NooJ is both a corpus processing tool and a linguistic development environment: it allows linguists to formalize several levels of linguistic phenomena: orthography and spelling, lexicons for simple words, multiword units and frozen expressions, inflectional, derivational and productive morphology, local, structural syntax and transformational syntax. For each of these levels, NooJ provides linguists with one or more formal tools specifically designed to facilitate the description of each phenomenon, as well as parsing tools designed to be as computationally efficient as possible. This approach distinguishes NooJ from most computational linguistic tools, which provide a single formalism that should describe everything. As a corpus processing tool, NooJ allows users to apply sophisticated linguistic queries to large corpora in order to build indices and concordances, annotate texts automatically, perform statistical analyses, etc. NooJ is freely available and linguistic modules can already be downloaded for Acadian, Arabic, Armenian, Bulgarian, Catalan, Chinese, Croatian, French, English, German, Hebrew, Greek, Hungarian, Italian, Polish, Portuguese, Spanish and Turkish. The present volume contains papers from the 2008 International NooJ conference which was held 8a10 June 2008 in Budapest. While the focus of the Budapest conference was on making NooJ compatible with other applications, the papers vary with respect to whether they regard Natural Language Processing (NLP) as a research goal or as a tool. However, they all present a slightly different problem either in the field of NLP, or in one that can be solved using NLP, or present a new development in the tool itself. The range of problems dealt with in the volume is quite varied, which will hopefully enable the readers to find contributions that are relevant to their field of interest.Selected Papers from the 2008 International NooJ Conference TamAis VAiradi, Max Silberztein, Judit Kuti ... Introduction The use of finite state automata in Natural Language Processing (NLP) is advantageous because these ... The speed of an automaton does not depend on its size (i.e. number of states) but rather on the number of transitions needed to arrive at a final state starting from the initial state.
|Title||:||Applications of Finite-State Language Processing|
|Author||:||Tamás Váradi, Max Silberztein, Judit Kuti|
|Publisher||:||Cambridge Scholars Publishing - 2010-10-12|