A k-Highest Expert Text Classification Algorithm Based on Choquet Integral
| Autor: | Shuchao Feng, Yuqi Wang, Wenqian Shang |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
business.industry
Cosine similarity Measure (physics) Pattern recognition Similarity measure computer.software_genre Statistical classification ComputingMethodologies_PATTERNRECOGNITION Categorization Similarity (network science) Choquet integral Algorithm design Data mining Artificial intelligence business computer Algorithm Mathematics |
| Zdroj: | ACIT-CSI |
| DOI: | 10.1109/acit-csi.2015.95 |
| Popis: | In recent years, the research on text classification algorithm is still a hot topic in text mining. The KNN is a classic text classification algorithm. The rule of finding the nearest neighbors directly affects the performance and precision of categorization. In this paper, we mainly focus on distance measure and similarity. We propose a new text classification algorithm which combines KNN and Choquet integral. Choquet integral provides a new way to find the k-nearest neighbors. The result of experiment shows that the performance of this method is better than the classical distance measure or similarity measure. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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