activity
20172021
most citedOn Search Powered Navigation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2021

Understanding who uses Reddit: Profiling individuals with a self-reported bipolar disorder diagnosis

Glorianna Jagfeld, Fiona Lobban, Paul Rayson +1

Recently, research on mental health conditions using public online data, including Reddit, has surged in NLP and health research but has not reported user characteristics, which ar…

cs.CL2019

A computational linguistic study of personal recovery in bipolar disorder

Glorianna Jagfeld

Mental health research can benefit increasingly fruitfully from computational linguistics methods, given the abundant availability of language data in the internet and advances of…

cs.CL2018

Sequence-to-Sequence Models for Data-to-Text Natural Language Generation: Word- vs. Character-based Processing and Output Diversity

Glorianna Jagfeld, Sabrina Jenne, Ngoc Thang Vu

We present a comparison of word-based and character-based sequence-to-sequence models for data-to-text natural language generation, which generate natural language descriptions for…

cs.CL2018

Comparing Attention-based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading Comprehension

Matthias Blohm, Glorianna Jagfeld, Ekta Sood +2

We propose a machine reading comprehension model based on the compare-aggregate framework with two-staged attention that achieves state-of-the-art results on the MovieQA question a…

cs.IR20171 cited

On Search Powered Navigation

Mostafa Dehghani, Glorianna Jagfeld, Hosein Azarbonyad +3

Query-based searching and browsing-based navigation are the two main components of exploratory search. Search lets users dig in deep by controlling their actions to focus on and fi…

cs.CL2017

Encoding Word Confusion Networks with Recurrent Neural Networks for Dialog State Tracking

Glorianna Jagfeld, Ngoc Thang Vu

This paper presents our novel method to encode word confusion networks, which can represent a rich hypothesis space of automatic speech recognition systems, via recurrent neural ne…