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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Language model-based automatic prefix abbreviation expansion method for biomedical big data analysis.

Xiaokun Du¹, Rongbo Zhu¹, Yanhong Li¹

¹College of Computer Science, South-Central University for Nationalities, Wuhan, China.

Future Generations Computer Systems : FGCS

|April 15, 2020

Summary

This summary is machine-generated.

This study introduces Language Model-based Automatic Abbreviation Expansion (LMAAE) to address challenges in biomedical big data analysis. LMAAE effectively expands standard and ad hoc abbreviations, improving data processing and analysis accuracy.

Keywords:

Abbreviation expansion Biomedical text analysis Language model

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Area of Science:

Biomedical Informatics
Natural Language Processing
Big Data Analytics

Background:

Increasing frequency of abbreviations in biomedical data hinders big data analysis.
Dictionary-based methods struggle with ad hoc abbreviations and lack comprehensive coverage.

Purpose of the Study:

To propose an effective automatic abbreviation expansion method for biomedical data.
To overcome limitations of existing dictionary-based approaches for handling diverse abbreviations.

Main Methods:

Developed Language Model-based Automatic Abbreviation Expansion (LMAAE).
Abbreviation segmentation, block restoration for candidate generation, and language model/clustering for filtering.
Constrained search space by focusing on prefix abbreviations and limiting partition length/effectiveness.

Main Results:

LMAAE achieves high precision for standard abbreviations, complementing dictionary methods.
Demonstrated increased precision in schema matching and knowledge fusion for ad hoc abbreviations.
Recall for standard abbreviations requires further improvement but overall method shows significant benefits.

Conclusions:

LMAAE offers a robust solution for automatic abbreviation expansion in the biomedical domain.
The method enhances the accuracy and efficiency of biomedical big data analysis.
LMAAE effectively complements existing dictionary-based approaches, particularly for ad hoc abbreviations.