A Model to Summarize User Action Log Files

Social networks, web portals or e-learning platforms produce in general a large amount of data everyday, normally stored in its raw format in log file systems and databases. Such data can be condensed and summarized to improve reporting performance and reduce the system load. This data summarization reduces the amount of space that is required to store software data but produces, as a side effect, a decrease of their informative capability due to an information loss. In this work we study the problem of summarizing data obtained by the log systems of chronology-dependent applications with a lot of users. In particular, we present a method to reduce the data size, collapsing the descriptions of more events in a unique descriptor or in a smaller set of descriptors and pose the optimal summarization problem.