The invention discloses a Markov decision process model based session search method. The method comprises the following steps of 1) in a preparation stage, crawling sufficient web pages and obtaining a corpus complete set C, wherein C is a result after screening crawled web page sets, and each web page correspondingly contains a document d; and performing spontaneous session search and recording a search process by a trainer to obtain training data, and generating a training document; 2) in a training stage, preprocessing the data, and making statistics on a degree of association between words t required to be used in a retrieval stage and the document d, wherein the degree of association includes Ps(t/d) using Dirichlet smoothing and Pus(t/d) not using the Dirichlet smoothing; and 3) in the retrieval stage, receiving a query statement qi currently input by a user; calculating a degree of association between each document d in the corpus complete set C and the current query statement qi through a formula; calculating a degree of association between each document d and search of the whole session; and returning first N documents with high degree of association.