Intuitive User Interface for Enhanced Search Experience

Negi, Suraj; Joseph, Shakhaf; Alemao, Cydnelle; Joseph, Vincy

doi:10.1109/cscita47329.2020.9137806

Cited by 2 publications

(1 citation statement)

References 2 publications

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“…The novel idea of their research work lies in the provision of interactive information retrieval interface design. Suraj Negi et al [16] suggested that, even with vast advancements in speed and availability, most of the search engine interface still relies on textual layouts to convey results. They aimed at developing a user interface with hand gesture recognition with the idea that an interface controlled by gestures will make user interaction more engaging.…”

Section: Search Interfacementioning

confidence: 99%

An Exploratory Study on a Reinforcement Learning Prototype for Multimodal Image Retrieval Using a Conversational Search Interface

2022

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In the realm of information, conversational search is a relatively new trend. In this study, we have developed, implemented, and evaluated a multiview conversational image search system to investigate user search behaviour. We have also explored the potential for reinforcement learning to learn from user search behaviour and support the user in the complex information seeking process. A conversational image search system may mimic a natural language discussion with a user via text or speech, and then assist the user in locating the required picture via a dialogue-based search. We modified and improved a dual-view search interface that displays discussions on one side and photos on the other. Based on the states, incentives, and dialogues in the initial run, we developed a reinforcement learning model and a customized search algorithm in the back end that predicts which reply and images would be provided to the user among a restricted set of fixed responses. Usability of the system was validated using methodologies such as Chatbot Usability Questionnaire, System Usability Scale, and User Experience Questionnaire, and the values were tabulated. The result of this usability experiment proved that most of the users found the system to be very usable and helpful for their image search.

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Section: Search Interfacementioning

confidence: 99%