On contextual photo tag recommendation

McParlane, P. J., Moshfeghi, Y. and Jose, J. M. (2013) On contextual photo tag recommendation. In: 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, Dublin, Ireland, 28 Jul - 1 Aug 2013, pp. 965-968. (doi: 10.1145/2484028.2484160)

Abstract

Image tagging is a growing application on social media websites, however, the performance of many auto-tagging methods are often poor. Recent work has exploited an image's context (e.g. time and location) in the tag recommendation process, where tags which co-occur highly within a given time interval or geographical area are promoted. These models, however, fail to address how and when different image contexts can be combined. In this paper, we propose a weighted tag recommendation model, building on an existing state-of-the-art, which varies the importance of time and location in the recommendation process, based on a given set of input tags. By retrieving more temporally and geographically relevant tags, we achieve statistically significant improvements to recommendation accuracy when testing on 519k images collected from Flickr. The result of this paper is an important step towards more effective image annotation and retrieval systems.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Jose, Professor Joemon and Mcparlane, Mr Philip and Moshfeghi, Dr Yashar
• Authors: McParlane, P. J., Moshfeghi, Y., and Jose, J. M.
• College/School: College of Science and Engineering > School of Computing Science