Concept-Based Automatic Amharic Document Categorization
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Summary
This research proposed a framework that automatically categorizes Amharic documents into predefined categories using concepts using concepts, and shows that the use of concepts for an Amaric document categorizer results in 92.9% accuracy.
- Type
- article
- Published
- 2009-01-01
- Cited by
- 5
- References
- 12
- Access
- Open access
- OpenAlex
- https://openalex.org/W4906400
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:19099608
Keywords
Amharic, Categorization, Computer science, Information retrieval, Ontology
References
- Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web
- Text Categorization Using Automatically Acquired Domain Ontology
- The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation
- Methodologies, tools and languages for building ontologies: Where is their meeting point?
- Automatic Arabic Document Categorization Based on the Naïve Bayes Algorithm
- Beyond Concepts: Ontology as Reality Representation
- Ontologies - Introduction and Overview
- An kNN Model-Based Approach and Its Application in Text Categorization
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