  Understanding human activities and movements on the Web is not only important
for computational social scientists but can also offer valuable guidance for
the design of online systems for recommendations, caching, advertising, and
personalization. In this work, we demonstrate that people tend to follow
routines on the Web, and these repetitive patterns of web visits increase their
browsing behavior's achievable predictability. We present an
information-theoretic framework for measuring the uncertainty and theoretical
limits of predictability of human mobility on the Web. We systematically assess
the impact of different design decisions on the measurement. We apply the
framework to a web tracking dataset of German internet users. Our empirical
results highlight that individual's routines on the Web make their browsing
behavior predictable to 85% on average, though the value varies across
individuals. We observe that these differences in the users' predictabilities
can be explained to some extent by their demographic and behavioral attributes.
