Name
Abstract | ||
|---|---|---|
A novel and efficient learning algorithm is proposed for the binary linear classification problem. The algorithm is trained using the Rocchio's relevance feedback technique and builds a classifier by the intermediate hyperplane of two common tangent hyperplanes for the given category and its complement. Experimental results presented are very encouraging and justify the need for further research. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1390334.1390547 | SIGIR |
Keywords | Field | DocType |
common tangent hyperplanes,intermediate hyperplane,relevance feedback technique,text categorization,relevance feedback,binary linear classification problem,efficient learning algorithm | Data mining,Relevance feedback,Computer science,Artificial intelligence,Hyperplane,Classifier (linguistics),Text categorization,Binary number,Pattern recognition,Algorithm,Tangent,Linear classifier,Machine learning | Conference |
Citations | PageRank | References |
4 | 0.60 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anestis Gkanogiannis | 1 | 12 | 2.23 |
| Theodore Kalamboukis | 2 | 51 | 8.43 |