Identifying Web Users on the Base of their Browsing Patterns

Our aim is to develop methodology for recognition of Internet portal users on the base of their browsing patterns. This is a classification task in which we have thousands values of decision attribute and objects are described by means of sequences of symbols. We develop feature selectors which make our task tractable. Since the behaviour usually does not distinguish users, we introduce user profiles which are clusters of indiscernible users. Then, we construct classifiers which assign descriptions of user behaviour to user profiles. We also derive quality measures specific for our task.

Abstract licence: CC BY-NC-ND

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.