Description

The aim of this course is to introduce the audience to the
finite-state NLP methods. The emphasis is on gaining a good
understanding of several generic finite-state techniques. The
participants learn to apply them to specific problems and to build
their own finite-state applications. The formal background is
introduced gradually and based on concrete examples.

NLP TOPICS COVERED: tokenisation, dictionaries, parsing, text
indexing, tagging. Each topic provides background for several
finite-state concepts and algorithms such as:

	     types of finite-state machines (FSMs): 
	     deterministic/non-deterministic 
	     acceptors/transducers bimachines

	     equivalence operations of FSMs 
             (determinisation/minimisation/etc.)

	     regular expressions

	     generalised pattern matching

	     rewrite rules
    
RELEVANCE/TIMELINESS: After decades of intense research, FSMs
constitute one of the most widely used formal frameworks for
NLP. Their applications are very varied, thus the ESSLI audience can
benefit from a uniform introduction covering the typical
constructs/techniques.

PREREQUISITES, LEVEL OF DIFFICULTY: see further particulars.