AIMC Topic: Vocabulary

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Few-Shot Text Classification with Global-Local Feature Information.

Sensors (Basel, Switzerland)
Meta-learning frameworks have been proposed to generalize machine learning models for domain adaptation without sufficient label data in computer vision. However, text classification with meta-learning is less investigated. In this paper, we propose ...

Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records.

Journal of neurodevelopmental disorders
BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyp...

Semantic Search for Large Scale Clinical Ontologies.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Finding concepts in large clinical ontologies can be challenging when queries use different vocabularies. A search algorithm that overcomes this problem is useful in applications such as concept normalisation and ontology matching, where concepts can...

Stopwords in technical language processing.

PloS one
There are increasing applications of natural language processing techniques for information retrieval, indexing, topic modelling and text classification in engineering contexts. A standard component of such tasks is the removal of stopwords, which ar...

Improved characterisation of clinical text through ontology-based vocabulary expansion.

Journal of biomedical semantics
BACKGROUND: Biomedical ontologies contain a wealth of metadata that constitutes a fundamental infrastructural resource for text mining. For several reasons, redundancies exist in the ontology ecosystem, which lead to the same entities being described...

Learning about phraseology from corpora: A linguistically motivated approach for Multiword Expression identification.

PloS one
Multiword Expressions (MWEs) are idiosyncratic combinations of words which pose important challenges to Natural Language Processing. Some kinds of MWEs, such as verbal ones, are particularly hard to identify in corpora, due to their high degree of mo...

Biomedical word sense disambiguation with bidirectional long short-term memory and attention-based neural networks.

BMC bioinformatics
BACKGROUND: In recent years, deep learning methods have been applied to many natural language processing tasks to achieve state-of-the-art performance. However, in the biomedical domain, they have not out-performed supervised word sense disambiguatio...

RnRTD: Intelligent Approach Based on the Relationship-Driven Neural Network and Restricted Tensor Decomposition for Multiple Accusation Judgment in Legal Cases.

Computational intelligence and neuroscience
The use of intelligent judgment technology to assist in judgment is an inevitable trend in the development of judgment in contemporary social legal cases. Using big data and artificial intelligence technology to accurately determine multiple accusati...

Intelligent diagnosis with Chinese electronic medical records based on convolutional neural networks.

BMC bioinformatics
BACKGROUND: Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural networks. The adven...