Web Service Query Selection for a Professional Social Network Members

The emergence of social networks have opened a new paradigm for Web practises from an individual (called as an actor or a member) to a professional students groups to exchange their information with their contemporaries quickly and efficiently. The social networking enables to set up relations among the actors who share common interests, activities or connections. The blending of a social network with good Web practises is the new area of research, which has opened new opportunities for activity based actors to be aware of the developments in their area without themselves asking for the information. In this paper, we present Web Service Query Selection for a Professional Social Network Members (WSQSPSNM) by considering actor's characteristic features like personal information, professional information, etc., which reflects on the Web queries generated by actors. In this method, we classify professional group members based on their hierarchical and equivalence relations with respect to professional activities. In the case of any group of actors raises a Web query, the proposed system selects appropriate Web service query for the rest of the group members based on the allocated weights, relations and level of actors. The designed WSQSPSNM is tested over an Academic Social Network (ASN) which constitutes a set of actors related to the academic profession. If any one of them raises a professional Web query, the system generates appropriate Web queries for all the group members based on relations and level. We have simulated different sets of academic professionals, and results were obtained for the average time required by a set of Web queries of actors and the accuracy of the model.

[1]  Luo Si,et al.  Identifying similar people in professional social networks with discriminative probabilistic models , 2011, SIGIR.

[2]  Jaime Simão Sichman,et al.  Trust-based recommendation for the social Web , 2012, IEEE Latin America Transactions.

[3]  Daniella Meeker,et al.  Variations in network boundary and type: A study of adolescent peer influences , 2013, Soc. Networks.

[4]  Jun Wang,et al.  Fast Pairwise Query Selection for Large-Scale Active Learning to Rank , 2013, 2013 IEEE 13th International Conference on Data Mining.

[5]  Yan Wang,et al.  User interests driven web personalization based on multiple social networks , 2012, WI&C '12.

[6]  Yan Wang,et al.  Ranking and combining social network data for web personalization , 2012, DUBMMSM '12.

[7]  Dmitri V. Kalashnikov,et al.  Exploiting Web querying for Web people search , 2012, ACM Trans. Database Syst..

[8]  Mohd Kamir Yusof,et al.  Designing an architecture for improving web query processing in heterogeneous databases access , 2011, WIMS '11.

[9]  Esteban Moro Egido,et al.  Affinity Paths and information diffusion in social networks , 2011, Soc. Networks.

[10]  Audun Jøsang,et al.  Integrating Trust with Public Reputation in Location-Based Social Networks for Recommendation Making , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[11]  Changjie Tang,et al.  Discovering Organizational Structure in Dynamic Social Network , 2009, 2009 Ninth IEEE International Conference on Data Mining.

[12]  Pallapa Venkataram,et al.  A Method of designing an Access Mechanism for Social Networks , 2013, 2013 National Conference on Communications (NCC).

[13]  Ivan Lopez-Arevalo,et al.  A strategy for identification of Web query interfaces using supervised learning , 2011, 2011 7th International Conference on Next Generation Web Services Practices.