Jove
Visualize
Contact Us

Related Concept Videos

Classification of Signals01:30

Classification of Signals

896
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
896
Force Classification01:22

Force Classification

1.6K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.6K
Aggregates Classification01:29

Aggregates Classification

386
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
386
Classification of Neurotransmitters01:30

Classification of Neurotransmitters

3.6K
Neurotransmitters play a crucial role in the communication between neurons in the autonomic nervous system. Neurons in the autonomic nervous system can be cholinergic or adrenergic depending on the neurotransmitters synthesized. Cholinergic neurons use acetylcholine as their primary neurotransmitter. This includes all the preganglionic fibers of the sympathetic and pre- and postganglionic fibers of the parasympathetic nervous systems. In addition, neurons of the somatic nervous system also use...
3.6K
Classification of Leukocytes01:30

Classification of Leukocytes

2.7K
Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
Neutrophils are the most abundant type of granular leukocytes, comprising 50-70% of all leukocytes. They feature small, evenly distributed granules and a...
2.7K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

2.6K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
2.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same journal

Genome misassembly detection using Stash: A data structure based on stochastic tile hashing.

PloS one·2026
Same journal

Germline-mediated ubiquitous recombination in ScxCre male mice: Implications for tendon research.

PloS one·2026
Same journal

Why do Canadians host refugees? A sequential explanatory mixed-methods study protocol.

PloS one·2026
Same journal

Patient safety management activities partially mediate nursing competences and patient safety culture in Vietnam.

PloS one·2026
Same journal

Instruments that measure evidence-based practice knowledge, skills, and attitudes among health professions students: A systematic review protocol.

PloS one·2026
Same journal

A dual-stream deep learning architecture for business impact scoring and alert escalation.

PloS one·2026
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Sep 13, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.7K

Features extraction based on Naive Bayes algorithm and TF-IDF for news classification.

Li Zhang1

  • 1School of Artificial Intelligence, Zhejiang College of Security Technology, Wenzhou, Zhejiang, China.

Plos One
|July 30, 2025
PubMed
Summary

This study introduces a hybrid news classification framework, combining traditional machine learning with natural language processing (NLP). The system achieves high accuracy and efficiency for organizing online news content.

More Related Videos

Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.3K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.6K

Related Experiment Videos

Last Updated: Sep 13, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.7K
Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.3K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.6K

Area of Science:

  • Natural Language Processing
  • Machine Learning
  • Information Retrieval

Background:

  • Online news proliferation necessitates automated classification for organization and recommendation.
  • Traditional methods (e.g., TF-IDF, Naive Bayes) struggle with semantic nuances and real-time processing.
  • Existing transformer models offer high accuracy but are computationally expensive.

Purpose of the Study:

  • To develop a hybrid news classification framework that balances accuracy and computational efficiency.
  • To integrate classical machine learning with advanced NLP techniques.
  • To provide a cost-effective solution for real-world news platforms.

Main Methods:

  • Domain-Specific Feature Engineering: Tailored n-grams and entity-aware TF-IDF weighting.
  • BERT-Guided Feature Selection: Utilizing distilled BERT for contextually important word identification.
  • Hybrid Framework: Combining classical ML with NLP advancements for efficient classification.

Main Results:

  • Achieved 95.12% test precision, significantly outperforming the SVM+TF-IDF baseline (84.43%).
  • Demonstrated high efficiency, reaching 95.2% of BERT's accuracy at a fraction of the inference cost (1/52.4th).
  • Exhibited strong performance in distinguishing semantically distinct categories with low inference latency (2.1ms).

Conclusions:

  • The proposed hybrid framework offers a practical and cost-effective solution for automated news classification.
  • It effectively bridges the gap between traditional feature engineering and complex transformer models.
  • Future work includes exploring hierarchical classification and dynamic topic adaptation for improved semantic boundary refinement.