Explicit Semantic Ranking for Academic Search via Knowledge Graph Embedding

@inproceedings{Xiong2017ExplicitSR,
  title={Explicit Semantic Ranking for Academic Search via Knowledge Graph Embedding},
  author={Chenyan Xiong and Russell Power and James P. Callan},
  booktitle={WWW},
  year={2017}
}
Highlight Information
This paper introduces Explicit Semantic Ranking (ESR), a new ranking technique that leverages knowledge graph embedding. [...] Key Result Experiments demonstrate ESR's ability in improving Semantic Scholar's online production system, especially on hard queries where word-based ranking fails.Expand Abstract

Citations

Publications citing this paper.
SHOWING 1-10 OF 73 CITATIONS

Exploring the Importance of Entities in Semantic Ranking

VIEW 5 EXCERPTS
CITES METHODS, BACKGROUND & RESULTS
HIGHLY INFLUENCED

Entity Set Search of Scientific Literature: An Unsupervised Ranking Approach

VIEW 11 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Word-Entity Duet Representations for Document Ranking

VIEW 8 EXCERPTS
CITES BACKGROUND & METHODS

A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications

VIEW 4 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

2017
2020

CITATION STATISTICS

  • 4 Highly Influenced Citations

  • Averaged 22 Citations per year from 2017 through 2019

  • 36% Increase in citations per year in 2019 over 2018

References

Publications referenced by this paper.
SHOWING 1-10 OF 29 REFERENCES

A Deep Relevance Matching Model for Ad-hoc Retrieval

VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Document Retrieval Using Entity-Based Language Models

VIEW 8 EXCERPTS
HIGHLY INFLUENTIAL

Entity Linking in Queries: Tasks and Evaluation

VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

Optimizing search engines using clickthrough data

VIEW 2 EXCERPTS
HIGHLY INFLUENTIAL

An Overview of Microsoft Academic Service (MAS) and Applications

VIEW 1 EXCERPT