Enhanced User Search Activity by Big Data Tools

Due to the emerging Big Data paradigm, traditional data management techniques result inadequate in many real life scenarios. In particular, the availability of huge amounts of data pertaining to social interactions among users calls for advanced analysis strategies. Furthermore, heterogeneity and high speed of this data require suitable data storage and management tools to be designed from scratch. In this paper, we describe a framework tailored for analyzing user interactions with intelligent systems while seeking for some domain specific information (e.g., choosing a good restaurant in a visited area). The framework enhances user quest for information by exploiting previous knowledge about their social environment, the extent of influence the users are potentially subject to and the influence they may exert on other users. It is worth noting that, gathering information about user preferences, is crucial in several scenarios like viral marketing, tourism promotion and food education.