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arXiv · 1712.08353

Relevance Score of Triplets Using Knowledge Graph Embedding - The Pigweed Triple Scorer at WSDM Cup 2017

Vibhor Kanojia·Riku Togashi·Hideyuki Maeda
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Abstract

Collaborative Knowledge Bases such as Freebase and Wikidata mention multiple professions and nationalities for a particular entity. The goal of the WSDM Cup 2017 Triplet Scoring Challenge was to calculate relevance scores between an entity and its professions/nationalities. Such scores are a fundamental ingredient when ranking results in entity search. This paper proposes a novel approach to ensemble an advanced Knowledge Graph Embedding Model with a simple bag-of-words model. The former deals with hidden pragmatics and deep semantics whereas the latter handles text-based retrieval and low-level semantics.

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Vibhor Kanojia, Riku Togashi, Hideyuki Maeda. 2017-12-22. Relevance Score of Triplets Using Knowledge Graph Embedding - The Pigweed Triple Scorer at WSDM Cup 2017. https://arxiv.org/abs/1712.08353

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