Improving Search and Navigation User Experience by Making Use of Social Data

Abstract

Available user-generated content provides a huge opportunity to contextualize and improve search and navigational processes. Currently, the huge amount of available social data requires that new forms of personalized content indexing be oriented towards a more efficient reuse and retrieval of information. Based on these considerations, this chapter presents a new system that makes use of the social profile of the user, which is automatically extracted and modeled from social network platforms, to improve the search and navigation experience of the user. This proposed system dynamically defines the social context of the user in way that allows it to be positively used to improve his navigational experience. In this chapter, the authors provide a set of visualization tools that permits the user to be immersed in a user-dependent visual space that represented by a set of text boxes that are semantically related to the user query. These boxes represent possible context-aware refinement of the user search interest which are represented through different cohesive set of terms extracted from his social profile. Within this immersive system, at each step, users can deepen their searches by selecting a semantic box that best fits with their needs. This chapter also presents an evaluation aimed at testing the efficiency and the usability of the proposed system and provides real case scenarios and user studies that validate the proposed approach from the user point of view.