A survey on recent advances in keyphrase extraction from pre-trained language models
Keyphrase Extraction (KE) is a critical component in Natural Language Processing (NLP)
systems for selecting a set of phrases from the document that could summarize the important …
systems for selecting a set of phrases from the document that could summarize the important …
Neural extractive summarization with hierarchical attentive heterogeneous graph network
Sentence-level extractive text summarization is substantially a node classification task of
network mining, adhering to the informative components and concise representations. There …
network mining, adhering to the informative components and concise representations. There …
From statistical methods to deep learning, automatic keyphrase prediction: A survey
Keyphrase prediction aims to generate phrases (keyphrases) that highly summarizes a
given document. Recently, researchers have conducted in-depth studies on this task from …
given document. Recently, researchers have conducted in-depth studies on this task from …
Attentionrank: Unsupervised keyphrase extraction using self and cross attentions
Keyword or keyphrase extraction is to identify words or phrases presenting the main topics
of a document. This paper proposes the AttentionRank, a hybrid attention model, to identify …
of a document. This paper proposes the AttentionRank, a hybrid attention model, to identify …
One size does not fit all: Generating and evaluating variable number of keyphrases
Different texts shall by nature correspond to different number of keyphrases. This
desideratum is largely missing from existing neural keyphrase generation models. In this …
desideratum is largely missing from existing neural keyphrase generation models. In this …
Leveraging graph neural networks for user profiling: Recent advances and open challenges
The proposed tutorial aims to familiarise the CIKM community with modern user profiling
techniques that utilise Graph Neural Networks (GNNs). Initially, we will delve into the …
techniques that utilise Graph Neural Networks (GNNs). Initially, we will delve into the …
Hyperbolic relevance matching for neural keyphrase extraction
Keyphrase extraction is a fundamental task in natural language processing and information
retrieval that aims to extract a set of phrases with important information from a source …
retrieval that aims to extract a set of phrases with important information from a source …
An empirical study on neural keyphrase generation
Recent years have seen a flourishing of neural keyphrase generation (KPG) works,
including the release of several large-scale datasets and a host of new models to tackle …
including the release of several large-scale datasets and a host of new models to tackle …
Do graph neural networks build fair user models? assessing disparate impact and mistreatment in behavioural user profiling
Recent approaches to behavioural user profiling employ Graph Neural Networks (GNNs) to
turn users' interactions with a platform into actionable knowledge. The effectiveness of an …
turn users' interactions with a platform into actionable knowledge. The effectiveness of an …
Importance estimation from multiple perspectives for keyphrase extraction
Keyphrase extraction is a fundamental task in Natural Language Processing, which usually
contains two main parts: candidate keyphrase extraction and keyphrase importance …
contains two main parts: candidate keyphrase extraction and keyphrase importance …