Extending a Single-Document Summarizer to Multi-Document: a Hierarchical Approach
July 10, 2015 Β· Declared Dead Β· π International Workshop on Semantic Evaluation
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
LuΓs Marujo, Ricardo Ribeiro, David Martins de Matos, JoΓ£o P. Neto, Anatole Gershman, Jaime Carbonell
arXiv ID
1507.02907
Category
cs.IR: Information Retrieval
Cross-listed
cs.CL
Citations
17
Venue
International Workshop on Semantic Evaluation
Last Checked
4 months ago
Abstract
The increasing amount of online content motivated the development of multi-document summarization methods. In this work, we explore straightforward approaches to extend single-document summarization methods to multi-document summarization. The proposed methods are based on the hierarchical combination of single-document summaries, and achieves state of the art results.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Information Retrieval
R.I.P.
π»
Ghosted
π
π
Old Age
Neural Graph Collaborative Filtering
R.I.P.
π»
Ghosted
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
R.I.P.
π»
Ghosted
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
R.I.P.
π
404 Not Found
Graph Neural Networks for Social Recommendation
R.I.P.
π»
Ghosted
Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted