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
Evaluation is central to Information Retrieval, and is how we compare the quality of systems. One im...
Abstract. With the huge increase in the volume of information available in digital form and the incr...
This paper presents the Unanimous Improvement Ratio (UIR), a measure that allows to compare systems ...
In this tutorial we present a formal account of evaluation metrics for three of the most salient inf...
We provide a uniform, general, and complete formal account of evaluation metrics for ranking, classi...
Effectiveness is a primary concern in the information retrieval (IR) field. Various metrics for IR e...
Retrieval system effectiveness can be measured in two quite different ways: by monitoring the behavi...
There are literally dozens (most likely more than one hun-dred) information retrieval effectiveness ...
Abstract — Some of the established approaches to evaluat-ing text clustering algorithms for informat...
This paper proposes a theoretical framework which models the information provided by retrieval syste...
An evaluation metric is used to evaluate the effectiveness of information retrieval systems and to j...
Although during the running of the ImageCLEF tracks there was no explicit co-ordination on the types...
Three measures of effectiveness of an information retrieval system are formulated in terms of a user...
Evaluation is central to Information Retrieval, and is how we compare the quality of systems. One im...
This report describes metrics for the evaluation of the effectiveness of segment-based retrieval bas...
Evaluation is central to Information Retrieval, and is how we compare the quality of systems. One im...
Abstract. With the huge increase in the volume of information available in digital form and the incr...
This paper presents the Unanimous Improvement Ratio (UIR), a measure that allows to compare systems ...
In this tutorial we present a formal account of evaluation metrics for three of the most salient inf...
We provide a uniform, general, and complete formal account of evaluation metrics for ranking, classi...
Effectiveness is a primary concern in the information retrieval (IR) field. Various metrics for IR e...
Retrieval system effectiveness can be measured in two quite different ways: by monitoring the behavi...
There are literally dozens (most likely more than one hun-dred) information retrieval effectiveness ...
Abstract — Some of the established approaches to evaluat-ing text clustering algorithms for informat...
This paper proposes a theoretical framework which models the information provided by retrieval syste...
An evaluation metric is used to evaluate the effectiveness of information retrieval systems and to j...
Although during the running of the ImageCLEF tracks there was no explicit co-ordination on the types...
Three measures of effectiveness of an information retrieval system are formulated in terms of a user...
Evaluation is central to Information Retrieval, and is how we compare the quality of systems. One im...
This report describes metrics for the evaluation of the effectiveness of segment-based retrieval bas...
Evaluation is central to Information Retrieval, and is how we compare the quality of systems. One im...
Abstract. With the huge increase in the volume of information available in digital form and the incr...
This paper presents the Unanimous Improvement Ratio (UIR), a measure that allows to compare systems ...