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Yes Pos is the retail and liquor stores barcode scanning billing, and inventory management software with all the customized features related to retail industry.
Part-of-Speech Tagging, Phrase Chunking and Named Entity Recognition with Python NLTK. Taggers and chunkers trained on treebank, brown, conll2000, ieer.
Stanford CoreNLP provides a set of human language technology tools. It can give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases and syntactic dependencies, indicate which noun phrases refer to the same entities, indicate sentiment, extract particular or open-class relations between entity mentions, get the quotes people said, etc.
Disciplinas e Corpo Docente
Disciplina
CH
Nome do Professor
Titulação
Unidade
Instituição
1. Conceitos, abrangência da atuação e aplicações do Design Instrucional no ensino on-line
30
Maria Cristina W. Tavela
Mestre
João XXIII
UFJF
2. Abordagens pedagógicas e DI
30
Ana Cristina L. S. Barbosa
Doutora
ARTES
ICE/UFJF
3. Uso de ferramentas em EAD on-line
30
Tarcisio de Sousa Lima
Mestre
DCC
ICE/UFJF
4. Metodologia e análise do processo de comunicação
30
Vani Moreira Kenski
Doutora
Site Educacional
(empresa parceira)
5. Planejamento e DI
30
Adriana Clementino
Doutora
Site Educacional
6. Processo de Criação I (design e storyboard)
30
Andréa Filatro
Doutora
Site Educacional
7. Construção de textos e hipertextos
30
Paula Carolei
Doutora
Site Educacional
8. Processo de Criação II (objetos de aprendizagem, uso de padrão SCORM)
30
Cláudio Fernando André
Mestre
Site Educacional
9. Avaliação
30
Gerson Pastre
Doutor
Site Educacional
10. DI e o acompanhamento e implementação de cursos on-line
30
Fernanda C. A. Campos
Doutora
DCC
ICE/UFJF
11. Seminário de DI
20
20
Regina M. Maciel Braga
Rubens de Oliveira
Doutora
Doutor
DCC
DCC
ICE/UFJF
ICE/UFJF
12. Orientação de monografia de DI
20
20
Ana Cristina L. S. Barbosa
Vani Moreira Kenski
UFJF
SITE
OpenNLP is an organizational center for open source projects related to natural language processing. It hosts a variety of java-based NLP tools which perform sentence detection, tokenization, pos-tagging, chunking and parsing, named-entity detection, and coreference using the OpenNLP Maxent machine learning package.
ASV Toolbox is a modular collection of tools for the exploration of written language data. They work either on word lists or text and solve several linguistic classification and clustering tasks. The topics covered contain language detection, POS-tagging, base form reduction, named entity recognition, and terminology extraction.
The TreeTagger is a tool for annotating text with part-of-speech and lemma information which has been developed within the TC project at the Institute for Computational Linguistics of the University of Stuttgart. The TreeTagger has been successfully used to tag German, English, French, Italian, Dutch, Spanish, Bulgarian, Russian, Greek, Portuguese, Chinese and old French texts and is easily adaptable to other languages if a lexicon and a manually tagged training corpus are available.
Online Demo of the TreeTagger. A tool for annotating text with part-of-speech and lemma information which has been developed at the Institute for Computational Linguistics of the University of Stuttgart.
Shalmaneser is a supervised learning toolbox for shallow semantic parsing, i.e. the automatic assignment of semantic classes and roles to text. The system was developed for Frame Semantics; thus we use Frame Semantics terminology and call the classes frames and the roles frame elements. However, the architecture is reasonably general, and with a certain amount of adaption, Shalmaneser should be usable for other paradigms (e.g., PropBank roles) as well. Shalmaneser caters both for end users, and for researchers.
K. Hashimoto, C. Xiong, Y. Tsuruoka, und R. Socher. (2016)cite arxiv:1611.01587Comment: Accepted as a full paper at the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP 2017).
R. Reichart, und A. Rappoport. Proceedings of the Thirteenth Conference on Computational Natural Language Learning, Seite 156--164. Stroudsburg, PA, USA, Association for Computational Linguistics, (2009)