Work

Exquisitor: Studying the Interplay Between Conversational Search and Relevance Feedback

Year: 2024

Type: conference-paper

Abstract: The Exquisitor search system employs two distinct paradigms for searching media collections: conversational search and user relevance feedback. These paradigms can be used independently or cooperatively within the search process. While we posit that these techniques are complementary, as conversational search can find specific examples for relevance feedback and relevance feedback can help the user better understand the collection and lead to improved queries, empirical user behavior in real-world search scenarios remains poorly understood. To explore how these approaches interact within Exquisitor, we must gather more data about user actions during sessions, as well as their post-session feedback on the system. At IVR4B, we intend to obtain this information through user interaction logs and postsession interviews.

Source: International Conference on Content-Based Multimedia Indexing (CBMI)

DOI: 10.1109/cbmi62980.2024.10859234

Authors: Omar Shahbaz Khan, Ujjwal Sharma, Stevan Rudinac, Björn Þór Jónsson

Institutions: Reykjavík University, University of Amsterdam

Language: English

Topic: Information Retrieval and Search Behavior

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Interthyr Research Foundation

Award: G8678678442