In this paper, we propose to incorporate such topical influence into a language model to both improve its accuracy and enable cross-stream analysis of topical influences.
we propose a novel language model called Topical Influence Language Model (TILM), which is a novel extension of a neural language model to capture the influence on the contents in one text stream by the evolving topics in another related (or possibly same) text stream.