no code implementations • 14 Jul 2018 • Gustavo Correa Publio, Diego Esteves, Agnieszka Ławrynowicz, Panče Panov, Larisa Soldatova, Tommaso Soru, Joaquin Vanschoren, Hamid Zafar
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, and experiments.
no code implementations • 20 Jun 2020 • Hamid Zafar, Mohnish Dubey, Jens Lehmann, Elena Demidova
Semantic Question Answering (SQA) systems automatically interpret user questions expressed in a natural language in terms of semantic queries.
1 code implementation • 27 Sep 2019 • Hamid Zafar, Maryam Tavakol, Jens Lehmann
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 corresponding entries in the database.