Analyzing and modeling the implicit semantic relationships in data sources is the key to achieving integration and sharing of heterogeneous data information. However, manual modeling of data semantics is a laborious and error-prone task that ...

• A novel supervised table-graph cross-modal retrieval model for automatic semantic modeling.
• An explainable representation learning method combining graph representation learning with an incremental search algorithm.
• An attention ...

Learning topic hierarchies from a multi-domain corpus is crucial in topic modeling as it reveals valuable structural information embedded within documents. Despite the extensive literature on hierarchical topic models, effectively discovering inter-topic ...

Currently, the knowledge graph construction from the text mainly relies on document-level relation extraction models. However, these models have lower accuracy due to the limitations in capturing relations across sentences and documents. To ...

The wrist pulse wave under the optimal pulse pressure plays an important role in detecting human body’s physiological and pathological information. Wavelet threshold filtering is a common method for pulse wave de-...

The purpose is to study the soil’s water-soluble organic matter and improve the utilization rate of the soil layer. This exploration is based on the theories of three-dimensional fluorescence spectroscopy, deep learning, and biochar. Chernozem in Harbin ...

• A novel quantification method for pulse waveform in the entire cardiac cycle involves six quantification parameters.

Pulse waveform contains abundant physiological and pathological information. The condition of surrounding arteries can be reflected sensitively by the contour and derivative changes of pulse waves. In order to ...

This paper proposes a hierarchical text categorization (TC) approach to encoding free-text clinical notes with ICD-9-CM codes. Preliminary experimental result on the 2007 Computational Medicine Challenge data shows a hierarchical TC system has achieved ...

This paper proposes a machine learning approach to the task of assigning the international standard on classification of diseases ICD-9-CM codes to clinical records. By treating the task as a text categorisation problem, a classification system was ...

Unlike abstracts, full articles of clinical case studies provide more detailed profiles of a patient, such as signs and symptoms, and important laboratory test results of the patient from the diagnostic and treatment procedures. This paper proposes a ...