Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/23111
Title: Image retrieval via topic modelling of Instagram hashtags
Authors: Tsapatsoulis, Nicolas 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Keywords: Topic modelling;Instagram hashtags;Automatic image annotation;Learning by example;Image retrieval
Issue Date: 29-Oct-2020
Source: 15th International Workshop on Semantic and Social Media Adaptation & Personalization, 2020, 29- 30 October, Zakynthos, Greece
Conference: International Workshop on Semantic and Social Media Adaptation and Personalization 
Abstract: Automatic Image Annotation (AIA) is the process of assigning tags to digital images without the intervention of humans. Most of the modern automatic image annotation methods are based on the learning by example paradigm. In those methods building the training examples, that is, pairs of images and related tags, is the first critical step. We have shown in our previous studies that hashtags accompanying images in social media and especially the Instagram provide a reach source for creating training sets for AIA. However, we concluded that only 20% of the Instagram hashtags describe the actual content of the image they accompany, thus, a series of filtering steps need to apply in order to identify the appropriate hashtags. In this paper we apply graph based topic modelling on Instagram hashtags in order to predict the subject of the related images and we propose an innovativeimage retrieval scheme that can be used in the context of Instagram with minimal training requirements.
URI: https://hdl.handle.net/20.500.14279/23111
ISBN: 9781728159195
DOI: 10.1109/SMAP49528.2020.9248465
Rights: © IEEE
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Conference Papers
Affiliation : Cyprus University of Technology 
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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