A survey of trust in social networks
- W. Sherchan, S. Nepal, Cécile Paris
- Computer ScienceCSUR
- 1 August 2013
This article presents the first comprehensive review of social and computer science literature on trust in social networks and discusses recent works addressing three aspects of social trust: trust information collection, trust evaluation, and trust dissemination.
Planning Text for Advisory Dialogues: Capturing Intentional and Rhetorical Information
- Johanna D. Moore, Cécile Paris
- SociologyComputational Linguistics
- 1 December 1993
It is argued that, to handle explanation dialogues successfully, a discourse model must include information about the intended effect of individual parts of the text on the hearer, as well as how the parts relate to one another rhetorically.
Using Dependency-Based Features to Take the ’Para-farce’ out of Paraphrase
- Stephen Wan, M. Dras, R. Dale, Cécile Paris
- Computer ScienceAustralasian Language Technology Association…
- 1 November 2006
A machine learning approach is proposed to be used to filter out inconsistent novel sentences, or False Paraphrases, using the Microsoft Research Paraphrase corpus and investigating whether features based on syntactic dependencies can aid in this task.
An Effective Transition-based Model for Discontinuous NER
- Xiang Dai, Sarvnaz Karimi, Ben Hachey, Cécile Paris
- Computer ScienceAnnual Meeting of the Association for…
- 1 April 2020
This work proposes a simple, effective transition-based model with generic neural encoding for discontinuous NER that can effectively recognize discontinuous mentions without sacrificing the accuracy on continuous mentions.
Improving Grammaticality in Statistical Sentence Generation: Introducing a Dependency Spanning Tree Algorithm with an Argument Satisfaction Model
- Stephen Wan, M. Dras, R. Dale, Cécile Paris
- Computer ScienceConference of the European Chapter of the…
- 30 March 2009
This work couch statistical sentence generation as a spanning tree problem in order to search for the best dependency tree spanning a set of chosen words and introduces a new search algorithm for this task that models argument satisfaction to improve the linguistic validity of the generated tree.
Cross-Target Stance Classification with Self-Attention Networks
- Chang Xu, Cécile Paris, S. Nepal, R. Sparks
- Computer ScienceAnnual Meeting of the Association for…
- 17 May 2018
This work proposes a neural model that can apply what has been learned from a source target to a destination target, and shows that this model can find useful information shared between relevant targets which improves generalization in certain scenarios.
Classifying microblogs for disasters
- Sarvnaz Karimi, Jie Yin, Cécile Paris
- Computer ScienceAustralasian Document Computing Symposium
- 5 December 2013
This work addresses the issue of filtering massive amounts of Twitter data to identify high-value messages related to disasters, and to further classify disaster-related messages into those pertaining to particular disaster types, such as earthquake, flooding, fire, or storm.
Detecting suicidality on Twitter
- B. O’Dea, Stephen Wan, P. Batterham, A. Calear, Cécile Paris, H. Christensen
- Medicine
- 1 May 2015
Talking about your health to strangers: understanding the use of online social networks by patients
- N. Colineau, Cécile Paris
- PsychologyNew Rev. Hypermedia Multim.
- 1 April 2010
It is found that, consistent with previous research, most patients were seeking information about their medical condition online, while, at the same time, still interacting with health professionals to talk about sensitive information and complex issues.
NNE: A Dataset for Nested Named Entity Recognition in English Newswire
- Nicky Ringland, Xiang Dai, Ben Hachey, Sarvnaz Karimi, Cécile Paris, J. Curran
- Computer ScienceAnnual Meeting of the Association for…
- 4 June 2019
This work describes NNE—a fine-grained, nested named entity dataset over the full Wall Street Journal portion of the Penn Treebank, which comprises 279,795 mentions of 114 entity types with up to 6 layers of nesting.
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