Name
Abstract | ||
|---|---|---|
To satisfy their information needs, users usually carry out searches on retrieval systems by continuously trading off between the examination of search results retrieved by under-specified queries and the refinement of these queries through reformulation. In Information Retrieval (IR), a series of query reformulations is known as a query-session. Research in IR evaluation has traditionally been focused on the development of measures for the ad hoc task, for which a retrieval system aims to retrieve the best documents for a single query. Thus, most IR evaluation measures, with a few exceptions, are not suitable to evaluate retrieval scenarios that call for multiple refinements over a query-session. In this paper, by formally modeling a user's expected behaviour over query-sessions, we derive a session-based evaluation measure, which results in a generalization of the evaluation measure Rank Biased Precision (RBP). We demonstrate the quality of this new session-based evaluation measure, named Session RBP (sRBP), by evaluating its user model against the observed user behaviour over the query-sessions of the 2014 TREC Session track. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3341981.3344216 | ICTIR |
Keywords | Field | DocType |
session search, retrieval evaluation, user model, sRBP | Information retrieval,Computer science,User modeling | Conference |
Citations | PageRank | References |
2 | 0.36 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aldo Lipani | 1 | 2 | 0.70 |
| Ben Carterette | 2 | 21 | 5.08 |
| Emine Yilmaz | 3 | 1459 | 96.39 |