Search Results for author: Cecile Paris

Found 32 papers, 9 papers with code

Harnessing Privileged Information for Hyperbole Detection

no code implementations ALTA 2021 Rhys Biddle, Maciek Rybinski, Qian Li, Cecile Paris, Guandong Xu

The detection of hyperbole is an important stepping stone to understanding the intentions of a hyperbolic utterance.

Lifelong Explainer for Lifelong Learners

1 code implementation EMNLP 2021 Xuelin Situ, Sameen Maruf, Ingrid Zukerman, Cecile Paris, Gholamreza Haffari

Our ablation study shows that the ER mechanism in our LLE approach enhances the learning capabilities of the student explainer.

text-classification Text Classification

Demonstrating the Reliability of Self-Annotated Emotion Data

no code implementations NAACL (CLPsych) 2021 Anton Malko, Cecile Paris, Andreas Duenser, Maria Kangas, Diego Molla, Ross Sparks, Stephen Wan

Vent is a specialised iOS/Android social media platform with the stated goal to encourage people to post about their feelings and explicitly label them.

Fake News Detection Through Graph-based Neural Networks: A Survey

no code implementations24 Jul 2023 Shuzhi Gong, Richard O. Sinnott, Jianzhong Qi, Cecile Paris

In recent years, graph-based methods have yielded strong results, as they can closely model the social context and propagation process of online news.

Fake News Detection Misinformation

Fake News Detection Through Temporally Evolving User Interactions

1 code implementation PAKDD: Advances in Knowledge Discovery and Data Mining 2023 Shuzhi Gong, Richard Sinnott, Jianzhong Qi, Cecile Paris

We join this model with a neural Hawkes process model to exploit the distinctive self-exciting patterns of true news and fake news on social media.

Fake News Detection

Learning to Explain: Generating Stable Explanations Fast

1 code implementation ACL 2021 Xuelin Situ, Ingrid Zukerman, Cecile Paris, Sameen Maruf, Gholamreza Haffari

The importance of explaining the outcome of a machine learning model, especially a black-box model, is widely acknowledged.

A Comprehensive Survey on Community Detection with Deep Learning

no code implementations26 May 2021 Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu

A community reveals the features and connections of its members that are different from those in other communities in a network.

Clustering Community Detection +3

Assessing Social License to Operate from the Public Discourse on Social Media

no code implementations COLING 2020 Chang Xu, Cecile Paris, Ross Sparks, Surya Nepal, Keith VanderLinden

Our experimental results show that SIRTA is highly effective in distilling stances from social posts for SLO level assessment, and that the continuous monitoring of SLO levels afforded by SIRTA enables the early detection of critical SLO changes.

text-classification Text Classification +2

Less is More: Rejecting Unreliable Reviews for Product Question Answering

1 code implementation9 Jul 2020 Shiwei Zhang, Xiuzhen Zhang, Jey Han Lau, Jeffrey Chan, Cecile Paris

In the literature, PQA is formulated as a retrieval problem with the goal to search for the most relevant reviews to answer a given product question.

Community Question Answering Conformal Prediction +1

Analysis of Trending Topics and Text-based Channels of Information Delivery in Cybersecurity

no code implementations26 Jun 2020 Tingmin Wu, Wanlun Ma, Sheng Wen, Xin Xia, Cecile Paris, Surya Nepal, Yang Xiang

We further compare the identified 16 security categories across different sources based on their popularity and impact.

Deep Learning for Community Detection: Progress, Challenges and Opportunities

1 code implementation17 May 2020 Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Jian Yang, Philip S. Yu

As communities represent similar opinions, similar functions, similar purposes, etc., community detection is an important and extremely useful tool in both scientific inquiry and data analytics.

Clustering Community Detection +1

An Effective Transition-based Model for Discontinuous NER

1 code implementation ACL 2020 Xiang Dai, Sarvnaz Karimi, Ben Hachey, Cecile Paris

Unlike widely used Named Entity Recognition (NER) data sets in generic domains, biomedical NER data sets often contain mentions consisting of discontinuous spans.

named-entity-recognition Named Entity Recognition +1

DAN: Dual-View Representation Learning for Adapting Stance Classifiers to New Domains

no code implementations13 Mar 2020 Chang Xu, Cecile Paris, Surya Nepal, Ross Sparks, Chong Long, Yafang Wang

We address the issue of having a limited number of annotations for stance classification in a new domain, by adapting out-of-domain classifiers with domain adaptation.

Domain Adaptation Representation Learning +1

Towards Generating Stylized Image Captions via Adversarial Training

no code implementations8 Aug 2019 Omid Mohamad Nezami, Mark Dras, Stephen Wan, Cecile Paris, Len Hamey

While most image captioning aims to generate objective descriptions of images, the last few years have seen work on generating visually grounded image captions which have a specific style (e. g., incorporating positive or negative sentiment).

Image Captioning

Image Captioning using Facial Expression and Attention

no code implementations8 Aug 2019 Omid Mohamad Nezami, Mark Dras, Stephen Wan, Cecile Paris

An analysis of the generated captions finds that, perhaps unexpectedly, the improvement in caption quality appears to come not from the addition of adjectives linked to emotional aspects of the images, but from more variety in the actions described in the captions.

Image Captioning

Figurative Usage Detection of Symptom Words to Improve Personal Health Mention Detection

no code implementations ACL 2019 Adith Iyer, Aditya Joshi, Sarvnaz Karimi, Ross Sparks, Cecile Paris

The introduction of figurative usage detection results in an average improvement of 2. 21% F-score of personal health mention detection, in the case of the feature augmentation-based approach.

Recognising Agreement and Disagreement between Stances with Reason Comparing Networks

no code implementations ACL 2019 Chang Xu, Cecile Paris, Surya Nepal, Ross Sparks

We identify agreement and disagreement between utterances that express stances towards a topic of discussion.

Using Similarity Measures to Select Pretraining Data for NER

1 code implementation NAACL 2019 Xiang Dai, Sarvnaz Karimi, Ben Hachey, Cecile Paris

Word vectors and Language Models (LMs) pretrained on a large amount of unlabelled data can dramatically improve various Natural Language Processing (NLP) tasks.

named-entity-recognition Named Entity Recognition

Does Multi-Task Learning Always Help?: An Evaluation on Health Informatics

no code implementations ALTA 2019 Aditya Joshi, Sarvnaz Karimi, Ross Sparks, Cecile Paris, C Raina MacIntyre

Multi-Task Learning (MTL) has been an attractive approach to deal with limited labeled datasets or leverage related tasks, for a variety of NLP problems.

Classification General Classification +1

Survey of Text-based Epidemic Intelligence: A Computational Linguistic Perspective

no code implementations14 Mar 2019 Aditya Joshi, Sarvnaz Karimi, Ross Sparks, Cecile Paris, C Raina MacIntyre

Epidemic intelligence deals with the detection of disease outbreaks using formal (such as hospital records) and informal sources (such as user-generated text on the web) of information.

Event Detection General Classification

Senti-Attend: Image Captioning using Sentiment and Attention

no code implementations24 Nov 2018 Omid Mohamad Nezami, Mark Dras, Stephen Wan, Cecile Paris

However, such models typically have difficulty in balancing the semantic aspects of the image and the non-factual dimensions of the caption; in addition, it can be observed that humans may focus on different aspects of an image depending on the chosen sentiment or style of the caption.

Image Captioning

Automatic Recognition of Student Engagement using Deep Learning and Facial Expression

3 code implementations7 Aug 2018 Omid Mohamad Nezami, Mark Dras, Len Hamey, Deborah Richards, Stephen Wan, Cecile Paris

This paper presents a deep learning model to improve engagement recognition from images that overcomes the data sparsity challenge by pre-training on readily available basic facial expression data, before training on specialised engagement data.

Facial Expression Recognition Facial Expression Recognition (FER)

Cross-Target Stance Classification with Self-Attention Networks

1 code implementation ACL 2018 Chang Xu, Cecile Paris, Surya Nepal, Ross Sparks

In stance classification, the target on which the stance is made defines the boundary of the task, and a classifier is usually trained for prediction on the same target.

Classification General Classification +1

Automated text summarisation and evidence-based medicine: A survey of two domains

no code implementations25 Jun 2017 Abeed Sarker, Diego Molla, Cecile Paris

We envision that this survey will serve as a first resource for the development of future operational text summarisation techniques for EBM.

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