Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1645953.1646284 | CIKM |
Keywords | Field | DocType |
search sequence,fourteen sequence analysis task,sequence analysis task,analysis framework,search activity,recent history,general framework,realistic baselines,local feature,simple mechanism,richer feature,simple class,sequential analysis,sequence analysis | Data mining,Information retrieval,Computer science,Baseline (configuration management),Vocabulary | Conference |
Citations | PageRank | References |
13 | 0.64 | 22 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiaozhu Mei | 1 | 4395 | 207.09 |
| Kristina Klinkner | 2 | 13 | 0.64 |
| Ravi Kumar | 3 | 13932 | 1642.48 |
| Andrew Tomkins | 4 | 9388 | 1401.23 |