| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0317515 |
| utime |
20240111140712.5 |
| mtime |
20081218235959.9 |
| title
(primary) (eng) |
Structural Poisson Mixtures for Classification of Documents |
| specification |
| page_count |
4 s. |
| media_type |
CD-ROM |
|
| serial |
| ARLID |
cav_un_epca*0317587 |
| ISBN |
978-1-4244-2174-9 |
| title
|
Proceedings of the 19th International Conference on Pattern Recognition |
| page_num |
1324-1327 |
| publisher |
| place |
Los Alamitos |
| name |
IEEE Press |
| year |
2008 |
|
|
| title
(cze) |
Strukturní Poissonovské směsi pro klasifikaci dokumentů |
| keyword |
classification of documents |
| keyword |
Poisson mixtures |
| keyword |
Structural approach |
| author
(primary) |
| ARLID |
cav_un_auth*0101091 |
| name1 |
Grim |
| name2 |
Jiří |
| institution |
UTIA-B |
| full_dept |
Department of Pattern Recognition |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101171 |
| name1 |
Novovičová |
| name2 |
Jana |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101197 |
| name1 |
Somol |
| name2 |
Petr |
| institution |
UTIA-B |
| full_dept |
Department of Pattern Recognition |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
1M0572 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0001814 |
|
| project |
| project_id |
2C06019 |
| agency |
GA MŠk |
| country |
CZ |
| ARLID |
cav_un_auth*0216518 |
|
| project |
| project_id |
GA102/07/1594 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0228611 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
Considering the statistical text classification problem we approximate class-conditional probability distributions by structurally modified Poisson mixtures. By introducing the structural model we can use different subsets of input variables to evaluate conditional probabilities of different classes in the Bayes formula. The method is applicable to document vectors of arbitrary dimension without any preprocessing. The structural optimization can be included into the EM algorithm in a statistically correct way. |
| abstract
(cze) |
V rámci statistického přístupu k problému klasifikace dokumentů jsou dokumenty reprezentovány formou /bag-of-words/. Podmíněné distribuce dokumentů v jednotlivých třídách jsou aproximovány ve tvaru strukturní poissonovské distribuční směsi. Bayesovská klasifikace dokumentů je ověřována na datových souborech Reuters a 20 NEWSGROUPS. |
| action |
| ARLID |
cav_un_auth*0245453 |
| name |
19th International Conference on Pattern Recognition |
| place |
Tampa |
| dates |
07.12.2008-11.12.2008 |
| country |
US |
|
| reportyear |
2010 |
| RIV |
IN |
| permalink |
http://hdl.handle.net/11104/0167137 |
| arlyear |
2008 |
| mrcbU56 |
hypertextový soubor 632 MB |
| mrcbU63 |
cav_un_epca*0317587 Proceedings of the 19th International Conference on Pattern Recognition 978-1-4244-2174-9 1324 1327 Los Alamitos IEEE Press 2008 |
|