Query-Dependent Contextualization of Streaming Data

We propose a method for linking entities in a stream of short textual documents that takes into account context both inside a document and inside the history of documents seen so far. Our method uses a generic optimization framework for combining several entity ranking functions, and we introduce a global control function to control optimization. Our results demonstrate the effectiveness of combining entity ranking functions that take into account context, which is further boosted by 6% when we use an informed global control function.