A Comparative Analysis of Cascade Measures for Novelty and Diversity

Resource type
Authors/contributors
Title
A Comparative Analysis of Cascade Measures for Novelty and Diversity
Abstract
Traditional editorial effectiveness measures, such as nDCG, remain standard for Web search evaluation. Unfortunately, these traditional measures can inappropriately reward redundant information and can fail to reflect the broad range of user needs that can underlie a Web query. To address these deficiencies, several researchers have recently proposed effectiveness measures for novelty and diversity. Many of these measures are based on simple cascade models of user behavior, which operate by considering the relationship between successive elements of a result list. The properties of these measures are still poorly understood, and it is not clear from prior research that they work as intended. In this paper we examine the properties and performance of cascade measures with the goal of validating them as tools for measuring effectiveness. We explore their commonalities and differences, placing them in a unified framework; we discuss their theoretical difficulties and limitations, and compare the measures experimentally, contrasting them against traditional measures and against other approaches to measuring novelty. Data collected by the TREC 2009 Web Track is used as the basis for our experimental comparison. Our results indicate that these measures reward systems that achieve an balance between novelty and overall precision in their result lists, as intended. Nonetheless, other measures provide insights not captured by the cascade measures, and we suggest that future evaluation efforts continue to report a variety of measures.
Date
2011
Proceedings Title
Proceedings of the Fourth ACM International Conference on Web Search and Data Mining
Place
New York, NY, USA
Publisher
ACM
Pages
75–84
Series
WSDM '11
Language
en
DOI
10.1145/1935826.1935847
ISBN
978-1-4503-0493-1
Accessed
2019-01-27T21:34:38Z
Library Catalog
ACM Digital Library
Citation
Clarke, C. L. A., Craswell, N., Soboroff, I., & Ashkan, A. (2011). A Comparative Analysis of Cascade Measures for Novelty and Diversity. In Proceedings of the Fourth ACM International Conference on Web Search and Data Mining (pp. 75–84). New York, NY, USA: ACM. https://doi.org/10.1145/1935826.1935847
Field of study