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 "sequenceresistant" tasks for which simple classes of local features perform as well as richer features and models.
REF present a general framework for studying sequences of search activities performed by users.
An analysis framework for search sequences
CIKM
Computer Science