An automatic learning of grammar for syntactic pattern recognition, 1988

The practical utility of a syntactic pattern recognizer depends on an automatic learning of pattern class grammars from a sample of patterns. The basic idea is to devise a learning process based on induction of repeated subs rings. Several techniques based on formal lattice structures, structural derivatives, information, k tails, lattice structures, structural information sequence, inductive inference and heuristic approach are widely found in the literature. The purpose of this research is to first devise a minimal finite state automaton which recognizes all patterns. The automaton is then manipulated so that the induction of repetition is captured by cycles or loops. The final phase consists of converting the reduced automaton into a context - free grammar. Now, an automatic parser for this grammar can recognize patterns which are in the respective class

Colored operads, series on colored operads, and combinatorial generating systems

We introduce bud generating systems, which are used for combinatorial generation. They specify sets of various kinds of combinatorial objects, called languages. They can emulate context-free grammars, regular tree grammars, and synchronous grammars, allowing us to work with all these generating systems in a unified way. The theory of bud generating systems uses colored operads. Indeed, an object is generated by a bud generating system if it satisfies a certain equation in a colored operad. To compute the generating series of the languages of bud generating systems, we introduce formal power series on colored operads and several operations on these. Series on colored operads are crucial to express the languages specified by bud generating systems and allow us to enumerate combinatorial objects with respect to some statistics. Some examples of bud generating systems are constructed; in particular to specify some sorts of balanced trees and to obtain recursive formulas enumerating these.Comment: 48 page

Description of predicative nouns in a Modern Greek financial corpus

This paper reports on a corpus-based description of predicative nouns in a register-diversified financial corpus. Structural linguistics (Chomsky 1981) and register analysis (Biber & Conrad 2009) are the theoretical backgrounds of this research. As predicative noun, we define a noun derived from a verb, an adjective or a noun that occurs in support verb constructions (Gross 1981).     In order to identify the predicative nouns occurring in a Modern Greek financial corpus we applied a. five Lexicon-Grammar tables containing predicative nouns, along with their distributional and transformational properties (Tziafa 2012); b. 122 finite state automata (Ioannidou 2013), representing noun phrases.