Zobrazeno 1 - 10
of 225
pro vyhledávání: '"Pavel Brazdil"'
Publikováno v:
Inteligencia Artificial, Vol 25, Iss 69 (2022)
Angola is characterized by many different languages and social, cultural and political realities, which had a marked effect on Angolan Portuguese (AP). Consequently, AP is characterized by diatopic variation. One of the marked effects is in the loanw
Externí odkaz:
https://doaj.org/article/4a3b320a1fae4845a52814cd2d8fc68e
Autor:
Pavel Brazdil, Shamsuddeen H. Muhammad, Fátima Oliveira, João Cordeiro, Fátima Silva, Purificação Silvano, António Leal
Publikováno v:
Mathematics, Vol 10, Iss 18, p 3232 (2022)
This paper describes two different approaches to sentiment analysis. The first is a form of symbolic approach that exploits a sentiment lexicon together with a set of shifter patterns and rules. The sentiment lexicon includes single words (unigrams)
Externí odkaz:
https://doaj.org/article/c1a00ff052994d03a5fc87155622cf88
Autor:
Fátima Silva, Purificação Silvano, António Leal, Fátima Oliveira, Pavel Brazdil, João Cordeiro, Débora Oliveira
Publikováno v:
Linguística, Vol 13, Pp 74-114 (2018)
The present study, which is developed in the interface between linguistics and computer science within the framework of sentiment analysis, aims at making a computational analysis of opinion articles in the area of economics and finance. The main obj
Externí odkaz:
https://doaj.org/article/57eff1ebc37242358e66678c9887f794
Publikováno v:
Oslo Studies in Language, Vol 7, Iss 1 (2015)
Encontrar pessoas com interesses semelhantes dentro de um domínio pode fornecer um importante auxílio na gestão de centros de investigação. Como a produção académica é facilmente obtida em bases de dados bibliográficas e académicas, estas
Externí odkaz:
https://doaj.org/article/89de593b0f324cc7a264f0cd38c57ce0
This open access book offers a comprehensive and thorough introduction to almost all aspects of metalearning and automated machine learning (AutoML), covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ens
Publikováno v:
Metalearning ISBN: 9783030670238
SummaryThis chapter discusses dataset characteristics that play a crucial role in many metalearning systems. Typically, they help to restrict the search in a given configuration space. The basic characteristic of the target variable, for instance, de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0004a95fe8d01208b37b5184e2a92074
https://doi.org/10.1007/978-3-030-67024-5_4
https://doi.org/10.1007/978-3-030-67024-5_4
Publikováno v:
Metalearning ISBN: 9783030670238
SummaryThis chapter starts by describing the organization of the book, which consists of three parts. Part I discusses some basic concepts, including, for instance, what metalearning is and how it is related to automatic machine learning (AutoML). Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5ba39720b498971b453cdc222349295
https://doi.org/10.1007/978-3-030-67024-5_1
https://doi.org/10.1007/978-3-030-67024-5_1
Publikováno v:
Metalearning ISBN: 9783030670238
This chapter focuses on metalearning approaches that have been applied to data streams. This is an important area, as many real-world data arrive in the form of a stream of observations. We first review some important aspects of the data stream setti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2725ebaf7a6d8d45573aee3fac8a00b7
https://doi.org/10.1007/978-3-030-67024-5_11
https://doi.org/10.1007/978-3-030-67024-5_11
Publikováno v:
Metalearning ISBN: 9783030670238
This chapter discusses some approaches that exploit metalearning methods in ensemble learning. It starts by presenting a set of issues, such as the ensemble method used, which affect the process of ensemble learning and the resulting ensemble. In thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::073378e91da7a969e631d89d0d176072
https://doi.org/10.1007/978-3-030-67024-5_10
https://doi.org/10.1007/978-3-030-67024-5_10
Publikováno v:
Metalearning ISBN: 9783030670238
SummaryAs metaknowledge has a central role in many approaches discussed in this book, we address the issue of what kind of metaknowledge is used in different metalearning/AutoML tasks, such as algorithm selection, hypeparameter optimization, and work
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46cb9bc005b08381de3ce1cf87e19760
https://doi.org/10.1007/978-3-030-67024-5_18
https://doi.org/10.1007/978-3-030-67024-5_18