Advances in Knowledge Representation

The Advances in Knowledge Representation (AKR) is an international forum for peer-reviewed research in knowledge representation. AKR aims to publish original research dedicated to representing information and knowledge about the world in a form that a computer system can use to solve complex tasks, focusing on ontologies. AKR is hosted in the Journal Portal of the Federal University of Minas Gerais using OJS.

Aims and Scope

The Journal welcomes rigorous work of theoretical, empirical, experimental, conceptual, or socio-technical nature in English. AKR is focused on research articles but also accepts in-depth review articles. Special issues in Portuguese will be announced frequently.

Keywords

Knowledge representation, artificial intelligence, ontologies, applied ontology, information science, information technology, computer science, information representation, and information retrieval.

Submissions

Submissions are always open and must follow AKR’s Author Guidelines to ensure our reviewers receive properly formatted and focused manuscripts. See also our template and make a submission

Permanent URL (PURL):

Advances in Knowledge Representation

Open Access Compliance:

This is an open access journal, which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access.

Fees:

The journal do not charge fees for publishing an article.

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An important note about the JOURNAL NAME

The original journal's name was "Frontiers of Knowledge Representation," unfortunately, another journal uses the label "Frontiers of..." in its publication. Then, we maintained our journal's name in the first phase - until 2024, vol.1 - and from 2024, vol.2, the journal was renamed to Advances in Knowledge Representation.
The Editors.

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