Personal skill information on social media is at the core of many interesting applications. In this paper, we propose a factor graph based approach to automatically infer skills from personal profile incorporated with both personal and skill connections. We first extract personal connections with similar academic and business background (e.g. co-major, co-university, and co-corporation). We then extract skill connections between skills from the same person. To well integrate various kinds of connections, we propose a joint prediction factor graph (JPFG) model to collectively infer personal skills with help of personal connection factor, skill connection factor, besides the normal textual attributes. Evaluation on a large-scale dataset from Linkedln.com validates the effectiveness of our approach.
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