The Notion of Motif Where Disciplines Intersect: Folkloristics, Narrativity, Bioinformatics, Automatic Text Processing and Linguistics

2019 ◽  
pp. 17-46
Author(s):  
Dominique Legallois ◽  
Stefan Koch
Keyword(s):  
Text Processing ◽  
And Linguistics ◽  
Automatic Text

scholarly journals THE ROLE OF THE QUESTION-ANSWER FORM OF WRITING IN THE «WRITER'S DIARY»

2021 ◽  
Author(s):  
Valeriya K. Marchenko ◽  
Keyword(s):  
Text Processing ◽  
Automatic Text

This article is devoted to the study of the role of the question-answer form of writing in the "Writer’s Diary" by F.M. Dostoevsky using automatic text processing programs.

Verification of Uncurated Protein Annotations

2010 ◽  
pp. 301-314
Author(s):  
Francisco M. Couto ◽  
Mário J. Silva ◽  
Vivian Lee ◽  
Emily Dimmer ◽  
Evelyn Camon ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Molecular Biology ◽  
Domain Knowledge ◽  
Text Processing ◽  
The Other ◽  
Research Projects ◽  
Evidence Text ◽  
Biological Sources ◽  
Biology Research ◽  
Automatic Text

Molecular Biology research projects produced vast amounts of data, part of which has been preserved in a variety of public databases. However, a large portion of the data contains a significant number of errors and therefore requires careful verification by curators, a painful and costly task, before being reliable enough to derive valid conclusions from it. On the other hand, research in biomedical information retrieval and information extraction are nowadays delivering Text Mining solutions that can support curators to improve the efficiency of their work to deliver better data resources. Over the past decades, automatic text processing systems have successfully exploited biomedical scientific literature to reduce the researchers’ efforts to keep up to date, but many of these systems still rely on domain knowledge that is integrated manually leading to unnecessary overheads and restrictions in its use. A more efficient approach would acquire the domain knowledge automatically from publicly available biological sources, such as BioOntologies, rather than using manually inserted domain knowledge. An example of this approach is GOAnnotator, a tool that assists the verification of uncurated protein annotations. It provided correct evidence text at 93% precision to the curators and thus achieved promising results. GOAnnotator was implemented as a web tool that is freely available at http://xldb.di.fc.ul.pt/rebil/tools/goa/.

scholarly journals Automated News Classification using N-gram Model and Key Features of Nepali Language

SCITECH Nepal ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. 64-69
Author(s):  
Dinesh Dangol ◽  
Rupesh Dahi Shrestha ◽  
Arun Timalsina
Keyword(s):  
Text Classification ◽  
English Language ◽  
Promising Result ◽  
Text Processing ◽  
Automatic Text Classification ◽  
Key Features ◽  
Research Experiment ◽  
N Gram ◽  
Automated Text Processing ◽  
Automatic Text

With an increasing trend of publishing news online on website, automatic text processing becomes more and more important. Automatic text classification has been a focus of many researchers in different languages for decades. There is a huge amount of research repository on features of English language and their uses on automated text processing. This research implements Nepali language key features for automatic text classification of Nepali news. In particular, the study on impact of Nepali language based features, which are extremely different than English language is more challenging because of the higher level of complexity to be resolved. The research experiment using vector space model, n-gram model and key feature based processing specific to Nepali language shows promising result compared to bag-of-words model for the task of automated Nepali news classification.

Exodus: Materials in Automatic Text Processing. Part I: Morphological, Syntactical and Literary Case Studies. Part II: Concordance

1985 ◽  
Vol 104 (4) ◽  
pp. 696
Author(s):  
Peter C. Patton ◽  
Ferenc Postma ◽  
Eep Talstra ◽  
Marc Vervenne
Keyword(s):  
Case Studies ◽  
Text Processing ◽  
Automatic Text

scholarly journals Predicate word dictionary as a tool for automatic text processing by situational-relational analysis

2021 ◽  
Author(s):  
Valery A. Mishlanov ◽  
◽  
Liudmila А. Kadzhaya ◽  
Vladimir A. Salimovskiy ◽  
Ivan V. Smirnov ◽  
...  
Keyword(s):  
Knowledge Acquisition ◽  
Text Analysis ◽  
Text Processing ◽  
Relational Analysis ◽  
Dictionary Structure ◽  
Automatic Text

This paper discusses the issues of improving a predicate word dictionary structure that is used in solving problems of knowledge acquisition and text analysis. The principle of open dictionary architecture is shown. It takes into account the stylistic differentiation of speech and involves the description of predicate word subsystems functioning in separate speech varieties.

scholarly journals BiDI: Using Machine Learning to collect and facilitate remote access to biomedical databases (Preprint)

2020 ◽  
Author(s):  
Eduardo Rosado ◽  
Miguel Garcia-Remesal Sr ◽  
Sergio Paraiso-Medina Sr ◽  
Alejandro Pazos Sr ◽  
Victor Maojo Sr
Keyword(s):  
Deep Learning ◽  
Text Processing ◽  
Biomedical Literature ◽  
Remote Access ◽  
Pubmed Central ◽  
Processing Pipeline ◽  
Learning Techniques ◽  
Different Types ◽  
Automatic Text ◽  
Biomedical Databases

BACKGROUND Currently, existing biomedical literature repositories do not commonly provide users with specific means to locate and remotely access biomedical databases. OBJECTIVE To address this issue we developed BiDI (Biomedical Database Inventory), a repository linking to biomedical databases automatically extracted from the scientific literature. BiDI provides an index of data resources and a path to access them in a seamless manner. METHODS We designed an ensemble of Deep Learning methods to extract database mentions. To train the system we annotated a set of 1,242 articles that included mentions to database publications. Such a dataset was used along with transfer learning techniques to train an ensemble of deep learning NLP models based on the task of database publication detection. RESULTS The system obtained an f1-score of 0.929 on database detection, showing high precision and recall values. Applying this model to the PubMed and PubMed Central databases we identified over 10,000 unique databases. The ensemble also extracts the web links to the reported databases, discarding the irrelevant links. For the extraction of web links the model achieved a cross-validated f1-score of 0.908. We show two use cases, related to “omics” and the COVID-19 pandemia. CONCLUSIONS BiDI enables the access of biomedical resources over the Internet and facilitates data-driven research and other scientific initiatives. The repository is available at (http://gib.fi.upm.es/bidi/) and will be regularly updated with an automatic text processing pipeline. The approach can be reused to create repositories of different types (biomedical and others).

Sign in / Sign up

Export Citation Format

Share Document