Semantic Classifier Approach to Document Classification
| Autor: | Piotr Borkowski, Krzysztof Ciesielski, Mieczyslaw A. Klopotek |
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| Rok vydání: | 2020 |
| Předmět: |
Training set
Computer science business.industry Computer Science::Information Retrieval Document classification 02 engineering and technology computer.software_genre ComputingMethodologies_PATTERNRECOGNITION Categorization Semantic similarity 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Classifier (UML) computer Natural language processing Semantic gap |
| Zdroj: | Artificial Intelligence and Soft Computing ISBN: 9783030614003 ICAISC (1) |
| Popis: | We propose a new document classification method, bridging discrepancies (so-called semantic gap) between the training set and the application sets of textual data. We demonstrate its superiority over classical text classification approaches, including traditional classifier ensembles. The method consists of combining a document categorization technique with a single classifier or a classifier ensemble. |
| Databáze: | OpenAIRE |
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