Abstract. Many different communities have conducted research on the efficacy of relevance feedback in multimedia information systems. Unlike text IR, performance evaluation of multimedia IR systems tends to conform to the accepted standards of the community within which the work is conducted. This leads to idiosyncratic performance evaluations and hampers the ability to compare different techniques fairly. In this paper we discuss some of the shortcomings of existing multimedia IR system performance evaluations. We propose a common framework in which to discuss the differing techniques proposed for relevance feedback and we develop a strategy for fairly comparing the relative performance of the techniques.
A prototype front-end system—Cirt—which permits weighting, ranking and relevance...
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in...
Evaluation of retrieval performance is a crucial problem in content-based image retrieval (CBIR). Ma...
Relevance feedback is a mature technique that has been used to take user subjectivity into account i...
Modern large retrieval environments tend to overwhelm their users by their large output. Since all d...
Content-based image retrieval has become one of the most active research areas in the past few year...
This chapter presents an academic and research perspective on the impact and importance of ImageCLEF...
Interactive video retrieval systems are becoming popular. On the one hand, these systems try to redu...
Relevance feedback has been shown to be a very effective tool for enhancing retrieval results in tex...
© 2019 Ziying YangBatch evaluation techniques are often used to measure and compare the performance ...
The purpose of an information retrieval (IR) system is to help users accomplish a task. IR system ...
Evaluation is a major force in research, development and applications related to information retriev...
In information retrieval (IR), research aiming to reduce the cost of retrieval system evaluations ha...
Evaluation of retrieval performance is a crucial problem in content-based image retrieval (CBIR). Ma...
This paper investigates methods for user and pseudo relevance feedback in video event retrieval. Exi...
A prototype front-end system—Cirt—which permits weighting, ranking and relevance...
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in...
Evaluation of retrieval performance is a crucial problem in content-based image retrieval (CBIR). Ma...
Relevance feedback is a mature technique that has been used to take user subjectivity into account i...
Modern large retrieval environments tend to overwhelm their users by their large output. Since all d...
Content-based image retrieval has become one of the most active research areas in the past few year...
This chapter presents an academic and research perspective on the impact and importance of ImageCLEF...
Interactive video retrieval systems are becoming popular. On the one hand, these systems try to redu...
Relevance feedback has been shown to be a very effective tool for enhancing retrieval results in tex...
© 2019 Ziying YangBatch evaluation techniques are often used to measure and compare the performance ...
The purpose of an information retrieval (IR) system is to help users accomplish a task. IR system ...
Evaluation is a major force in research, development and applications related to information retriev...
In information retrieval (IR), research aiming to reduce the cost of retrieval system evaluations ha...
Evaluation of retrieval performance is a crucial problem in content-based image retrieval (CBIR). Ma...
This paper investigates methods for user and pseudo relevance feedback in video event retrieval. Exi...
A prototype front-end system—Cirt—which permits weighting, ranking and relevance...
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in...
Evaluation of retrieval performance is a crucial problem in content-based image retrieval (CBIR). Ma...