PIGA : partitioned inverted index using genetic algorithm
| dc.contributor.advisor | Ohm Sornil, advisor | th |
| dc.contributor.author | Suteera Vonganansup | th |
| dc.date.accessioned | 2014-05-05T08:54:58Z | |
| dc.date.available | 2014-05-05T08:54:58Z | |
| dc.date.issued | 2007 | th |
| dc.date.issuedBE | 2550 | th |
| dc.description | Thesis (M.S. (Computer Sience))--National Institute of Development Administration, 2007. | th |
| dc.format.extent | [x], 61 leaves ; 30 cm. | th |
| dc.format.mimetype | application/pdf | th |
| dc.identifier.uri | http://repository.nida.ac.th/handle/662723737/423 | th |
| dc.language.iso | eng | th |
| dc.publisher | National Institute of Development Administration | th |
| dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | th |
| dc.subject.lcc | Z 695.92 Su83 2007 | th |
| dc.subject.other | Automatic indexing | th |
| dc.subject.other | Text processing (Computer science) | th |
| dc.title | PIGA : partitioned inverted index using genetic algorithm | th |
| dc.type | text--thesis--master thesis | th |
| mods.genre | Thesis | th |
| mods.physicalLocation | National Institute of Development Administration. Library and Information Center | th |
| thesis.degree.department | School of Applied Statistics | th |
| thesis.degree.discipline | Computer Science | th |
| thesis.degree.grantor | National Institute of Development Administration | th |
| thesis.degree.level | Masters | th |
| thesis.degree.name | Master of Science | th |
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