Qiang Ning
Allen Institute for Artificial Intelligence
Publications28
h-index8
Citations143
Highly Influential Citations18
- Publications
- Influence
Identifying temporal relations between events is an essential step towards natural language understanding. However, the temporal relation between two events in a story depends on, and is often… Continue Reading
Understanding temporal and causal relations between events is a fundamental natural language understanding task. Because a cause must be before its effect in time, temporal and causal relations are… Continue Reading
Existing temporal relation (TempRel) annotation schemes often have low inter-annotator agreements (IAA) even between experts, suggesting that the current annotation task needs a better definition.… Continue Reading
Extracting temporal relations (before, after, overlapping, etc.) is a key aspect of understanding events described in natural language. We argue that this task would gain from the availability of a… Continue Reading
PURPOSE
To improve signal-to-noise ratio (SNR) for high-resolution spectroscopic imaging using a subspace-based technique known as SPectroscopic Imaging by exploiting spatiospectral CorrElation… Continue Reading
Implementing a Natural Language Processing (NLP) system requires considerable engineering effort: creating data-structures to represent language constructs; reading corpora annotations into these… Continue Reading
In this letter, we present a new algorithm for a single image super-resolution using the analysis sparse prior in the lαβ color space. Experimental results show that our algorithm outperforms other… Continue Reading
Automatic extraction of temporal information in text is an important component of natural language understanding. It involves two basic tasks: (1) Understanding time expressions that are mentioned… Continue Reading
Annotating temporal relations (TempRel) between events described in natural language is known to be labor intensive, partly because the total number of TempRels is quadratic in the number of events.… Continue Reading
Spectral Quantification for High-Resolution MR Spectroscopic Imaging With Spatiospectral Constraints
<italic>Objective:</italic> To obtain reliable spectral estimation from magnetic resonance spectroscopic imaging (MRSI) data. <italic>Methods:</italic> The proposed method takes advantage of prior… Continue Reading