Análise e Implementação de Modelos Contextuais para Desambiguação de Entidades Nomeadas em Fluxos de Mensagens

• Alexandre Davis UFMG
• Adriano C. M. Pereira UFMG

Abstract

Named entity disambiguation in message streams is a new challenge in natural language processing. The low informational rate and lack of syntactical structure in this kind of text may decrease the accuracy of traditional disambiguation approaches. In this paper, we propose to use contextual models of Twitter messages to minimize text usage. Our models are based on the behavior of social network users and on the instant in which the message has been posted. Our results show that these models perform better than approaches that consider only textual attributes.

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