Temat: knowledge representation - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Structural representations of unstructured knowledge
Autorzy:: Traczyk, W.
Powiązania:: https://bibliotekanauki.pl/articles/309054.pdf
Data publikacji:: 2005
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: textual knowledge
knowledge representation languages
ontology
Opis:: Knowledge should be represented in a formal, structured manner if we want to process and manage it. Unfortunately a source knowledge presented in many documents has informal, unstructured shape. The goal of these considerations is to present the methods of translation from the textual, unstructured knowledge to the structured knowledge, preserving textual form.
Źródło:: Journal of Telecommunications and Information Technology; 2005, 3; 81-86
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Contextual probability
Autorzy:: Wang, H.
Powiązania:: https://bibliotekanauki.pl/articles/307791.pdf
Data publikacji:: 2003
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: mathematical foundations
knowledge representation
machine learning
uncertainty
data mining
Opis:: In this paper we present a new probability function G that generalizes the classical probability function. A mass function is an assignment of basic probability to some context (events, propositions). It represents the strength of support for some contexts in a domain. A context is a subset of the basic elements of interest in a domain - the frame of discernment. It is a medium to carry the "probabilistic" knowledge about a domain. The G function is defined in terms of a mass function under various contexts. G is shown to be a probability function satisfying the axioms of probability. Therefore G has all the properties attributed to a probability function. If the mass function is obtained from probability function by normalization, then G is shown to be a linear function of probability distribution and a linear function of probability. With this relationship we can estimate probability distribution from probabilistic knowledge carried in some contexts without any model assumption.
Źródło:: Journal of Telecommunications and Information Technology; 2003, 3; 92-97
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Semantic Knowledge Management and Blockchain-based Privacy for Internet of Things Applications
Autorzy:: Lamri, Manal
Sabri, Lyazid
Powiązania:: https://bibliotekanauki.pl/articles/2142317.pdf
Data publikacji:: 2022
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: hyperledger fabric
ontology
security of distributed system
spatio-temporal knowledge representation
Opis:: Design of distributed complex systems raises several important challenges, such as: confidentiality, data authentication and integrity, semantic contextual knowledge sharing, as well as common and intelligible understanding of the environment. Among the many challenges are semantic heterogeneity that occurs during dynamic knowledge extraction and authorization decisions which need to be taken when a resource is Accessem in an open, dynamic environment. Blockchain offers the tools to protect sensitive personal data and solve reliability issues by providing a secure communication architecture. However, setting-up blockchain-based applications comes with many challenges, including processing and fusing heterogeneous information from various sources. The ontology model explored in this paper relies on a unified knowledge representation method and thus is the backbone of a distributed system aiming to tackle semantic heterogeneity and to model decentralized management of Access control authorizations.We intertwine the blockchain technology with an ontological model to enhance knowledge management processes for distributed systems. Therefore, rather than reling on the mediation of a third party, the approach enhances autonomous decision-making. The proposed approach collects data generated by sensors into higher-level abstraction using n-ary hierarchical structures to describe entities and actions. Moreover, the proposed semantic architecture relies on hyperledger fabric to ensure the checking and authentication of knowledge integrity while preserving privacy.
Źródło:: Journal of Telecommunications and Information Technology; 2022, 3; 75--83
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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