Journals Proceedings

Abstract

The rapid development of communication and networking has lessened geographical boundaries further to social networking, which enables to set up relations among people who share common interests, activities or connections. In social networks, actors (or people) often want to acquire information based on their activities, education, role, etc. The social network concept handles human relationships in networks efficiently to achieve the information provision. Due to advent of social networks, the need for flexible, adaptable and rapid response time to information provision has become increasingly important. An academic social network is grouping of a specific academic faculty group members at different levels. For example, a communication group in a research institution could have the members like professor, faculty, research students, graduate students, project staff, lab assistants, etc. At each level group members, they need relevant information on the projects currently leading on elsewhere. Hence, we feel that any one of the group member searches for related research information for his level appropriately, the system intelligently makes other group members aware of developments on the issues. For example, a professor gets some information in a concept based environment, on the other hand, the system should be providing relevant lab oriented information to lab assistant. The information need to be provided suitable to actors with different requirements, hence, to enable such intelligent way of information provision, we need to consider various characteristic features of actors such as personal information, professional information, etc. Traditional networks provide static information which are not actor adaptive, and they do not use characteristic information of actors and their profile parameters to provide dynamically adapted information. In this paper, we present an Intelligent Method of Information Provisioning in an Academic Social Network (IMIPASON) by considering actor’s characteristic features like activity, education, qualification, etc., which reflects on the web queries generated by actors. In this method, we classify academic group of actors based on their hierarchical relations with respect to academic activities. In the case of any group of actors raises a web query, the proposed system generates appropriate queries for rest of the actors who need information based on the activities of the entire group. The designed IMIPASON is tested over an Academic SOcial Network (ASON) which constitutes a set of actors related to the academic profession. The system generates appropriate queries for all the actors if any one of them desires the information. We have simulated different sets of academic actors and tested the system. Results were obtained for the accuracy of our proposed IMIPASON model, and the average service time required for generating queries for a set of actors.