Validating Ranking in Web Documents Using Normalized Social Media Information
Ahmed Samy Moursi, Nawal Ahmed El-Fishawy, Sherin Moustafa Youssef · Menoufia Journal of Electronic Engineering Research · 2016
Social Information Retrieval (SIR) is a relatively new domain which uses social information to enhance information retrieval processes. To find more interesting search results, social behavior can indicate how much these results are interesting. Social interaction over Web 2.0 are used here to enhance ranking of web results in response to a query. A dataset from Open Directory Project (ODP) is used here to show the improvement of ranking. We propose the usage of normalization and social services weights to give better performance. The proposed framework gets data from various types of social info (social bookmarking, social news, social network, discovery engines). Data is parsed into fields and significant values are used in the ranking process. Precision and Mean Average Precision (MAP) are used to evaluate results. Simulation results show better ranking with the proposed model.