Search Results for author: Sophia Ananiadou

Found 65 papers, 12 papers with code

GenCompareSum: a hybrid unsupervised summarization method using salience

1 code implementation BioNLP (ACL) 2022 Jennifer Bishop, Qianqian Xie, Sophia Ananiadou

To this end, we propose a hybrid, unsupervised, abstractive-extractive approach, in which we walk through a document, generating salient textual fragments representing its key points.

Extractive Summarization Text Summarization

Transformer for Graphs: An Overview from Architecture Perspective

1 code implementation17 Feb 2022 Erxue Min, Runfa Chen, Yatao Bian, Tingyang Xu, Kangfei Zhao, Wenbing Huang, Peilin Zhao, Junzhou Huang, Sophia Ananiadou, Yu Rong

In this survey, we provide a comprehensive review of various Graph Transformer models from the architectural design perspective.

Investigating Text Simplification Evaluation

1 code implementation Findings (ACL) 2021 Laura Vásquez-Rodríguez, Matthew Shardlow, Piotr Przybyła, Sophia Ananiadou

Modern text simplification (TS) heavily relies on the availability of gold standard data to build machine learning models.

Text Simplification

One-shot to Weakly-Supervised Relation Classification using Language Models

1 code implementation AKBC 2021 Thy Thy Tran, Phong Le, Sophia Ananiadou

Unfortunately, both annotation methodologies are costly and time-consuming since they depend on intensive human labour for annotation or for knowledge base creation.

Relation Classification

EPICURE Ensemble Pretrained Models for Extracting Cancer Mutations from Literature

no code implementations11 Jun 2021 Jiarun Cao, Elke M van Veen, Niels Peek, Andrew G Renehan, Sophia Ananiadou

To interpret the genetic profile present in a patient sample, it is necessary to know which mutations have important roles in the development of the corresponding cancer type.

Data Augmentation named-entity-recognition +1

Distantly Supervised Relation Extraction with Sentence Reconstruction and Knowledge Base Priors

no code implementations NAACL 2021 Fenia Christopoulou, Makoto Miwa, Sophia Ananiadou

We propose a multi-task, probabilistic approach to facilitate distantly supervised relation extraction by bringing closer the representations of sentences that contain the same Knowledge Base pairs.

Multi-Task Learning Relation Extraction

Paladin: an annotation tool based on active and proactive learning

no code implementations EACL 2021 Minh-Quoc Nghiem, Paul Baylis, Sophia Ananiadou

In this paper, we present Paladin, an open-source web-based annotation tool for creating high-quality multi-label document-level datasets.

Active Learning

HSEarch: semantic search system for workplace accident reports

no code implementations23 Mar 2021 Emrah Inan, Paul Thompson, Tim Yates, Sophia Ananiadou

Semantic search engines, which integrate the output of text mining (TM) methods, can significantly increase the ease and efficiency of finding relevant documents and locating important information within them.

SpanEmo: Casting Multi-label Emotion Classification as Span-prediction

1 code implementation EACL 2021 Hassan Alhuzali, Sophia Ananiadou

We propose a new model "SpanEmo" casting multi-label emotion classification as span-prediction, which can aid ER models to learn associations between labels and words in a sentence.

Classification Emotion Classification +3

DeepEventMine: end-to-end neural nested event extraction from biomedical texts

1 code implementation17 Jun 2020 Hai-Long Trieu, Thy Thy Tran, Khoa N A Duong, Anh Nguyen, Makoto Miwa, Sophia Ananiadou

Motivation Recent neural approaches on event extraction from text mainly focus on flat events in general domain, while there are less attempts to detect nested and overlapping events.

Semantic Annotation for Improved Safety in Construction Work

no code implementations LREC 2020 Paul Thompson, Tim Yates, Emrah Inan, Sophia Ananiadou

In response, we have designed a novel named entity annotation scheme and associated guidelines for this domain, which covers hazards, consequences, mitigation strategies and project attributes.

named-entity-recognition NER

Revisiting Unsupervised Relation Extraction

1 code implementation ACL 2020 Thy Thy Tran, Phong Le, Sophia Ananiadou

Unsupervised relation extraction (URE) extracts relations between named entities from raw text without manually-labelled data and existing knowledge bases (KBs).

Inductive Bias Relation Extraction

A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection

no code implementations IJCNLP 2019 Kurt Espinosa, Makoto Miwa, Sophia Ananiadou

We tackle the nested and overlapping event detection task and propose a novel search-based neural network (SBNN) structured prediction model that treats the task as a search problem on a relation graph of trigger-argument structures.

Dependency Parsing Event Detection +2

Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network

no code implementations ACL 2019 Sunil Kumar Sahu, Fenia Christopoulou, Makoto Miwa, Sophia Ananiadou

Inter-sentence relation extraction deals with a number of complex semantic relationships in documents, which require local, non-local, syntactic and semantic dependencies.

Relation Extraction

APLenty: annotation tool for creating high-quality datasets using active and proactive learning

no code implementations EMNLP 2018 Minh-Quoc Nghiem, Sophia Ananiadou

In this paper, we present APLenty, an annotation tool for creating high-quality sequence labeling datasets using active and proactive learning.

Active Learning Multi-Label Learning +1

A Neural Layered Model for Nested Named Entity Recognition

1 code implementation NAACL 2018 Meizhi Ju, Makoto Miwa, Sophia Ananiadou

Each flat NER layer is based on the state-of-the-art flat NER model that captures sequential context representation with bidirectional Long Short-Term Memory (LSTM) layer and feeds it to the cascaded CRF layer.

Entity Linking named-entity-recognition +4

Paths for uncertainty: Exploring the intricacies of uncertainty identification for news

no code implementations WS 2018 Chrysoula Zerva, Sophia Ananiadou

We compare the differences in the definition and expression of uncertainty between a scientific domain, i. e., biomedicine, and newswire.

Proactive Learning for Named Entity Recognition

no code implementations WS 2017 Maolin Li, Nhung Nguyen, Sophia Ananiadou

The goal of active learning is to minimise the cost of producing an annotated dataset, in which annotators are assumed to be perfect, i. e., they always choose the correct labels.

Active Learning named-entity-recognition +2

Distributed Document and Phrase Co-embeddings for Descriptive Clustering

no code implementations EACL 2017 Motoki Sato, Austin J. Brockmeier, Georgios Kontonatsios, Tingting Mu, John Y. Goulermas, Jun{'}ichi Tsujii, Sophia Ananiadou

Descriptive document clustering aims to automatically discover groups of semantically related documents and to assign a meaningful label to characterise the content of each cluster.

Information Retrieval Semantic Textual Similarity

Ensemble Classification of Grants using LDA-based Features

no code implementations LREC 2016 Yannis Korkontzelos, Beverley Thomas, Makoto Miwa, Sophia Ananiadou

Classifying research grants into useful categories is a vital task for a funding body to give structure to the portfolio for analysis, informing strategic planning and decision-making.

Classification Decision Making +1

Identifying Content Types of Messages Related to Open Source Software Projects

no code implementations LREC 2016 Yannis Korkontzelos, Paul Thompson, Sophia Ananiadou

Assessing the suitability of an Open Source Software project for adoption requires not only an analysis of aspects related to the code, such as code quality, frequency of updates and new version releases, but also an evaluation of the quality of support offered in related online forums and issue trackers.

Locating Requests among Open Source Software Communication Messages

no code implementations LREC 2014 Ioannis Korkontzelos, Sophia Ananiadou

As a first step towards assessing the quality of support offered online for Open Source Software (OSS), we address the task of locating requests, i. e., messages that raise an issue to be addressed by the OSS community, as opposed to any other message.

General Classification

Interoperability and Customisation of Annotation Schemata in Argo

no code implementations LREC 2014 Rafal Rak, Jacob Carter, Andrew Rowley, Riza Theresa Batista-Navarro, Sophia Ananiadou

Argo aids the development of custom annotation schemata and supports their interoperability by featuring a schema editor and specialised analytics for schemata alignment.

Collaborative Development and Evaluation of Text-processing Workflows in a UIMA-supported Web-based Workbench

no code implementations LREC 2012 Rafal Rak, Andrew Rowley, Sophia Ananiadou

Challenges in creating comprehensive text-processing worklows include a lack of the interoperability of individual components coming from different providers and/or a requirement imposed on the end users to know programming techniques to compose such workflows.

A data and analysis resource for an experiment in text mining a collection of micro-blogs on a political topic.

no code implementations LREC 2012 William Black, Rob Procter, Steven Gray, Sophia Ananiadou

The analysis of a corpus of micro-blogs on the topic of the 2011 UK referendum about the Alternative Vote has been undertaken as a joint activity by text miners and social scientists.

Named Entity Recognition Sentiment Analysis

Identification of Manner in Bio-Events

no code implementations LREC 2012 Raheel Nawaz, Paul Thompson, Sophia Ananiadou

Until recently, these corpora, and hence the event extraction systems trained on them, focussed almost exclusively on the identification and classification of event arguments, without taking into account how the textual context of the events could affect their interpretation.

Event Extraction

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