Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Zafar, Hamid"'
Publikováno v:
Journal of Web Semantics Volume 64, October 2020, 100586
Semantic Question Answering (SQA) systems automatically interpret user questions expressed in a natural language in terms of semantic queries. This process involves uncertainty, such that the resulting queries do not always accurately match the user
Externí odkaz:
http://arxiv.org/abs/2006.11534
The emergence of structured databases for Question Answering (QA) systems has led to developing methods, in which the problem of learning the correct answer efficiently is based on a linking task between the constituents of the question and the corre
Externí odkaz:
http://arxiv.org/abs/1909.12566
Autor:
Publio, Gustavo Correa, Esteves, Diego, Ławrynowicz, Agnieszka, Panov, Panče, Soldatova, Larisa, Soru, Tommaso, Vanschoren, Joaquin, Zafar, Hamid
The ML-Schema, proposed by the W3C Machine Learning Schema Community Group, is a top-level ontology that provides a set of classes, properties, and restrictions for representing and interchanging information on machine learning algorithms, datasets,
Externí odkaz:
http://arxiv.org/abs/1807.05351
Autor:
Tahira, Ulfat, Jan, Abdul Wadood, Memon, Quratulain, Ullah, Saeed, Jabeen, Norina, Zafar, Hamid, Ali, Mubarik
Publikováno v:
Journal of Pharmaceutical Negative Results; 2023 Special Issue, Vol. 14, p216-222, 7p
Publikováno v:
The Semantic Web
Question Answering (QA) systems over Knowledge Graphs (KGs) aim to provide a concise answer to a given natural language question. Despite the significant evolution of QA methods over the past years, there are still some core lines of work, which are
Autor:
Zafar, Hamid
Publikováno v:
Pakistan Forum, 1973 Feb 01. 3(5), 5-7.
Externí odkaz:
https://www.jstor.org/stable/2568993
Autor:
Correa Publio, Gustavo, Esteves, Diego, Ławrynowicz, Agnieszka, Panov, Panče, Soldatova, Larisa, Soru, Tommaso, Vanschoren, J., Zafar, Hamid
Publikováno v:
ICML 2018 Workshop on Reproducibility in Machine Learning
The ML-Schema, proposed by the W3C Machine Learning Schema Community Group, is a top-level ontology that provides a set of classes, properties, and restrictions for representing and interchanging information on machine learning algorithms, datasets,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::1c98894eb951251ebab6631238b9f6ee
https://research.tue.nl/nl/publications/2f9a12bc-ceb1-454d-a395-478a45b70da0
https://research.tue.nl/nl/publications/2f9a12bc-ceb1-454d-a395-478a45b70da0