Paper 125 (In-Use track)

Exploring the Synergy Between Knowledge Graph and Computer Vision for Personalisation Systems

Author(s): Chun Lu, Philippe Laublet, Milan Stankovic, Filip Radulovic

Abstract: In this paper, we explore the synergy between knowledge graph and computer vision tools for personalisation systems. We propose two image user profiling approaches which map an image to knowledge graph entities representing the interests of a user who appreciates the image. We show the superiority of one of our approaches against the baseline Google Cloud Vision API in terms of accuracy and argue the importance of the capacity to create semantically useful profiles. This approach is then applied in a novel personalisation use case where we seek to select the most appropriate image to display in recommendation banners. Our proposed knowledge-based approach tries to select the images which are the most in line with the user profiles. We conduct a user study with a real commercial travel catalogue and show its promising performance in terms of persuasion, attention, efficiency and affinity. A demo about the presented approaches is made available online.

Keywords: Knowledge Graph; Computer Vision; Image; Personalisation; User Profiling; Travel; Recommender System

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