Papers Keyphrase Extraction

Etat de l'art des m\'ethodes d'apprentissage profond pour l'extraction automatique de termes-cl\'es (State of the art of deep learning methods for automatic keyphrase extraction )

Les termes-cl{\'e}s facilitent la recherche de documents dans de larges collections de donn{\'e}es. Le co{\^u}t d{'}annotation de document en termes-cl{\'e}s tr{\`e}s {\'e}lev{\'e}, c{'}est pourquoi les chercheurs s{'}in…

Glocal: Incorporating Global Information in Local Convolution for Keyphrase Extraction

Graph Convolutional Networks (GCNs) are a class of spectral clustering techniques that leverage localized convolution filters to perform supervised classification directly on graphical structures. While such methods mode…

DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases

Keyphrase extraction from documents is useful to a variety of applications such as information retrieval and document summarization. This paper presents an end-to-end method called DivGraphPointer for extracting a set of…

A Review of Keyphrase Extraction

Keyphrase extraction is a textual information processing task concerned with the automatic extraction of representative and characteristic phrases from a document that express all the key aspects of its content. Keyphras…

Inflo: News Categorization and Keyphrase Extraction for Implementation in an Aggregation System

The work herein describes a system for automatic news category and keyphrase labeling, presented in the context of our motivation to improve the speed at which a user can find relevant and interesting content within an a…

Keyphrase Extraction from Bengali Document using LSTM Recurrent Neural Network

Abstract—Keyphrases are single or multiple word phrases of a document which portrays the principal points of that document. These keyphrases help readers to get an overview of the document. In this paper, we proposed …

Semi-Supervised Learning for Neural Keyphrase Generation

We study the problem of generating keyphrases that summarize the key points for a given document. While sequence-to-sequence (seq2seq) models have achieved remarkable performance on this task (Meng et al., 2017), model t…

Unsupervised Keyphrase Extraction from Scientific Publications

We propose a novel unsupervised keyphrase extraction approach that filters candidate keywords using outlier detection. It starts by training word embeddings on the target document to capture semantic regularities among t…

Encoding Conversation Context for Neural Keyphrase Extraction from Microblog Posts

Existing keyphrase extraction methods suffer from data sparsity problem when they are conducted on short and informal texts, especially microblog messages. Enriching context is one way to alleviate this problem. Consider…

Key2Vec: Automatic Ranked Keyphrase Extraction from Scientific Articles using Phrase Embeddings

Keyphrase extraction is a fundamental task in natural language processing that facilitates mapping of documents to a set of representative phrases. In this paper, we present an unsupervised technique (Key2Vec) that lever…

Improving Unsupervised Keyphrase Extraction using Background Knowledge

Unsupervised Keyphrase Extraction with Multipartite Graphs

We propose an unsupervised keyphrase extraction model that encodes topical information within a multipartite graph structure. Our model represents keyphrase candidates and topics in a single graph and exploits their mutu…

WikiRank: Improving Keyphrase Extraction Based on Background Knowledge

Keyphrase is an efficient representation of the main idea of documents. While background knowledge can provide valuable information about documents, they are rarely incorporated in keyphrase extraction methods. In this p…

Simple Unsupervised Keyphrase Extraction using Sentence Embeddings

Keyphrase extraction is the task of automatically selecting a small set of phrases that best describe a given free text document. Supervised keyphrase extraction requires large amounts of labeled training data and genera…

Learning Feature Representations for Keyphrase Extraction

In supervised approaches for keyphrase extraction, a candidate phrase is encoded with a set of hand-crafted features and machine learning algorithms are trained to discriminate keyphrases from non-keyphrases. Although th…

Local Word Vectors Guiding Keyphrase Extraction

Automated keyphrase extraction is a fundamental textual information processing task concerned with the selection of representative phrases from a document that summarize its content. This work presents a novel unsupervis…

Exploiting and Evaluating a Supervised, Multilanguage Keyphrase Extraction pipeline for under-resourced languages

This paper evaluates different techniques for building a supervised, multilanguage keyphrase extraction pipeline for languages which lack a gold standard. Starting from an unsupervised English keyphrase extraction pipeli…

PKU\_ICL at SemEval-2017 Task 10: Keyphrase Extraction with Model Ensemble and External Knowledge

This paper presents a system that participated in SemEval 2017 Task 10 (subtask A and subtask B): Extracting Keyphrases and Relations from Scientific Publications (Augenstein et al., 2017). Our proposed approach utilizes…

WING-NUS at SemEval-2017 Task 10: Keyphrase Extraction and Classification as Joint Sequence Labeling

We describe an end-to-end pipeline processing approach for SemEval 2017{'}s Task 10 to extract keyphrases and their relations from scientific publications. We jointly identify and classify keyphrases by modeling the subt…

SZTE-NLP at SemEval-2017 Task 10: A High Precision Sequence Model for Keyphrase Extraction Utilizing Sparse Coding for Feature Generation

In this paper we introduce our system participating at the 2017 SemEval shared task on keyphrase extraction from scientific documents. We aimed at the creation of a keyphrase extraction approach which relies on as little…