جستجوی مقالات مرتبط با کلیدواژه "semantic web" در نشریات گروه "فناوری اطلاعات"

Artificial intelligence is a branch of the science of producing and studying machines that aim to stimulate human intelligence processes. The main goal of artificial intelligence is to optimize routine processes, improve their speed and efficiency. As a result, the number of functions and services that use artificial intelligence continues to increase worldwide. Today, artificial intelligence has entered the field of education and training and is rapidly replacing traditional methods with modern methods. In this article, we discuss the functions of artificial intelligence in the field of education and electronic knowledge transfer. Considering the increasing development of virtual education in today's world, artificial intelligence can play an effective role in the field of education and electronic knowledge transfer. Artificial intelligence as a powerful tool can be used to improve the quality of education, reduce costs and increase the speed of education. This technology allows students and teachers to provide the best solutions to improve the quality of teaching and learning through intelligent and data-based systems. With the use of artificial intelligence, virtual education can become an effective and affordable method. In general conclusion, it can be said that this technology is very useful in all stages of education, including lesson planning and design, content presentation, exercises and evaluation, and it will soon become an integral part of education.

To buy his/her necessities such as books, movies, CD, music, etc., one always trusts others’ oral and written consultations and offers and include them in his/her decisions. Nowadays, regarding the progress of technologies and development of e-business in websites, a new age of digital life has been commenced with the Recommender systems. The most important objectives of these systems include attracting the customers and their confidences by detecting their interests and tastes and recommending them the most appropriate offer. Using the relationships between entities in the DBpedia ontology, this study tries to investigate the application of and extracting the information in the movie area. In the next step, the structure of Recommender System is designed and its performance is evaluated using information extracted from "MovieLens" database. This study’s endeavor is to present a comprehensive overview of Recommender systems and a proposed method based on the benefits of semantic web databases, along with the implementation compared to existing methods. Our results indicate that the proposed method outperforms in terms of efficiency and performance.

This paper presents a framework for publishing Persian linked data. First, the steps of the framework are presented including selecting target data, publishing data as RDF and HTML, linking to LOD cloud and publishing void. In order to evaluate the proposed framework, the case study of publishing some academic data from Ferdowsi University of Mashhad of Mashhad is discussed. By analyzing the experimental results of the project and classifying the problems, some publisher-oriented recommendations are proposed to improve the quality of datasets on the web.