Explicit Semantic Ranking for Academic Search via Knowledge Graph Embedding
C. Xiong, R. Power, and J. Callan. Proceedings of the 26th International Conference on World Wide Web, page 1271--1279. Republic and Canton of Geneva, Switzerland, International World Wide Web Conferences Steering Committee, (2017)
This paper introduces Explicit Semantic Ranking (ESR), a new ranking technique that leverages knowledge graph embedding. Analysis of the query log from our academic search engine, SemanticScholar.org, reveals that a major error source is its inability to understand the meaning of research concepts in queries. To addresses this challenge, ESR represents queries and documents in the entity space and ranks them based on their semantic connections from their knowledge graph embedding. Experiments demonstrate ESR's ability in improving Semantic Scholar's online production system, especially on hard queries where word-based ranking fails.