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Zhen Sun and Xinfu Li
Named entity recognition can deeply explore semantic features and enhance the ability of vector representation of text data. This paper proposes a named entity recognition method based on multi-head attention to aim at the problem of fuzzy lexical bounda...
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Michelle P. Banawan, Jinnie Shin, Tracy Arner, Renu Balyan, Walter L. Leite and Danielle S. McNamara
Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies, and similarities i...
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Michele Soavi, Nicola Zeni, John Mylopoulos and Luisa Mich
The aim of the research is to semi-automate the process of generating formal specifications from legal contracts in natural language text form. Towards this end, the paper presents a tool, named ContrattoA, that semi-automatically conducts semantic annot...
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A. Yu. Zinoveva
Pág. 64 - 72
Today?s natural language processing research frequently addresses the issue of content semantization (including the semantization of unstructured texts such as electronic news) by means of semantic annotation or its special case, ontology-based and domai...
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Arthur M. Jacobs and Annette Kinder
In this paper, we compute the affective-aesthetic potential (AAP) of literary texts by using a simple sentiment analysis tool called SentiArt. In contrast to other established tools, SentiArt is based on publicly available vector space models (VSMs) and ...
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