title: Frequent subgraphs mining for time-dependent graphs
body: <p>I need to know if there are "<em>frequent subgraph mining</em>" algorithms that take into account time information on edges.</p>
  
  <p>Let me explain,</p>
  
  <p>I have a graph in which, nodes represent building rooms, and the edges represent the movement of an occupant among the rooms. Example: R1 and R2 are two rooms, (R1,R2, T) represents the movement of the occupant between the room R1 and the room R2 in time interval T.
  For each day, occupant moves within building rooms then these movements are saved in a graph. The same thing for all other days.Example: if we have 7 days, we will have 7 graphs.
  I want to know if there is "graph mining algorithm" or "graph algorithm" that allow extracting frequent subgraphs in a <strong>specified time interval</strong>, to learn the frequent movement of the occupant among building rooms.</p>
  
  <p>Remark: I think that <em>Apriori-based approach</em> and <em>Pattern-growth approach</em> do not consider time-dependent graphs.</p>
  
  <p>Thank you for your help.</p>