Statistical Modeling and Classification — LT World

LT World

Supporters

provided by

dfki logo

with support by

eu star logofp7 logo

through

meta logo
clarin logo

as well as by

bmbf logo

through

take logo

N.B.

This site uses Google Analytics to record statistics about site visits - see Legal Information.

You are here: Home kb Information & Knowledge Technologies Statistical Modeling and Classification

Statistical Modeling and Classification


Foundations of Statistical Natural Language Processing.
Christopher D. Manning and Hinrich Schütze.
MIT Press. Cambridge, MA.,1999.

The Nature of Statistical Learning Theory.
V. Vapnik.
Springer, NY. 199



http://www.lt-world.org/hlt_survey/ltw-chapter11-2.pdf

In most applications of human language technology some tasks cannot be solved by purely deductive (rule-based) approaches, but need quantitative mechanisms to pick the most plausible out of a larger set of potential outcomes, or rank a set of possibilities. Often, the required preferences can be extracted from training examples by suitable statistical techniques. Statistical language modeling for speech recognition and text retrieval and categorization have been among the earliest applications. today this also includes speech understanding, information extraction and word sense disambiguation. Recent work in many subfields of HLT focusses on the integration of statistical (implicit) and rule-based (explicit) knowledge.


Statistical Modeling; Statistical Classification