Ebook: Exploring Formal Models of Linguistic Data Structuring. Enhanced Solutions for Knowledge Management Systems Based on NLP Applications

The principal aim of this research is describing to which extent formal
models for linguistic data structuring are crucial in Natural Language
Processing (NLP) applications. In this sense, we will pay particular attention to those Knowledge Management Systems (KMS) which are
designed for the Internet, and also to the enhanced solutions they may
require. In order to appropriately deal with this topics, we will describe
how to achieve computational linguistics applications helpful to humans in establishing and maintaining an advantageous relationship with
technologies, especially with those technologies which are based on or
produce man-machine interactions in natural language.
We will explore the positive relationship which may exist between
well-structured Linguistic Resources (LR) and KMS, in order to state
that if the information architecture of a KMS is based on the formalization of linguistic data, then the system works better and is more consistent.
As for the topics we want to deal with, frist of all it is indispensable
to state that in order to structure efficient and effective Information Retrieval (IR) tools, understanding and formalizing natural language combinatory mechanisms seems to be the first operation to achieve, also
because any piece of information produced by humans on the Internet is
necessarily a linguistic act. Therefore, in this research work we will also
discuss the NLP structuring of a linguistic formalization Hybrid Model,
which we hope will prove to be a useful tool to support, improve and
refine KMSs.
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Exploring Formal Models of Linguistic Data Structuring
More specifically, in section 1 we will describe how to structure language resources implementable inside KMSs, to what extent they can
improve the performance of these systems and how the problem of linguistic data structuring is dealt with by natural language formalization
methods.
In section 2 we will proceed with a brief review of computational
linguistics, paying particular attention to specific software packages
such Intex, Unitex, NooJ, and Cataloga, which are developed according to Lexicon-Grammar (LG) method, a linguistic theory established
during the 60’s by Maurice Gross.
In section 3 we will describe some specific works useful to monitor
the state of the art in Linguistic Data Structuring Models, Enhanced
Solutions for KMSs, and NLP Applications for KMSs.
In section 4 we will cope with problems related to natural language
formalization methods, describing mainly Transformational-Generative Grammar (TGG) and LG, plus other methods based on statistical
approaches and ontologies.
In section 5 we will propose a Hybrid Model usable in NLP applications in order to create effective enhanced solutions for KMSs. Specific
features and elements of our hybrid model will be shown through some
results on experimental research work. The case study we will present
is a very complex NLP problem yet little explored in recent years, i.e.
Multi Word Units (MWUs) treatment.
In section 6 we will close our research evaluating its results and presenting possible future work perspectives.
Keywords
Knowledge Management System, Natural Language Processing, Linguistic Formal Model, Hybrid Formal Model.