A General Account of Effectiveness Metrics for Information Tasks: Retrieval, Filtering, and Clustering

被引：1
|
作者：
Amigo, Enrique [1 ]
Gonzalo, Julio [1 ]
Mizzaro, Stefano [2 ]
机构：
[1] UNED, ETSI Informat, C Juan de Rosal 16, Madrid 28040, Spain
[2] Univ Udine, Dept Math & CompSci, I-33100 Udine, Italy
来源：
SIGIR'14: PROCEEDINGS OF THE 37TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL | 2014年
关键词：
Evaluation; Metrics;
D O I：
10.1145/2600428.2602296
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this tutorial we will present, review, and compare the most popular evaluation metrics for some of the most salient information related tasks, covering: (i) Information Retrieval, (ii) Clustering, and (iii) Filtering. The tutorial will make a special emphasis on the specification of constraints for suitable metrics in each of the three tasks, and on the systematic comparison of metrics according to such constraints. The last part of the tutorial will investigate the challenge of combining and weighting metrics.
引用
收藏
页码：1289 / 1289
页数：1
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