Papers with recommending citations
Content-Based Citation Recommendation (N18-1)
Copied to clipboard
| Challenge: | Existing citation recommendation systems rely on information of query documents such as author names and publication venue. |
| Approach: | They propose a content-based method for recommending citations in academic paper drafts . they embed a given query document into a vector space and use its nearest neighbors as candidates . |
| Outcome: | The proposed method outperforms published methods on PubMed and DBLP datasets without metadata. |
SymTax: Symbiotic Relationship and Taxonomy Fusion for Effective Citation Recommendation (2024.findings-acl)
Copied to clipboard
| Challenge: | Existing recommendations focus on local context or global context but fail to consider actual human citation behaviour. |
| Approach: | They propose a recommendation architecture that considers both local and global contexts . they use hyperbolic separation to compute query-candidate similarity . |
| Outcome: | The proposed framework performs better on a large dataset with 8.27 million citation contexts . it learns to embed the infused taxonomies in the hyperbolic space and computes similarity . |