Sciweavers

ACL
2015

Encoding Distributional Semantics into Triple-Based Knowledge Ranking for Document Enrichment

8 years 23 days ago
Encoding Distributional Semantics into Triple-Based Knowledge Ranking for Document Enrichment
Document enrichment focuses on retrieving relevant knowledge from external resources, which is essential because text is generally replete with gaps. Since conventional work primarily relies on special resources, we instead use triples of Subject, Predicate, Object as knowledge and incorporate distributional semantics to rank them. Our model first extracts these triples automatically from raw text and converts them into real-valued vectors based on the word semantics captured by Latent Dirichlet Allocation. We then represent these triples, together with the source document that is to be enriched, as a graph of triples, and adopt a global iterative algorithm to propagate relevance weight from source document to these triples so as to select the most relevant ones. Evaluated as a ranking problem, our model significantly outperforms multiple strong baselines. Moreover, we conduct a task-based evaluation by incorporating these triples as additional features into document classification...
Muyu Zhang, Bing Qin, Mao Zheng, Graeme Hirst, Tin
Added 13 Apr 2016
Updated 13 Apr 2016
Type Journal
Year 2015
Where ACL
Authors Muyu Zhang, Bing Qin, Mao Zheng, Graeme Hirst, Ting Liu
Comments (0)