The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Explicit Semantic Ranking for Academic Search via Knowledge Graph Embedding
Abstract
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.
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“Scholarly knowledge graph provides services such as intelligent contextual recommendation and ranking [113, 114] by discovering information from the scientific articles.”
From Scholarly knowledge graphs through structuring scholarly communication: a review (2023) · cites this paper as [113]
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Cites
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Cited by
Sorted by citations
A Survey on Knowledge Graphs: Representation, Acquisition, and Applications
Ji, S., Pan, S., Cambria, E., Marttinen, P., & Yu, P. S. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3070843 · Cited by 2,947
A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications
Cai, H., Zheng, V. W., & Chang, K. C.-C. (2018) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2018.2807452 · Cited by 2,034
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Sun, Z., Deng, Z.-H., Nie, J.-Y., & Tang, J. (2019) · arXiv · doi:10.48550/arxiv.1902.10197 · Cited by 1,414
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network
Nguyen, D. Q., Nguyen, T. D., Nguyen, D. Q., & Phung, D. (2018) · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers) · doi:10.18653/v1/n18-2053 · Cited by 923
Continual Relation Learning via Episodic Memory Activation and Reconsolidation
Han, X., Dai, Y., Gao, T., Lin, Y., Liu, Z., Li, P., Sun, M., & Zhou, J. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.573 · Cited by 104
Metadata
- Authors
- Xiong, C., Power, R., & Callan, J.
- Venue
- Proceedings of the 26th International Conference on World Wide Web
- Published
- 2017-04-03
- Pages
- 1271-1279
- Cited by
- 301
- References
- 2
- Funders
- Allen Institute for Artificial Intelligence
- NSF (IIS-1422676)
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