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| Content Provider | ACM Digital Library |
|---|---|
| Author | Hanbury, Allan Zuccon, Guido Palotti, Joao |
| Abstract | We explore the implications of using query variations for evaluating information retrieval systems and how these variations should be exploited to compare system effectiveness. Current evaluation approaches consider the availability of a set of topics (information needs), and only one expression of each topic in the form of a query is used for evaluation and system comparison. While there is strong evidence that considering query variations better models the usage of retrieval systems and accounts for the important user aspect of user variability, it is unclear how to best exploit query variations for evaluating and comparing information retrieval systems. We propose a framework for evaluating retrieval systems that explicitly takes into account query variations. The framework considers both the system mean effectiveness and its variance over query variations and topics, as opposed to current approaches that only consider the mean across topics or perform a topic-focused analysis of variance across systems. Furthermore, the framework extends current evaluation practice by encoding: (1) user tolerance to effectiveness variations, (2) the popularity of different query variations, and (3) the relative importance of individual topics. These extensions and our findings make information retrieval comparisons more aligned with user behaviour. |
| Starting Page | 691 |
| Ending Page | 700 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450340731 |
| DOI | 10.1145/2983323.2983723 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-10-24 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Evaluation framework Portfolio theory Query variations Information retrieval evaluation Mean variance evaluation Mean variance analysis |
| Content Type | Text |
| Resource Type | Article |
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