Detailed Information on Publication Record
2003
Strojové učení a přirozený jazyk (abtrakt tutoriálu)
POPELÍNSKÝ, LubomírBasic information
Original name
Strojové učení a přirozený jazyk (abtrakt tutoriálu)
Name (in English)
Machine learning and natural language processing
Authors
POPELÍNSKÝ, Lubomír (203 Czech Republic, guarantor)
Edition
Ostrava, Sborník konference ZNALOSTI 2003, p. 18-19, 2 pp. 2003
Publisher
FEI VŠB-TU Ostrava
Other information
Language
Czech
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Czech Republic
Confidentiality degree
není předmětem státního či obchodního tajemství
RIV identification code
RIV/00216224:14330/03:00009163
Organization unit
Faculty of Informatics
ISBN
80-248-0229-5
Keywords in English
machine learning; natural language processing
Změněno: 21/11/2003 10:02, doc. RNDr. Lubomír Popelínský, Ph.D.
V originále
Natural language processing (NLP) aims at employing computers for natural language understanding. We focus here on application machine learning in NLP, namely on instance-based learning, Bayesian methods, transformation-based learning and inductive logic programming. Different disambiguation tasks will be discussed including morphological disambiguation and word-sense disambiguation. In the second part we will introduce application of learning for document categorization and information extraction from collection of documents. We conclude with text mining. We will present the results obtained with NLP and machine learning in NLP Lab FI MU.
In English
Natural language processing (NLP) aims at employing computers for natural language understanding. We focus here on application machine learning in NLP, namely on instance-based learning, Bayesian methods, transformation-based learning and inductive logic programming. Different disambiguation tasks will be discussed including morphological disambiguation and word-sense disambiguation. In the second part we will introduce application of learning for document categorization and information extraction from collection of documents. We conclude with text mining. We will present the results obtained with NLP and machine learning in NLP Lab FI MU.
Links
| MSM 143300003, plan (intention) |
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