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Triple Scoring Using Paragraph Vector - The Gailan Triple Scorer at WSDM Cup 2017
In this paper we describe our solution to the WSDM Cup 2017 Triple Scoring
task. Our approach generates a relevance score based on the textual description
of the triple's subject and value (Object). It measures how similar (related)
the text description of the subject is to the text description of its values.
The generated similarity score can then be used to rank the multiple values
associated with this subject. We utilize the Paragraph Vector algorithm to
represent the unstructured text into fixed length vectors. The fixed length
representation is then employed to calculate the similarity (relevance) score
between the subject and its multiple values. Our experimental results have
shown that the suggested approach is promising and suitable to solve this
problem.Comment: Triple Scorer at WSDM Cup 2017, see arXiv:1712.0808