The theme of Master project is a posibility to use arificial neural networks for textual analysis and automatic categorization of textual documents in editorial programs. The task of the work was to analyze diferent methods of text clasification using diferent neural networks (SOM, Feed Forward, Learning Vector Quantization, etc.). There are much researchers who works on text clasification and artificial neural networks, but there is no practical fitting of such research. In this work I tried to find posibilities and dificulties of practical use of text clasification. I find that very important thing is initial amount and quality of information and not all neural networks fits for solving text categorization problems.
| Identifer | oai:union.ndltd.org:LABT_ETD/oai:elaba.lt:LT-eLABa-0001:E.02~2006~D_20060611_210906-15120 |
| Date | 11 June 2006 |
| Creators | Šatas, Arūnas |
| Contributors | Daunys, Gintautas, Lauruška, Vidas, Miniotas, Darius, Laurutis, Vincas, Laurutis, Remigijus, Siauliai University |
| Publisher | Lithuanian Academic Libraries Network (LABT), Siauliai University |
| Source Sets | Lithuanian ETD submission system |
| Language | Lithuanian |
| Detected Language | English |
| Type | Master thesis |
| Format | application/pdf |
| Source | http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2006~D_20060611_210906-15120 |
| Rights | Unrestricted |
Page generated in 0.002 seconds