Procedural Knowledge Mining - A New Method for Extracting Best Practices by Applying Machine Learning on Data Graph

Autor:	Souaad Hamza-Cherif, Azzedine Chikh
Rok vydání:	2022
Předmět:	Artificial Intelligence Software
Zdroj:	Revue d'Intelligence Artificielle. 36:297-304
ISSN:	1958-5748 0992-499X
DOI:	10.18280/ria.360214
Popis:	In recent years with the increase in sharing tools and sites such as Meta, Twitter, WikiHow..., the web has become a constant and permanent source of scalable knowledge where users share their know-how in the form of procedural knowledge. This procedural knowledge, which consists of a successive set of steps for achieving a specific goal, is called good practice. Extracting and formalizing these good practices is a major asset in the field of artificial intelligence. In this context we present a new method for formalizing good practices extracted from the web, and extracting the best practice for a given request by applying the techniques of artificial learning and text summary on data graphs.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0a67e4b450b88303f19229739871ecc0 https://doi.org/10.18280/ria.360214 Zobrazit plný text záznamu