Conference

Dyadic Memory Networks for Aspect-based Sentiment Analysis
This paper proposes Dyadic Memory Networks (DyMemNN), a novel extension of end-to-end memory networks (memNN) for aspect-based …
SkipFlow:Incorporating Neural Coherence Features for End-to-End Automatic Text Scoring
Deep learning has demonstrated tremendous potential for Automatic Text Scoring (ATS) tasks. In this paper, we describe a new neural …
Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering
The dominant neural architectures in question answer retrieval are based on recurrent or convolutional encoders configured with complex …
Latent Relational Metric Learning via Memory-based Attention for Collaborative Ranking
This paper proposes a new neural architecture for collaborative ranking with implicit feedback. Our model, LRML (\textit{Latent …
Learning to Rank Question Answer Pairs with Holographic Dual LSTM Architecture
We describe a new deep learning architecture for learning to rank question answer pairs. Our approach extends the long short-term …
Non-Parametric Estimation of Multiple Embeddings for Link Prediction on Dynamic Knowledge Graphs
Knowledge graphs play a significant role in many intelligent systems such as semantic search and recommendation systems. Recent works …
Random Semantic Tensor Ensemble for Scalable Knowledge Graph Link Prediction
Link prediction on knowledge graphs is useful in numerous application areas such as semantic search, question answering, entity …
Utilizing Temporal Information for Taxonomy Construction
Taxonomies play an important role in many applications by organizing domain knowledge into a hierarchy of ‘is-a’ relations between …
Learning Term Embeddings for Taxonomic Relation Identification with Dynamic Weighting Neural Network
In this paper, the aim is to recognize the ‘is-a’ relation between two terms through taxonomic relation identification. …
Overview of the Gene Ontology Task at BioCreative IV
Gene ontology (GO) annotation is a common task among model organism databases (MODs) for capturing gene function data from journal …