Conference proceeding
A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity
SIGBIOMED WORKSHOP ON BIOMEDICAL NATURAL LANGUAGE PROCESSING (BIONLP 2018)
01 Jan 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We investigate the quality of task specific word embeddings created with relatively small, targeted corpora. We present a comprehensive evaluation framework including both intrinsic and extrinsic evaluation that can be expanded to named entities beyond drug name. Intrinsic evaluation results tell that drug name embeddings created with a domain specific document corpus outperformed the previously published versions that derived from a very large general text corpus. Extrinsic evaluation uses word embedding for the task of drug name recognition with Bi-LSTM model and the results demonstrate the advantage of using domain-specific word embeddings as the only input feature for drug name recognition with F1-score achieving 0.91. This work suggests that it may be advantageous to derive domain specific embeddings for certain tasks even when the domain specific corpus is of limited size.
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Details
- Title
- A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity
- Creators
- Mengnan Zhao - Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USAAaron J. Masino - Childrens Hosp Philadelphia, Dept Biomed & Hlth Informat, Philadelphia, PA 19104 USAChristopher C. Yang - Drexel UniversityAssoc Computat Linguist
- Publication Details
- SIGBIOMED WORKSHOP ON BIOMEDICAL NATURAL LANGUAGE PROCESSING (BIONLP 2018)
- Conference
- SIGBIOMED WORKSHOP ON BIOMEDICAL NATURAL LANGUAGE PROCESSING (BIONLP 2018)
- Publisher
- Assoc Computational Linguistics-Acl
- Number of pages
- 5
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Identifiers
- 991019170469204721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Medical Informatics