BLOG: Relational Modeling with Unknown Objects
In many real-world probabilistic reasoning problems, one of the questions we want to answer is: how many objects are out there? Examples of such problems range from multitarget tracking to extracting information from text documents. However, most probabilistic modeling formalisms — even firstorder ones — assume a fixed, known set of objects. We introduce a language called Blog for specifying probability distributions over relational structures that include varying sets of objects. In this paper we present Blog informally, by means of example models for multi-target tracking and citation matching. We discuss some attractive features of Blog models and some avenues of future work.