A crucial aspect of information retrieval is the process of making relevance judgments. Although this highly complex decision making procedure still eludes researchers, it is evident that a number of mental models are involved: models of the information need, retrieval system, database, user's knowl
Policy capturing models for multi-faceted relevance judgments
β Scribed by Xiaoli Huang; Ryen W. White
- Publisher
- Wiley (John Wiley & Sons)
- Year
- 2006
- Tongue
- English
- Weight
- 163 KB
- Volume
- 42
- Category
- Article
- ISSN
- 0044-7870
No coin nor oath required. For personal study only.
β¦ Synopsis
Abstract
We applied policy capturing and bootstrapping methods to investigate the relevance judgment process, with a particular focus on understanding how judges summarize an overall relevance judgment from five specific aspects of relevance. Our data come from relevance judgments made in the development of the MALACH (Multilingual Access to Large Spoken ArCHives) Speech Retrieval Test Collection. We developed a linear model for each of four relevance judges by regressing his/her overall judgments on the five specific relevance aspects. According to these models, different judges tended to assign different importance weights to different aspects. One of the linear models was applied to seven new judgment sets and was highly successful at predicting accurate overall judgments for the seven judgment sets.
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