Neural finite-state transducers: a bottom-up approach to natural language processing

Author(s):  
R. Pozarlik
Author(s):  
Mans Hulden

Finite-state machines—automata and transducers—are ubiquitous in natural-language processing and computational linguistics. This chapter introduces the fundamentals of finite-state automata and transducers, both probabilistic and non-probabilistic, illustrating the technology with example applications and common usage. It also covers the construction of transducers, which correspond to regular relations, and automata, which correspond to regular languages. The technologies introduced are widely employed in natural language processing, computational phonology and morphology in particular, and this is illustrated through common practical use cases.


2018 ◽  
Vol 11 (3) ◽  
pp. 1-25
Author(s):  
Leonel Figueiredo de Alencar ◽  
Bruno Cuconato ◽  
Alexandre Rademaker

ABSTRACT: One of the prerequisites for many natural language processing technologies is the availability of large lexical resources. This paper reports on MorphoBr, an ongoing project aiming at building a comprehensive full-form lexicon for morphological analysis of Portuguese. A first version of the resource is already freely available online under an open source, free software license. MorphoBr combines analogous free resources, correcting several thousand errors and gaps, and systematically adding new entries. In comparison to the integrated resources, lexical entries in MorphoBr follow a more user-friendly format, which can be straightforwardly compiled into finite-state transducers for morphological analysis, e.g. in the context of syntactic parsing with a grammar in the LFG formalism using the XLE system. MorphoBr results from a combination of computational techniques. Errors and the more obvious gaps in the integrated resources were automatically corrected with scripts. However, MorphoBr's main contribution is the expansion in the inventory of nouns and adjectives. This was carried out by systematically modeling diminutive formation in the paradigm of finite-state morphology. This allowed MorphoBr to significantly outperform analogous resources in the coverage of diminutives. The first evaluation results show MorphoBr to be a promising initiative which will directly contribute to the development of more robust natural language processing tools and applications which depend on wide-coverage morphological analysis.KEYWORDS: computational linguistics; natural language processing; morphological analysis; full-form lexicon; diminutive formation. RESUMO: Um dos pré-requisitos para muitas tecnologias de processamento de linguagem natural é a disponibilidade de vastos recursos lexicais. Este artigo trata do MorphoBr, um projeto em desenvolvimento voltado para a construção de um léxico de formas plenas abrangente para a análise morfológica do português. Uma primeira versão do recurso já está disponível gratuitamente on-line sob uma licença de software livre e de código aberto. MorphoBr combina recursos livres análogos, corrigindo vários milhares de erros e lacunas. Em comparação com os recursos integrados, as entradas lexicais do MorphoBr seguem um formato mais amigável, o qual pode ser compilado diretamente em transdutores de estados finitos para análise morfológica, por exemplo, no contexto do parsing sintático com uma gramática no formalismo da LFG usando o sistema XLE. MorphoBr resulta de uma combinação de técnicas computacionais. Erros e lacunas mais óbvias nos recursos integrados foram automaticamente corrigidos com scripts. No entanto, a principal contribuição de MorphoBr é a expansão no inventário de substantivos e adjetivos. Isso foi alcançado pela modelação sistemática da formação de diminutivos no paradigma da morfologia de estados finitos. Isso possibilitou a MorphoBr superar de forma significativa recursos análogos na cobertura de diminutivos. Os primeiros resultados de avaliação mostram que o MorphoBr constitui uma iniciativa promissora que contribuirá de forma direta para conferir robustez a ferramentas e aplicações de processamento de linguagem natural que dependem de análise morfológica de ampla cobertura.PALAVRAS-CHAVE: linguística computacional; processamento de linguagem natural; análise morfológica; léxico de formas plenas; formação de diminutivos.


2021 ◽  
Author(s):  
Christoph Stich ◽  
Emmanouil Tranos ◽  
Max Nathan

This paper proposes a new methodological framework to identify economic clusters over space and time. We employ a unique open source dataset of geolocated and archived business webpages and interrogate them using Natural Language Processing to build bottom-up classi- fications of economic activities. We validate our method on an iconic UK tech cluster – Shoreditch, East London. We benchmark our results against existing case studies and admin- istrative data, replicating the main features of the cluster and providing fresh insights. As well as overcoming limitations in conventional industrial classification, our method addresses some of the spatial and temporal limitations of the clustering literature.


2011 ◽  
Vol 17 (2) ◽  
pp. 141-144
Author(s):  
ANSSI YLI-JYRÄ ◽  
ANDRÁS KORNAI ◽  
JACQUES SAKAROVITCH

For the past two decades, specialised events on finite-state methods have been successful in presenting interesting studies on natural language processing to the public through journals and collections. The FSMNLP workshops have become well-known among researchers and are now the main forum of the Association for Computational Linguistics' (ACL) Special Interest Group on Finite-State Methods (SIGFSM). The current issue on finite-state methods and models in natural language processing was planned in 2008 in this context as a response to a call for special issue proposals. In 2010, the issue received a total of sixteen submissions, some of which were extended and updated versions of workshop papers, and others which were completely new. The final selection, consisting of only seven papers that could fit into one issue, is not fully representative, but complements the prior special issues in a nice way. The selected papers showcase a few areas where finite-state methods have less than obvious and sometimes even groundbreaking relevance to natural language processing (NLP) applications.


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