Jove
Visualize
Contact Us
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 Concept Videos

Survival Tree01:19

Survival Tree

464
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
464
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

1.3K
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
1.3K
Correlation and Regression00:53

Correlation and Regression

4.0K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
4.0K
Classification of Systems-II01:31

Classification of Systems-II

548
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
548
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

20.4K
It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
20.4K
Classification of Systems-I01:26

Classification of Systems-I

652
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
652

You might also read

Related Articles

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

Sort by
Same author

Automated detection of defective coffee beans based on improved YOLOv10 framework.

Current research in food science·2026
Same author

Advances and Prospects of ZIF-Based Nanoplatforms for Therapeutic and Diagnosis Strategies in Endocrine Diseases.

ACS applied bio materials·2026
Same author

Booster vaccine reduces BCG-primed mice's protection against primary Mycobacterium tuberculosis infection by raising IL-10 levels.

Vaccine·2026
Same author

Synthesis and Structure-Property Relationships of 5/8/5 Fused Tricyclic Energetic Materials Via Triazinane-to-Tetrazocane Skeleton Transformation.

Organic letters·2026
Same author

Growth Inhibition and Allelopathy Enhancement of <i>Alternanthera philoxeroides</i> Under Long-Term Exposure to Different Sound Intensities.

Plants (Basel, Switzerland)·2026
Same author

Brain cortical activation and functional connection of Tai Chi Yunshou during different tasks: An fNIRS study.

Journal of integrative medicine·2026
Same journal

RETRACTION: Multidimensional Heterogeneous Network Link Adaptation Based on Mobile Environment.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Facial Emotion Recognition Using a Novel Fusion of Convolutional Neural Network and Local Binary Pattern in Crime Investigation.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Intangible Cultural Heritage Reproduction and Revitalization: Value Feedback, Practice, and Exploration Based on the IPA Model.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: CNN Based Multiclass Brain Tumor Detection Using Medical Imaging.

Computational intelligence and neuroscience·2025
See all related articles

Related Experiment Video

Updated: Mar 22, 2026

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

2.2K

Support Vector Machine with Ensemble Tree Kernel for Relation Extraction.

Xiaoyong Liu1, Hui Fu1, Zhiguo Du2

  • 1Department of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, Guangdong 510665, China.

Computational Intelligence and Neuroscience
|April 28, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a novel ensemble learning algorithm (LXRE) for semisupervised relation extraction, improving accuracy by addressing semantic variation. Experiments show LXRE outperforms existing methods in key evaluation metrics.

Related Experiment Videos

Last Updated: Mar 22, 2026

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

2.2K

Area of Science:

  • Natural Language Processing
  • Machine Learning
  • Information Extraction

Background:

  • Traditional semisupervised relation extraction methods struggle with semantic variation, leading to inaccuracies.
  • Semantic variation poses a significant challenge in accurately identifying relationships between entities in text.

Purpose of the Study:

  • To propose a novel semisupervised relation extraction algorithm (LXRE) that overcomes the limitations of semantic variation.
  • To enhance the precision and recall of relation extraction through ensemble learning.

Main Methods:

  • Developed a novel semisupervised relation extraction algorithm named LXRE, utilizing ensemble learning.
  • Integrated two types of tree kernel-based support vector machine classifiers.
  • Employed a constrained extension seed set strategy to improve model robustness.

Main Results:

  • The LXRE algorithm demonstrated superior performance compared to two common relation extraction methods.
  • LXRE achieved better results across Precision, Recall, F-measure, and Accuracy on benchmark datasets (PropBank and AIMed).
  • The proposed method effectively mitigates inaccuracies caused by semantic variation.

Conclusions:

  • The LXRE algorithm offers a robust and effective solution for semisupervised relation extraction.
  • Ensemble learning and constrained seed set extension significantly improve relation extraction capabilities.
  • LXRE shows strong potential for practical applications in information extraction.