This paper proposes a location-based Rocchio framework (LRoc) ,with three variants. The method uses different kernel functions to model the term location in the feedback documents,obtains the importance information from the locations of candidate expansion terms,and integrates it into the classic Rocchio model. When selecting and evaluating the candidate expansion terms,this method not only considers term frequency,but also considers the influence of term location,which helps to obtain the expansion terms that are more likely to be relevant to the query. Finally,a series of experiments are per...
