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Semantics

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Semi-supervised disentangled framework for transferable named entity recognition.

Neural networks : the official journal of the International Neural Network Society
Named entity recognition (NER) for identifying proper nouns in unstructured text is one of the most important and fundamental tasks in natural language processing. However, despite the widespread use of NER models, they still require a large-scale la...

Continuous Similarity Learning with Shared Neural Semantic Representation for Joint Event Detection and Evolution.

Computational intelligence and neuroscience
In the era of the rapid development of today's Internet, people often feel overwhelmed by vast official news streams or unofficial self-media tweets. To help people obtain the news topics they care about, there is a growing need for systems that can ...

Predicting risk of dyslexia with an online gamified test.

PloS one
Dyslexia is a specific learning disorder related to school failure. Detection is both crucial and challenging, especially in languages with transparent orthographies, such as Spanish. To make detecting dyslexia easier, we designed an online gamified ...

Transforming the study of organisms: Phenomic data models and knowledge bases.

PLoS computational biology
The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanie...

Learning sparse and meaningful representations through embodiment.

Neural networks : the official journal of the International Neural Network Society
How do humans acquire a meaningful understanding of the world with little to no supervision or semantic labels provided by the environment? Here we investigate embodiment with a closed loop between action and perception as one key component in this p...

Modality independent adversarial network for generalized zero shot image classification.

Neural networks : the official journal of the International Neural Network Society
Zero Shot Learning (ZSL) aims to classify images of unseen target classes by transferring knowledge from source classes through semantic embeddings. The core of ZSL research is to embed both visual representation of object instance and semantic descr...

From electronic health records to terminology base: A novel knowledge base enrichment approach.

Journal of biomedical informatics
Enriching terminology base (TB) is an important and continuous process, since formal term can be renamed and new term alias emerges all the time. As a potential supplementary for TB enrichment, electronic health record (EHR) is a fundamental source f...

Learning Dual Encoding Model for Adaptive Visual Understanding in Visual Dialogue.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Different from Visual Question Answering task that requires to answer only one question about an image, Visual Dialogue task involves multiple rounds of dialogues which cover a broad range of visual content that could be related to any objects, relat...

Robust facial landmark detection by cross-order cross-semantic deep network.

Neural networks : the official journal of the International Neural Network Society
Recently, convolutional neural networks (CNNs)-based facial landmark detection methods have achieved great success. However, most of existing CNN-based facial landmark detection methods have not attempted to activate multiple correlated facial parts ...

List-wise learning to rank biomedical question-answer pairs with deep ranking recursive autoencoders.

PloS one
Biomedical question answering (QA) represents a growing concern among industry and academia due to the crucial impact of biomedical information. When mapping and ranking candidate snippet answers within relevant literature, current QA systems typical...