A modular architecture for systematic text categorisation
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Summary
This work examines and attempts to overcome issues caused by the lack of formal standardisation when defining text categorisation techniques and detailing how they might be appropriately integrated with each other, to indicate the potential benefits that can be gained when a formalised approach is utilised.
- Type
- dissertation
- Published
- 2013-05-01
- Cited by
- 0
- References
- 135
- Access
- Open access
- OpenAlex
- https://openalex.org/W325568
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:129153
Keywords
Computer science, Ambiguity, Set (abstract data type), Modular design, Architecture
References
- Learning to Classify Email into “Speech Acts”
- KDD, SEMMA and CRISP-DM: a parallel overview
- A Tutorial on Automated Text Categorisation
- Exploring Support Vector Machines and Random Forests for Spam Detection
- Functional Annotation of Genes Using Hierarchical Text Categorization
- Learning Rules that Classify E-Mail
- Beyond TFIDF Weighting for Text Categorization in the Vector Space Model
- Named Entity Recognition for Question Answering
- Improving Precision in Information Retrieval for Swedish using Stemming
- Word Stemming to Enhance Spam Filtering
- Using Ontologies to Strengthen Folksonomies and Enrich Information Retrieval in Weblogs: Theoretical background and corporate use-case
- Improving Text Classification by Shrinkage
- A Study of Approaches to Hypertext Categorization
- A Framework for Comparing Text Categorization Approaches
- Indexing for Fast Categorisation
- Classification of text documents
- Folksonomies : (Un) controlled vocabulary?
- Automatic Query Expansion Using SMART: TREC 3
- N-gram-based text categorization
- Folksonomies vs. Bag-of-Words: The Evaluation & Comparison of Different Types of Document Representations
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