their results, and a brief account of the methods
employed. In a nutshell, the task was to compute relevance scores for
knowledge-base triples from relations, where such scores make sense. Due to the
way the ground truth was constructed, scores were required to be integers from
the range 0..7. For example, reasonable scores for the triples "Tim Burton
profession Director" and "Tim Burton profession Actor" would be 7 and 2,
respectively, because Tim Burton is well-known as a director, but he acted only
in a few lesser known movies.
The triple scoring task attracted considerable interest, with 52 initial
registrations and 21 teams who submitted a valid run before the deadline. The
winning team achieved an accuracy of 87%, that is, for that fraction of the
triples from the test set (which was revealed only after the deadline) the
difference to the score from the ground truth was at most 2. The best result
for the average difference from the test set scores was 1.50