Articles

AbstractWe describe our methods in trying to detect the target of sarcasm as part of ALTA 2019 shared task. We use combination of ensemble of clas- sifiers and a rule-based system. Our team ob- tained a Dice-Sorensen Coefficient score of 0.37150, which placed 2nd in the public leader- board. Despite …...

AbstractWe present an overview of the 2019 ALTA shared task. This is the 10th of the series of shared tasks organised by ALTA since 2010. The task was to detect the target of sarcastic comments posted on social media. We intro- duce the task, describe the data and present the …...

We propose a novel algorithm of graph-to- string alignment that constructs automata from a sample of string sequences. While being a variant of global edit distance, the algorithm also employs graph construction operations in order to form an optimal alignment. It al- lows dynamic insertion of edges and nodes driven …...

We propose a modular rule-based system for Text Simplification and show that it out- performs the state-of-the-art neural-based simplification system in terms of simplic- ity. We compare the output of both systems to highlight the differences between the two approaches. Further, we present an ad- aptation of our system to …...

Transformer-based models have been popu- lar recently and have improved performance for many Natural Language Processing (NLP) Tasks, including those in the biomedical field. Previous research suggests that, when us- ing these models, an in-domain vocabulary is more suitable than using an open-domain vocabulary. We investigate the effects of a …...

Many computer-assisted language learning (CALL) systems offer gap-fill items, often with multiple choices in order to facilitate im- mediate feedback. Automatic distractor gener- ation can therefore be helpful in providing the multiple choices. While existing algorithms focus on proposing the most plausible distrac- tors, many realistic scenarios make use of …...

Women are underrepresented in many spheres of our societies, including research. A com- mon excuse for exclusively male line-ups is that suitable women could not be found. One way of promoting visibility of women in in- dustry and academia is to explicitly provide solutions to find them. Expert Connect is …...

AbstractMulti-Task Learning (MTL) has been an attractive approach to deal with limited labeled datasets or leverage related tasks, for a variety of NLP problems. We examine the benefit of MTL for three specific pairs of health informatics tasks that deal with: (a) overlapping symptoms for the same classification problem (personal …...

AbstractReading is important for any language learner, but the difficulty level of the text needs to match a reader’s level to enable efficient learning of new vocabulary. Many widely used traditional readability measures are not effective for those who speak English as a second or additional language. This study examines …...

AbstractThe first step towards designing an information system is conceptual modelling where domain experts and knowledge engineers identify the necessary information together to build an information system. Entity relationship modelling is one of the most popular conceptual modelling techniques that represents an information system in terms of entities, attributes and …...

Background: Datasets available for abstract sentence classification modelling are predominately comprised of abstracts sourced from biomedical research. Aims: To contribute a large non-biomedical multidisciplinary dataset for abstract sentence classification model research. Method: Bulk extract and transformation of Emerald Group Publishing structured abstracts indexed on Scopus. Results: We present the largest …...

AbstractThe coarse-to-fine (coarse2fine) methods have recently been widely used in the generation tasks. The methods first generate a rough sketch in the coarse stage and then use the sketch to get the final result in the fine stage. However, they usually lack the correction ability when getting a wrong sketch. …...

AbstractPain is the main symptom that patients present with to the emergency department (ED). Pain management, however, is often poorly done aspect of emergency care and patients with painful conditions can endure long waits before their pain is assessed or treated. To improve pain management quality, identifying whether or not …...

AbstractExtracting chemical reactions from patents is a crucial task for chemists working on chemical exploration. In this paper we introduce the novel task of detecting the textual spans that describe or refer to chemical reactions within patents. We formulate this task as a paragraph-level sequence tagging problem, where the system …...

One key challenge for building a semantic parser in new domains is the difficulty to an- notate new datasets. In this paper, we pro- pose a sequential transfer learning method as a domain adaptation method to tackle this is- sue. We show that we can obtain a model with better …...

Semantic parsing targets at mapping human utterances into structured meaning represen- tations, such as logical forms, programming snippets, SQL queries etc. In this work, we focus on logical form generation, which is ex- tracted from an automated email assistant sys- tem. Since this task is dialogue-oriented, in- formation across utterances …...

AbstractCatastrophic forgetting — whereby a model trained on one task is fine-tuned on a second, and in doing so, suffers a “catastrophic” drop in performance over the first task — is a hurdle in the development of better transfer learning techniques. Despite impressive progress in reducing catastrophic forgetting, we have …...

AbstractDespite the success of attention-based neural models for natural language generation and classification tasks, they are unable to capture the discourse structure of larger documents. We hypothesize that explicit discourse representations have utility for NLP tasks over longer documents or document sequences, which sequence-to-sequence models are unable to capture. For …...

Politically-contested issues are often discussed with different emphases by different people. This emphasis is called a frame. In this pa- per, we examine the performance of classifiers trained using the media frames Corpus (MFC) (Card et al., 2015); a collection of US news la- belled with fifteen different frame categories. …...

With the advent of neural models, there has been a rapid move away from feature engineer- ing, or at best, simplistically combining hand- crafted features with learned representations as side information. We propose a method that uses hand-crafted features to guide learn- ing by explicitly attending to feature indica- tors …...