Lazy multigram learning environment for automatic content recommendation systems

In this paper I present an environment and algorithm for lazy (incremental) construction of multigram profile models as part of IR (information retrieval) training and exploatation processes. N-grams are traditionally used for natural language text models, but they can be also successfully used for domain independent document classification. I am demonstrating results of a prototype utility which proves these ideas.