Name
Abstract | ||
|---|---|---|
In this paper 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 in combining a document categorization technique with a single classifier or a classifier ensemble (SEMCOM algorithm - Committee with Semantic Categorizer). |
Year | Venue | Field |
|---|---|---|
2017 | arXiv: Information Retrieval | Document classification,Training set,Data mining,Categorization,Pattern recognition,Computer science,Bridging (networking),Semantic gap,Artificial intelligence,Classifier (linguistics),Linear classifier,Quadratic classifier |
DocType | Volume | Citations |
Journal | abs/1701.04292 | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Piotr Borkowski | 1 | 8 | 3.65 |
| Krzysztof Ciesielski | 2 | 296 | 29.71 |
| Mieczyslaw A. Klopotek | 3 | 366 | 78.58 |