Work

Performance Evaluation in Multimedia Retrieval

Year: 2024

Type: article

Abstract: Performance evaluation in multimedia retrieval, as in the information retrieval domain at large, relies heavily on retrieval experiments, employing a broad range of techniques and metrics. These can involve human-in-the-loop and machine-only settings for the retrieval process itself and the subsequent verification of results. Such experiments can be elaborate and use-case-specific, which can make them difficult to compare or replicate. In this article, we present a formal model to express all relevant aspects of such retrieval experiments, as well as a flexible open-source evaluation infrastructure that implements the model. These contributions intend to make a step towards lowering the hurdles for conducting retrieval experiments and improving their reproducibility.

Source: ACM Transactions on Multimedia Computing Communications and Applications

DOI: 10.1145/3678881

Authors: Loris Sauter, Ralph Gasser, Heiko Schuldt, Abraham Bernstein, Luca Rossetto

Institutions: University of Basel, University of Zurich

Language: English

Topic: Information Retrieval and Search Behavior

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Award: MediaGraph