AIMC Topic: Natural Language Processing

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An Experimental Study of Neural Approaches to Multi-Hop Inference in Question Answering.

International journal of neural systems
Question answering aims at computing the answer to a question given a context with facts. Many proposals focus on questions whose answer is explicit in the context; lately, there has been an increasing interest in questions whose answer is not explic...

Brains and algorithms partially converge in natural language processing.

Communications biology
Deep learning algorithms trained to predict masked words from large amount of text have recently been shown to generate activations similar to those of the human brain. However, what drives this similarity remains currently unknown. Here, we systemat...

Can natural language processing models extract and classify instances of interpersonal violence in mental healthcare electronic records: an applied evaluative study.

BMJ open
OBJECTIVE: This paper evaluates the application of a natural language processing (NLP) model for extracting clinical text referring to interpersonal violence using electronic health records (EHRs) from a large mental healthcare provider.

Weak Disambiguation for Partial Structured Output Learning.

IEEE transactions on cybernetics
Existing disambiguation strategies for partial structured output learning just cannot generalize well to solve the problem that there are some candidates that can be false positive or similar to the ground-truth label. In this article, we propose a n...

Chinese Image Caption Generation via Visual Attention and Topic Modeling.

IEEE transactions on cybernetics
Automatic image captioning is to conduct the cross-modal conversion from image visual content to natural language text. Involving computer vision (CV) and natural language processing (NLP), it has become one of the most sophisticated research issues ...

SMAN: Stacked Multimodal Attention Network for Cross-Modal Image-Text Retrieval.

IEEE transactions on cybernetics
This article focuses on tackling the task of the cross-modal image-text retrieval which has been an interdisciplinary topic in both computer vision and natural language processing communities. Existing global representation alignment-based methods fa...

A Topic Recognition Method of News Text Based on Word Embedding Enhancement.

Computational intelligence and neuroscience
Topic recognition technology has been commonly applied to identify different categories of news topics from the vast amount of web information, which has a wide application prospect in the field of online public opinion monitoring, news recommendatio...

Improved Spoken Language Representation for Intent Understanding in a Task-Oriented Dialogue System.

Sensors (Basel, Switzerland)
Successful applications of deep learning technologies in the natural language processing domain have improved text-based intent classifications. However, in practical spoken dialogue applications, the users' articulation styles and background noises ...

A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human professionals.

Nature communications
To accelerate biomedical research process, deep-learning systems are developed to automatically acquire knowledge about molecule entities by reading large-scale biomedical data. Inspired by humans that learn deep molecule knowledge from versatile rea...

Transfer Learning for Radio Frequency Machine Learning: A Taxonomy and Survey.

Sensors (Basel, Switzerland)
Transfer learning is a pervasive technology in computer vision and natural language processing fields, yielding exponential performance improvements by leveraging prior knowledge gained from data with different distributions. However, while recent wo...