LinkedIn is unarguably the necessary network for professionals. Svetlin, John and Tobias, computer scientists at University of California have produced a paper that presents LinkedVis, an interactive visual recommendation system that combines social and semantic knowledge to produce career recommendations based on the LinkedIn API.
The software looks at your LinkedIn network to identify professionals with similar career paths and produces personalized recommendations of both companies and roles. LinkedVis is developed using lightweight natural language processing and entity resolution using semantic information from a variety of end-points on the web. Various elements of the recommendation algorithm are exposed to the user through an interactive interface. User then will have the capability to manipulate different aspects and the data it operates on,allowing users to explore a variety of “what-if” scenarios around their current profile.
LinkedVis is tested on a data corpus collected from 47 users and their LinkedIn connections, as well as through a supervised study of 27 users exploring their own profile and recommendations interactively. The authors state that, the results are quite satisfactory in terms of accuracy and diversity.
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