Multi Agent Ontology Mapping Framework in the AQUA Question Answering System

2005 ◽  
pp. 70-79 ◽  
Author(s):  
Miklos Nagy ◽  
Maria Vargas-Vera ◽  
Enrico Motta
Keyword(s):  
Question Answering ◽  
Ontology Mapping ◽  
Question Answering System ◽  
Multi Agent

A Multi-Agent Question-Answering System for E-Learning and Collaborative Learning Environment

2014 ◽  
pp. 134-149
Author(s):  
Tannaz Alinaghi ◽  
Ardeshir Bahreininejad
Keyword(s):  
Collaborative Learning ◽  
Learning Environment ◽  
Question Answering ◽  
Question Answering System ◽  
Course Materials ◽  
Life Styles ◽  
History Of ◽  
E Learning ◽  
Multi Agent ◽  
Collaborative Learning Environment

The increasing advances of new Internet technologies in all application domains have changed life styles and interactions. E-learning and collaborative learning environment systems are originated through such changes and aim at providing facilities for people in different times and geographical locations to cooperate, collaborate, learn and work together by using various educational services. One of the most important requirements of learners in online and virtual environments is the ability to ask questions and receive appropriate answers. The nature of such environments and the lack of physical existence of teachers make such issues critical and challenging problems. This paper presents a multi-agent system for building a question-answering system in learning management systems and collaborative learning environments. In the proposed system, after validating the content of questions, all available resources including course materials, frequently asked questions and responses from other learners will be gathered and finally using a recommender system, the most appropriate answer(s) with respect to several criteria such as learner’s knowledge, research background, history of previous questions, and the candidate answers relevant to the question will be suggested. A simplified version of the system has been implemented and integrated to a well known open source collaborative learning environment system in order to simulate and evaluate the applicability and appropriateness of the proposed system. The result shows that the proposed question-answering system may be used efficiently and expanded to accommodate further advanced capabilities.

A Multi-Agent Question-Answering System for E-Learning and Collaborative Learning Environment

2011 ◽  
Vol 9 (2) ◽  
pp. 23-39 ◽  
Author(s):  
Tannaz Alinaghi ◽  
Ardeshir Bahreininejad
Keyword(s):  
Collaborative Learning ◽  
Learning Environment ◽  
Question Answering ◽  
Question Answering System ◽  
Course Materials ◽  
Life Styles ◽  
History Of ◽  
E Learning ◽  
Multi Agent ◽  
Collaborative Learning Environment

The increasing advances of new Internet technologies in all application domains have changed life styles and interactions. E-learning and collaborative learning environment systems are originated through such changes and aim at providing facilities for people in different times and geographical locations to cooperate, collaborate, learn and work together by using various educational services. One of the most important requirements of learners in online and virtual environments is the ability to ask questions and receive appropriate answers. The nature of such environments and the lack of physical existence of teachers make such issues critical and challenging problems. This paper presents a multi-agent system for building a question-answering system in learning management systems and collaborative learning environments. In the proposed system, after validating the content of questions, all available resources including course materials, frequently asked questions and responses from other learners will be gathered and finally using a recommender system, the most appropriate answer(s) with respect to several criteria such as learner’s knowledge, research background, history of previous questions, and the candidate answers relevant to the question will be suggested. A simplified version of the system has been implemented and integrated to a well known open source collaborative learning environment system in order to simulate and evaluate the applicability and appropriateness of the proposed system. The result shows that the proposed question-answering system may be used efficiently and expanded to accommodate further advanced capabilities.

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