Results 1 - 10 of 6,451

Elastically Averaged Precision Alignment by

by Patrick Willoughby, B. S. Mechanical Engineering, Alexander H. Slocum , 2005
"... (This page is intentionally left blank.) Elastically Averaged Precision Alignment by ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
(This page is intentionally left blank.) Elastically Averaged Precision Alignment by

Average Precision and the Problem of Generalisation

by Simon I. Hill, Hugo Zaragoza, Ralf Herbrich, Peter J. W. Rayner - In Proceedings of the ACM SIGIR Workshop on Mathematical and Formal Methods in Information Retrieval , 2002
"... In this paper we study the problem of generalisation in information retrieval. In particular we study precision-recall curves and the average precision value. We provide two types of bounds: large-deviation bounds of the average precision and maximum deviation bounds with respect to a given point ..."
Abstract - Cited by 3 (2 self) - Add to MetaCart
In this paper we study the problem of generalisation in information retrieval. In particular we study precision-recall curves and the average precision value. We provide two types of bounds: large-deviation bounds of the average precision and maximum deviation bounds with respect to a given

A support vector method for optimizing average precision

by Yisong Yue, Thomas Finley, Filip Radlinski, Thorsten Joachims - In SIGIR ’07 , 2007
"... Machine learning is commonly used to improve ranked re-trieval systems. Due to computational difficulties, few learn-ing techniques have been developed to directly optimize for mean average precision (MAP), despite its widespread use in evaluating such systems. Existing approaches optimiz-ing MAP ei ..."
Abstract - Cited by 195 (7 self) - Add to MetaCart
Machine learning is commonly used to improve ranked re-trieval systems. Due to computational difficulties, few learn-ing techniques have been developed to directly optimize for mean average precision (MAP), despite its widespread use in evaluating such systems. Existing approaches optimiz-ing MAP

the average precision criterion

by Zhuoran Chen
"... sequence comparison methods with ..."
Abstract - Add to MetaCart
sequence comparison methods with

Estimating average precision with incomplete and imperfect judgments

by Emine Yilmaz, Javed A. Aslam - In Proc. of CIKM2006 , 2006
"... We consider the problem of evaluating retrieval systems using incomplete judgment information. Buckley and Voorhees recently demonstrated that retrieval systems can be efficiently and effectively evaluated using incomplete judgments via the bpref measure [6]. When relevance judgments are complete, t ..."
Abstract - Cited by 105 (4 self) - Add to MetaCart
, the value of bpref is an approximation to the value of average precision using complete judgments. However, when relevance judgments are incomplete, the value of bpref deviates from this value, though it continues to rank systems in a manner similar to average precision evaluated with a complete judgment

Extending Average Precision to Graded Relevance Judgments

by Stephen E. Robertson, Evangelos Kanoulas, Emine Yilmaz
"... Evaluation metrics play a critical role both in the context of comparative evaluation of the performance of retrieval systems and in the context of learning-to-rank (LTR) as objective functions to be optimized. Many different evaluation metrics have been proposed in the IR literature, with average p ..."
Abstract - Cited by 16 (0 self) - Add to MetaCart
precision (AP) being the dominant one due a number of desirable properties it possesses. However, most of these measures, including average precision, do not incorporate graded relevance. In this work, we propose a new measure of retrieval effectiveness, the Graded Average Precision (GAP). GAP generalizes

Rethinking How to Extend Average Precision to Graded Relevance

by Marco Ferrante, Nicola Ferro, Maria Maistro
"... Abstract. We present two new measures of retrieval effectiveness, in-spired by Graded Average Precision (GAP), which extends Average Pre-cision (AP) to graded relevance judgements. Starting from the random choice of a user, we define Extended Graded Average Precision (xGAP) and Expected Graded Avera ..."
Abstract - Add to MetaCart
Abstract. We present two new measures of retrieval effectiveness, in-spired by Graded Average Precision (GAP), which extends Average Pre-cision (AP) to graded relevance judgements. Starting from the random choice of a user, we define Extended Graded Average Precision (xGAP) and Expected Graded

Inferring Document Relevance via Average Precision

by Javed A. Aslam, Emine Yilmaz - In Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval , 2006
"... We consider the problem of evaluating retrieval systems using a limited number of relevance judgments. Recent work has demonstrated that one can accurately estimate average precision via a judged pool corresponding to a relatively small random sample of documents. In this work, we demonstrate that g ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
We consider the problem of evaluating retrieval systems using a limited number of relevance judgments. Recent work has demonstrated that one can accurately estimate average precision via a judged pool corresponding to a relatively small random sample of documents. In this work, we demonstrate

Bootstrap confidence intervals for Mean Average Precision

by Laurence Park, Laurence A. F. Park
"... Bootstrap confidence intervals for Mean Average Precision Due to the unconstrained nature of language, search engines (such as the Google search engine) are developed and compared by obtaining a document set, a sample set of queries and the associated relevance judgments for the queries on the docum ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Bootstrap confidence intervals for Mean Average Precision Due to the unconstrained nature of language, search engines (such as the Google search engine) are developed and compared by obtaining a document set, a sample set of queries and the associated relevance judgments for the queries

Optimizing Average Precision using Weakly Supervised Data

by Aseem Behl, C. V. Jawahar, M. Pawan Kumar
"... The performance of binary classification tasks, such as action classification and object detection, is often measured in terms of the average precision (AP). Yet it is common practice in computer vision to employ the support vector machine (SVM) classifier, which optimizes a surrogate 0-1 loss. The ..."
Abstract - Cited by 5 (3 self) - Add to MetaCart
The performance of binary classification tasks, such as action classification and object detection, is often measured in terms of the average precision (AP). Yet it is common practice in computer vision to employ the support vector machine (SVM) classifier, which optimizes a surrogate 0-1 loss
Results 1 - 10 of 6,451