Most of the existing question answering models can be largely compiled into two categories: i) open domain question answering models that answer generic questions and use large-scale knowledge base along with the targeted web-corpus retrieval and ii) closed domain question answering models that address focused questioning area and use complex deep learning models. Both the above models derive answers through textual comprehension methods. Due to their inability to capture the pedagogical meaning of textual content, these models are not appropriately suited to the educational field for pedagogy. In this paper, we propose an on-the-fly conceptual network model that incorporates educational semantics. The proposed model preserves correlations between conceptual entities by applying intelligent indexing algorithms on the concept network so as to improve answer generation. This model can be utilized for building interactive conversational agents for aiding classroom learning.
The intelligent Processing technique is more and more attractive to researchers due to its ability to deal with key problems in Vehicular Ad hoc networks. However, several problems in applying intelligent processing technologies in VANETs remain open. The existing applications are comprehensively reviewed and discussed, and classified into different categories in this paper. Their strategies, advantages/disadvantages, and performances are elaborated. By generalizing different tactics in various applications related to different scenarios of VANETs and evaluating their performances, several promising directions for future research have been suggested.
Holding commercial negotiations and selecting the best supplier in supply chain management systems are among weaknesses of producers in production process. Therefore, applying intelligent systems may have an effective role in increased speed and improved quality in the selections .This paper introduces a system which tries to trade using multi-agents systems and holding negotiations between any agents. In this system, an intelligent agent is considered for each segment of chains which it tries to send order and receive the response with attendance in negotiation medium and communication with other agents .This paper introduces how to communicate between agents, characteristics of multi-agent and standard registration medium of each agent in the environment. JADE (Java Application Development Environment) was used for implementation and simulation of agents cooperation.