A Global Lexical Dataset (GLED) with cognate annotation and phonological alignments

This repository comprises a dataset developed from a subset of ASJP, in which all lemmas are presented in a broad phonological transcription, automatically annotated for cognacy, and phonologically aligned. Per-family NEXUS files with binary annotation of presence/absence of cognate sets are also available. The dataset is intended to facilitate prototyping studies and methods in quantitative historical linguistics

A INTRODUÇÃO DO ULISSES CENTRÍFUGO: TRADUÇÃO E COMENTÁRIO DO CANTO XXVI DO “INFERNO” DE DANTE ALIGHIERI

Este trabalho apresenta uma tradução comentada do canto XXVI do Inferno de Dante Alighieri, oferecida como suporte de estudo para pesquisas em âmbito de historiografia literária. O texto é comentado verso a verso, com atenção filológica na tradução, e pensado como suplemento ao original ao qual é dependente, sem objetivos estéticos

Aplicação da metodologia DMAIC para melhoria de desempenho de uma equipe de vendas do setor de calçados e confecções

Trabalho de Conclusão de Curso (Graduação)Uma equipe qualificada da área de vendas é alma de qualquer pequeno ou médio negócio no varejo, pois é através dela que se pode vender aquilo que o cliente deseja, atribuindo, em primeiro lugar, satisfação através de um atendimento de qualidade. Além disso, é através da satisfação do cliente e consequentemente, da fidelização que os resultados podem alavancar o faturamento da empresa. O trabalho tem como objetivo obter melhorias no desempenho de vendas dos atendentes da loja através da qualidade e produtividade de atendimento. Para isso, foi realizada uma pesquisa-ação com aplicação de uma metodologia da Gestão da Qualidade, denominada DMAIC. A aplicação da metodologia possibilitou uma análise geral do desempenho de vendas da equipe estudada, identificando os principais pontos responsáveis por níveis baixos de desempenho quando analisados indicadores secundários: “Ticket Médio”, “Produto por Atendimento” e “Taxa de Conversão”. Com a coleta de dados e análise dos processos de vendas, foi possível identificar variados pontos de falhas com as respectivas causas raízes. Com a aplicação da metodologia, além de identificar as falhas do processo, foi possível formular um plano de ações com as principais melhorias: treinamento da equipe de vendas, melhoria na gestão, preparação de loja e alcance de indicadores de crescimento

Computer-Assisted Language Comparison in Practice. Tutorials on Computational Approaches to the History and Diversity of Languages. Volume I

This document summarizes all contributions to the blog "Computer-Assisted Language Comparison in Practice" from 2018, online also available under https://calc.hypotheses.org

Computer-Assisted Language Comparison in Practice. Tutorials on Computational Approaches to the History and Diversity of Languages. Volume II

This document summarizes all contributions to the blog "Computer-Assisted Language Comparison in Practice" from 2019, online also available under https://calc.hypotheses.org

CLICS² An Improved Database of Cross-Linguistic Colexifications : Assembling Lexical Data with the Help of Cross-Linguistic Data Formats

International audienceThe Database of Cross-Linguistic Colexifications (CLICS), has established a computer-assisted framework for the interactive representation of cross-linguistic colexification patterns. In its current form, it has proven to be a useful tool for various kinds of investigation into cross-linguistic semantic associations , ranging from studies on semantic change, patterns of conceptualization, and linguistic pale-ontology. But CLICS has also been criticized for obvious shortcomings, ranging from the underlying dataset, which still contains many errors, up to the limits of cross-linguistic colexification studies in general. Building on recent standardization efforts reflected in the Cross-Linguistic Data Formats initiative (CLDF) and novel approaches for fast, efficient, and reliable data aggregation, we have created a new database for cross-linguistic colexifications, which not only supersedes the original CLICS database in terms of coverage but also offers a much more principled procedure for the creation, curation and aggregation of datasets. The paper presents the new database and discusses its major features

Sequence comparison in computational historical linguistics

With increasing amounts of digitally available data from all over the world, manual annotation of cognates in multi-lingual word lists becomes more and more time-consuming in historical linguistics. Using available software packages to pre-process the data prior to manual analysis can drastically speed-up the process of cognate detection. Furthermore, it allows us to get a quick overview on data which have not yet been intensively studied by experts. LingPy is a Python library which provides a large arsenal of routines for sequence comparison in historical linguistics. With LingPy, linguists can not only automatically search for cognates in lexical data, but they can also align the automatically identified words, and output them in various forms, which aim at facilitating manual inspection. In this tutorial, we will briefly introduce the basic concepts behind the algorithms employed by LingPy and then illustrate in concrete workflows how automatic sequence comparison can be applied to multi-lingual word lists. The goal is to provide the readers with all information they need to (1) carry out cognate detection and alignment analyses in LingPy, (2) select the appropriate algorithms for the appropriate task, (3) evaluate how well automatic cognate detection algorithms perform compared to experts, and (4) export their data into various formats useful for additional analyses or data sharing. While basic knowledge of the Python language is useful for all analyses, our tutorial is structured in such a way that scholars with basic knowledge of computing can follow through all steps as well.This research was supported by the European Research Council Starting Grant ‘Computer-Assisted Language Comparison’ (Grant CALC 715618, J.M.L., T.T.) and the Australian Research Council’s Centre of Excellence for the Dynamics of Language (Australian National University, Grant CE140100041, S.J.G.). As part of the GlottoBank project (http://glottobank.org), this work was further supported by the Department of Linguistic and Cultural Evolution of the Max Planck Institute for the Science of Human History (Jena) and the Royal Society of New Zealand (Marsden Fund, Grant 13-UOA-121)

Sequence comparison in computational historical linguistics

With increasing amounts of digitally available data from all over the world, manual annotation of cognates in multi-lingual word lists becomes more and more time-consuming in historical linguistics. Using available software packages to pre-process the data prior to manual analysis can drastically speed-up the process of cognate detection. Furthermore, it allows us to get a quick overview on data which have not yet been intensively studied by experts. LingPy is a Python library which provides a large arsenal of routines for sequence comparison in historical linguistics. With LingPy, linguists can not only automatically search for cognates in lexical data, but they can also align the automatically identified words, and output them in various forms, which aim at facilitating manual inspection. In this tutorial, we will briefly introduce the basic concepts behind the algorithms employed by LingPy and then illustrate in concrete workflows how automatic sequence comparison can be applied to multi-lingual word lists. The goal is to provide the readers with all information they need to (1) carry out cognate detection and alignment analyses in LingPy, (2) select the appropriate algorithms for the appropriate task, (3) evaluate how well automatic cognate detection algorithms perform compared to experts, and (4) export their data into various formats useful for additional analyses or data sharing. While basic knowledge of the Python language is useful for all analyses, our tutorial is structured in such a way that scholars with basic knowledge of computing can follow through all steps as well

CLICS2: An improved database of cross-linguistic colexifications assembling lexical data with the help of cross-linguistic data formats

The Database of Cross-Linguistic Colexifications (CLICS), has established a computer-assisted framework for the interactive representation of cross-linguistic colexification patterns. In its current form, it has proven to be a useful tool for various kinds of investigation into cross-linguistic semantic associations, ranging from studies on semantic change, patterns of conceptualization, and linguistic paleontology. But CLICS has also been criticized for obvious shortcomings, ranging from the underlying dataset, which still contains many errors, up to the limits of cross-linguistic colexification studies in general. Building on recent standardization efforts reflected in the Cross-Linguistic Data Formats initiative (CLDF) and novel approaches for fast, efficient, and reliable data aggregation, we have created a new database for cross-linguistic colexifications, which not only supersedes the original CLICS database in terms of coverage but also offers a much more principled procedure for the creation, curation and aggregation of datasets. The paper presents the new database and discusses its major features