Proceedings of the 2017 ACM on Conference on Information and Knowledge Management 2017
DOI: 10.1145/3132847.3133137
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Recipe Popularity Prediction with Deep Visual-Semantic Fusion

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Cited by 30 publications
(19 citation statements)
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“…Piotrkowicz et al predicted popularity of news articles using only headline features (Piotrkowicz et al 2017). Sanjo et al proposed a visual-semantic fusion model for online recipe popularity prediction, leveraging image and short text features in recipes (Sanjo and Katsurai 2017). User-guided hierarchical attention network (Zhang et al 2018) learned modalities content and user features for social image popularity prediction.…”
Section: Related Workmentioning
confidence: 99%
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“…Piotrkowicz et al predicted popularity of news articles using only headline features (Piotrkowicz et al 2017). Sanjo et al proposed a visual-semantic fusion model for online recipe popularity prediction, leveraging image and short text features in recipes (Sanjo and Katsurai 2017). User-guided hierarchical attention network (Zhang et al 2018) learned modalities content and user features for social image popularity prediction.…”
Section: Related Workmentioning
confidence: 99%
“…On the other hand, recent works have proved the effectiveness of content features in the popularity prediction, such as short text descriptions, titles and images (Zhang et al 2018;Piotrkowicz et al 2017;Sanjo and Katsurai 2017). However, online articles are usually long texts which are non-trivial to model, and diverse forms of meta-data features further complicate the content feature modeling.…”
Section: Introductionmentioning
confidence: 99%
“…Users' needs give rise to smart cooking-oriented tasks that contribute towards the definition of computational cooking as a research field by itself [1]. Indeed, the research community is very active in investigating issues regarding food-related tasks, such as ingredient identification [8], recipe recommendation [11], or recipe popularity prediction [35]. A first line of work consists in leveraging the semantics behind recipe texts and images using deep learning approaches [34,35].…”
Section: Related Work 21 Computational Cookingmentioning
confidence: 99%
“…Designing powerful tools that support cooking activities has become an attractive research field in recent years due to the growing interest of users to eat home-made food and share recipes on social platforms [35]. These massive amounts of data shared on devoted sites, such as All Recipes 1 , allow gathering food-related data including text recipes, images, videos, and/or user preferences.…”
Section: Introductionmentioning
confidence: 99%
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