Frequency and recency context for the management and retrieval of personal information on mobile devices

Journal Article

Published in:

Pervasive and Mobile Computing, Elsevier, Volume 15, p.100-112 (2014)


call prediction, Context, Mobile personal information management


As users store increasingly larger amounts of personal information on their mobiles, the task of retrieving such items (e.g., contacts) becomes more difficult. We show that users can be categorized by their communication patterns and that each category benefits differently from supporting contact management applications. By examining mobile user call logs, we show that it is possible to aid retrieval tasks using relatively simple heuristics and algorithms that describe usage context, using solely the dimensions of contact use frequency and recency. We compare and discuss the results of the proposed method applied on two different mobile datasets: a large dataset from NOKIA and a smaller dataset collected by ourselves.