Ask, don´t search: A social help engine for online social network mobile users

In this paper, we present the architectural details of Odin Help Engine, a novel social search engine that leverages online social networks and sensing data from mobile devices to find targeted answers for subjective queries and recommendation requests. In Odin, users´ queries are routed to those connections in their social network who (i) are most likely to help answer the question and (ii) can do so with a high level of confidence. Specifically, we first apply a link-based latent variable model to infer social relationships between users from their social network data to form a strength-weighted relationship graph. We then infer users´ expertise by context mining from social network data as well as from their mobile device sensor data. Lastly we apply pagerank-like algorithm that takes both relationship strength and user expertise into account to find a person that is most likely willing to answer the question posted by the user. We present the general design of the architecture and outline a location-related query example for detailed illustration.