Paper-Conference

Glocal: Incorporating Global Information in Local Convolution for Keyphrase Extraction
Graph Convolutional Networks (GCNs) are a class of spectral clustering techniques that leverage localized convolution filters to …
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Predicting Helpful Posts in Open-Ended Discussion Forums: A Neural Architecture
Users participate in online discussion forums to learn from others and share their knowledge with the community. They often start a …
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Treatment Side Effect Prediction from Online User-generated Content
With Health 2.0, patients and caregivers increasingly seek information regarding possible drug side effects during their medical …
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Identifying Emergent Research Trends by Key Authors and Phrases
Identifying emergent research trends is a key issue for both primary researchers as well as secondary research managers. Such processes …
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Countering Position Bias in Instructor Interventions in MOOC Discussion Forums
We systematically confirm that instructors are strongly influenced by the user interface presentation of Massive Online Open Course …
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Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures
Existing solutions to task-oriented dialogue systems follow pipeline designs which introduces architectural complexity and fragility. …
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The ACL Anthology: Current State and Future Directions
The Association of Computational Linguistic′s Anthology is the open source archive, and the main source for computational linguistics …
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Modeling Temporal Progression of Emotional Status in Mental Health Forum: A Recurrent Neural Net Approach
Patients turn to Online Health Communities not only for information on specific conditions but also for emotional support. Previous …
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WING-NUS at SemEval-2017 Task 10: Keyphrase Extraction and Classification as Joint Sequence Labeling
We describe an end-to-end pipeline processing approach for SemEval 2017′s Task 10 to extract keyphrases and their relations from …
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Health Forum Thread Recommendation Using an Interest Aware Topic Model
We introduce a general, interest-aware topic model (IATM), in which known higher-level interests on topics expressed by each user can …
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