Our work deals with calendar information as it is expressed in natural language (NL), that is to say through textual units such as prepositional phrases or noun phrases (e.g. in the 90s, at the beginning of the XVth century). We call these textual units Calendar Expressions (CE). Our work aims at showing how Information Retrieval systems can benefit from dealing with CE. In this paper we describe our overall approach which consists in a formal analysis of CEs that leads to a semantic representation. We then detail an algorithm that uses this representation to filter and rank CEs embedded in texts, according to a query containing a CE. The algorithm is integrated in an experimental search engine (called CaSE). Our representation of calendar information as it is expressed in NL and the function which computes the proximity between the two CEs, one in the text and the other in the query, provides a mean to process a query without any overlapping