Parallelizing Machine Learning as a service for the end-user. Input data

Loreti, Daniela (2020) Parallelizing Machine Learning as a service for the end-user. Input data. Università di Bologna. DOI 10.6092/unibo/amsacta/6394. [Dataset]
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[thumbnail of This is the dataset described in: Parallelizing Machine Learning as a Service for the End-User, Daniela Loreti, Marco Lippi, Paolo Torroni, Future Generation Computer Systems 105 (2020) 275-286 DOI: 10.1016/j.future.2019.11.042] Archive (This is the dataset described in: Parallelizing Machine Learning as a Service for the End-User, Daniela Loreti, Marco Lippi, Paolo Torroni, Future Generation Computer Systems 105 (2020) 275-286 DOI: 10.1016/j.future.2019.11.042)
License: Creative Commons: Attribution-Share Alike 4.0 (CC BY-SA 4.0)
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Abstract

The dataset includes 50 documents downloaded from the Project Gutenberg web site, yielding 466,483 total sentences. The documents are in plain text and in English.

Abstract
Document type
Dataset
Creators
CreatorsAffiliationORCID
Loreti, DanielaDISI, Alma Mater Studiorum - Università di Bologna0000-0002-6507-7565
Keywords
machine learning, natural language processing, argument mining
Subjects
Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 Sistemi di elaborazione delle informazioni
DOI
10.6092/unibo/amsacta/6394
Contributors
Name
Affiliation
ORCID
Type
Lippi, Marco
DISMI, Università di Modena e Reggio-Emilia
Researcher
Torroni, Paolo
DISI, Alma Mater Studiorum - Università di Bologna
Researcher
Deposit date
03 Jun 2020 10:27
Last modified
03 Jun 2020 10:27
Related identifier
Related identifier type
Relation type
Code
arXiv
this upload is supplement to
DOI
this upload is supplement to
Project name
AI4EU - A European AI On Demand Platform and Ecosystem
Funding program
EC - H2020
URI
https://amsacta.unibo.it/id/eprint/6394

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