Automatically transforming full length biomedical articles into search queries for retrieving related articles
نویسندگان
چکیده
منابع مشابه
Automatically Classifying Sentences in Full-Text Biomedical Articles into Introduction, Methods, Results and Discussion
BIOMEDICAL TEXTS CAN BE TYPICALLY REPRESENTED BY FOUR RHETORICAL CATEGORIES: introduction, methods, results and discussion (IMRAD). Classifying sentences into these categories can benefit many other text-mining tasks. Although many studies have applied approaches to automatically classify sentences in MEDLINE abstracts into the IMRAD categories, few have explored the classification of sentences...
متن کاملDatabase Citation in Full Text Biomedical Articles
Molecular biology and literature databases represent essential infrastructure for life science research. Effective integration of these data resources requires that there are structured cross-references at the level of individual articles and biological records. Here, we describe the current patterns of how database entries are cited in research articles, based on analysis of the full text Open...
متن کاملAutomatically classifying the role of citations in biomedical articles.
Citations are widely used in scientific literature. The traditional model of referencing considers all citations to be the same; however, semantically, citations play different roles. By studying the context in which citations appear, it is possible to determine the role that they play. Here, we report on the development of an eight-category classification scheme, annotation using that scheme, ...
متن کاملClassifying Biomedical Articles
This paper presents a novel approach for text classification on biomedical literature, involving the use of information extracted from related web resources. Our method creates a representation of an article based on information extracted from public online databases, that is afterwards used by traditional statistical text classification algorithms. We validated this approach by implementing th...
متن کاملSemi-Automatic Indexing of Full Text Biomedical Articles
The main application of U.S. National Library of Medicine's Medical Text Indexer (MTI) is to provide indexing recommendations to the Library's indexing staff. The current input to MTI consists of the titles and abstracts of articles to be indexed. This study reports on an extension of MTI to the full text of articles appearing in online medical journals that are indexed for Medline. Using a col...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Egyptian Informatics Journal
سال: 2021
ISSN: 1110-8665
DOI: 10.1016/j.eij.2020.04.004