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Related Concept Videos

Language and Cognition01:27

Language and Cognition

Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
Cognitive Learning01:21

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Cognitivism01:17

Cognitivism

Cognitive psychology emerged as a significant field in the mid-20th century. It focused on understanding humans' internal mental processes. This approach emphasizes how people perceive, remember, think, and solve problems—elements critical to human cognition.
Previously dominated by behaviorism, which prioritized observable behaviors and largely ignored mental processes, psychology transformed in the 1950s. Cognitive psychologists argue that understanding how we think and process information is...
Introduction to Learning01:18

Introduction to Learning

Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
Ethical Dilemmas II01:30

Ethical Dilemmas II

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Ethical Issues01:27

Ethical Issues

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Ethical Concerns in Healthcare:

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Related Experiment Videos

Issues in learning an ontology from text.

Christopher Brewster1, Simon Jupp, Joanne Luciano

  • 1Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. C.A.Brewster@aston.ac.uk

BMC Bioinformatics
|May 12, 2009
PubMed
Summary
This summary is machine-generated.

This study developed an automated method for constructing ontologies from text, achieving high recall but lower precision for animal behaviour terms. The approach simplifies ontology creation for scientific domains, aiding exploration and formalization.

Related Experiment Videos

Area of Science:

  • Life Sciences
  • Bioinformatics
  • Computational Biology

Background:

  • Ontology construction is complex and labor-intensive.
  • Efficient methodologies are crucial for advancing life sciences.
  • Automated approaches can reduce costs and increase efficiency.

Purpose of the Study:

  • To explore rapid ontology construction from text in the animal behaviour domain.
  • To evaluate the effectiveness of automated text processing for ontology development.
  • To identify challenges in focusing ontologies from heterogeneous corpora.

Main Methods:

  • Utilized pre-existing text processing steps for cleaning input data.
  • Derived terms and structured them into hierarchies.
  • Employed lexico-syntactic patterns for term validation and subsumption testing.

Main Results:

  • Constructed an 18,055-term ontology-like structure.
  • Achieved 73% recall of animal behaviour terms with 26% precision.
  • Successfully filtered terms and identified subsumption relationships.

Conclusions:

  • Presents a systematic method for initial ontology construction requiring limited human effort.
  • Contributes to ontology learning and maintenance in scientific domains.
  • Highlights term filtering from heterogeneous corpora as a key research challenge.