Open AccessProceedings Article
Applying Graph-based Keyword Extraction to Document Retrieval
Youngsam Kim,Munhyong Kim,Andrew Cattle,Julia Otmakhova,Suzi Park,Hyopil Shin +5 more
- pp 864-868
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TLDR
A keyword extraction process, based on the PageRank algorithm, to reduce noise of input data for measuring semantic similarity and experimental results showed significantly improved document retrieval performance with this extraction process in place.Abstract:
This paper proposes a keyword extraction process, based on the PageRank algorithm, to reduce noise of input data for measuring semantic similarity. This paper will introduce several features related to implementation and discuss their effects. It will also discuss experimental results which showed significantly improved document retrieval performance with this extraction process in place.read more
Citations
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Proceedings ArticleDOI
DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
TL;DR: An end-to-end method called DivGraphPointer is presented for extracting a set of diversified keyphrases from a document that combines the advantages of traditional graph-based ranking methods and recent neural network-based approaches.
Journal ArticleDOI
Fast and Constrained Absent Keyphrase Generation by Prompt-Based Learning
TL;DR: The result shows that the proposed constrained absent keyphrase generation method can generate more consistent keyphrases, which can improve document retrieval performance, and with a non-autoregressive decoding manner, can speed up the absentKeyphrase generation by 8.67× compared with the autoregressive method.
Proceedings ArticleDOI
Hyperbolic Relevance Matching for Neural Keyphrase Extraction
TL;DR: A newhyperbolic matching model (HyperMatch) is designed to explore keyphrase extraction in hyperbolic space and outperforms the recent state-of-the-art baselines on six benchmark datasets.
Proceedings ArticleDOI
DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
TL;DR: DivGraphPointer as discussed by the authors combines the advantages of traditional graph-based ranking methods and recent neural network-based approaches to extract a set of diversified keyphrases from a document.
Proceedings ArticleDOI
Extraction of keyphrases from single document based on hierarchical concepts
Miroslav Smatana,Peter Butka +1 more
TL;DR: This paper provides modification of approaches for extraction of keyphrases from single textual document based on the hierarchical concepts created upon the text of particular document using FCA-based algorithm known as generalized one-sided concept lattice.
References
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