A Comparative Study of Conversational and Conventional Search Methods for Image Retrieval

With the continuous growth of multimedia archives, there is significant interest in developing search-effective methods to locate relevant content which are natural and intuitive to users. Conversational search presents an opportunity to address these challenges by improving multimedia search effectiveness and reducing the cognitive load on users. In this study, we conduct an experiment to investigate multi-stage conversational assistance for multimedia search, incorporating multimodal clarification questions through a text-based chat interface. In our study, we compare user experience for our conversational approach to an equivalent conventional “one-shot” text-based search approach. We find that users rate their search experience statistically signif-icantly more positively in our conversational filtering condition compared to the one shot search condition. They rate it as more attractive (p <. 001), efficient (p =. 0036), dependable (p =. 001), stimulating (p <. 01) and novel (p <. 01). Our results indicate that conversational filtering has the potential to offer a more engaging and efficient way to search, particularly in image retrieval scenarios.