A Method for Microblog Search by Adjusting the Language Model with Time

Abstract

Time is a good scale for a microblog search. The traditional retrieval model only uses content to query microblog information. Many studies thought that the relevant microblogs most likely appear when it is close to the instant time of query. Through an analysis of microblog data, people find that the relevant information in microblogs possibly appears when it is far from the query time. These two opinions are conflict each other. Therefore, in this paper we report a modified language model which can be used to adjust time difference with appropriate weights. This way the order of the microblogs can be readjusted. The experimental results on microblog show the model works well.