An analysis framework for search sequences.

In this paper we present a general framework to study sequences of search activities performed by a user. Our framework provides (i) a vocabulary to discuss types of features, models, and tasks, (ii) straightforward feature re-use across problems, (iii) realistic baselines for many sequence analysis tasks we study, and (iv) a simple mechanism to develop baselines for sequence analysis tasks beyond those studied in this paper. Using this framework we study a set of fourteen sequence analysis tasks with a range of features and models. While we show that most tasks benefit from features based on recent history, we also identify two categories of "sequence-resistant" tasks for which simple classes of local features perform as well as richer features and models.