Abstract
Social networks provide rich information about user interests and activities representing a valuable source for search personalization. However, social information is typically large and dynamic making its exploitation to obtain relevant search results a very challenging task. This work presents a PhD project plan that investigates Social Information Retrieval. The goal is threefolds: (1) create confidence area for information search by community detection based on tags similarity (2) introduce a new notion of Social Document Profile based on user activities, and (3) propose a novel ranking model based on social relevance.