Collaborative Search Trails for Video Search

TL;DR

This paper introduces a collaborative feedback system for video search that leverages user interaction data to improve search results and exploration, leading to better user performance and preferences.

Contribution

It presents a novel approach using collaborative search trails to enhance video search effectiveness and user exploration capabilities.

Findings

Improved user performance in finding relevant videos.

Users explored more of the video collection.

Users preferred the recommendation system.

Abstract

In this paper we present an approach for supporting users in the difficult task of searching for video. We use collaborative feedback mined from the interactions of earlier users of a video search system to help users in their current search tasks. Our objective is to improve the quality of the results that users find, and in doing so also assist users to explore a large and complex information space. It is hoped that this will lead to them considering search options that they may not have considered otherwise. We performed a user centred evaluation. The results of our evaluation indicate that we achieved our goals, the performance of the users in finding relevant video clips was enhanced with our system; users were able to explore the collection of video clips more and users demonstrated a preference for our system that provided recommendations.