List of Articles ontology.

• Open Access Article
  • Abstract Page
  • Full-Text
  
  1 - Ontology-Based Up gradation of Entrepreneurship Skills Using Educational Portals
  Somayeh Ahari
  Nowadays, organizational portals hold a key role in disseminating organizational information at different layers. Within their scope, educational portals are particularly significant, due to their ability in upgrading users’ knowledge and skill in realizing entrepreneur More

  Nowadays, organizational portals hold a key role in disseminating organizational information at different layers. Within their scope, educational portals are particularly significant, due to their ability in upgrading users’ knowledge and skill in realizing entrepreneurship business. Considering the geographical distributed-ness as well as job variation in entrepreneurship and the parameters which are influential in the process of designing these portals, developing a mechanism that can offer a high capability to portals in upgrading entrepreneurship skill, is of high priority. This necessitates the very features which are essential to designing efficiently these sorts of portals. In this paper, an approach is suggested according to which the features expected for designing an educational portal are represented in terms of an ontology, and it is subsequently explained how and in what way these features can on the one hand help realize entrepreneurship business and on the other hand help entrepreneurship training/education come true in a reasonable way. At the end, the capability of the proposed approach will be discussed in terms of two practical scenarios being used frequently. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  2 - A semantic sentiment recognition model based on ontology and cellular deep learning automata
  Hoshang Salehi Reza Ghaemi maryam khairabadi
  Today, social networks and communication media play a significant role in the daily life of users. Users talk and exchange information in different fields in social networks. In the sentences and comments of users, there are negative and positive feelings in relation to More

  Today, social networks and communication media play a significant role in the daily life of users. Users talk and exchange information in different fields in social networks. In the sentences and comments of users, there are negative and positive feelings in relation to the news of the day, current events, etc., and recognizing these feelings faces many challenges. So far, various methods such as machine learning, statistical approaches, artificial intelligence, etc., have been proposed for the purpose of detecting emotions, which despite their many applications; But they have not yet been able to have acceptable accuracy, transparency and accuracy. Therefore, in this article, an ontology-based semantic analysis model using cellular deep learning automata based on GMDH deep neural network is presented. Ontology approach is used to select salient features based on production rules and cellular deep learning automata is used to classify user sentiments. The main innovation of this article is the proposed algorithm that a deep learning method is developed to process only one expression and then by transferring it to the field of cellular automata, parallel or distributed processing is provided. In this article, the data sets of Amazon customers, Twitter, Facebook, fake news of COVID-19, Amazon and fake news network are used. By simulating the proposed method, it was observed that the proposed method has an average improvement of 3% compared to other methods Manuscript profile